Mode analysis of heuristic behavior of searching for multimodal optimum point

Energy Technology Data Exchange (ETDEWEB)

Kamei, K; Araki, Y; Inoue, K

1982-01-01

Describes an experimental study of a heuristic behavior of searching for the global optimum (maximum) point of a two-dimensional, multimodal, nonlinear and unknown function. First, the authors define three modes dealing with the trial purposes, called the purpose modes and show the heuristic search behaviors expressed by the purpose modes which the human subjects select in the search experiments. Second, the authors classify the heuristic search behaviors into three types according to the mode transitions and extracts eight states of searches which cause the mode transitions. Third, a model of the heuristic search behavior is composed of the eight mode transitions. The analysis of the heuristic search behaviors by use of the purpose modes plays an important role in the heuristic search techniques. 6 references.

Theory of Randomized Search Heuristics in Combinatorial Optimization

DEFF Research Database (Denmark)

The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS), the Metr......The rigorous mathematical analysis of randomized search heuristics(RSHs) with respect to their expected runtime is a growing research area where many results have been obtained in recent years. This class of heuristics includes well-known approaches such as Randomized Local Search (RLS...... analysis of randomized algorithms to RSHs. Mostly, the expected runtime of RSHs on selected problems is analzyed. Thereby, we understand why and when RSHs are efficient optimizers and, conversely, when they cannot be efficient. The tutorial will give an overview on the analysis of RSHs for solving...

Integer programming formulation and variable neighborhood search metaheuristic for the multiproduct pipeline scheduling problem

Energy Technology Data Exchange (ETDEWEB)

Souza Filho, Erito M.; Bahiense, Laura; Ferreira Filho, Virgilio J.M. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE); Lima, Leonardo [Centro Federal de Educacao Tecnologica Celso Sukow da Fonseca (CEFET-RJ), Rio de Janeiro, RJ (Brazil)

2008-07-01

Pipeline are known as the most reliable and economical mode of transportation for petroleum and its derivatives, especially when large amounts of products have to be pumped for large distances. In this work we address the short-term schedule of a pipeline system comprising the distribution of several petroleum derivatives from a single oil refinery to several depots, connected to local consumer markets, through a single multi-product pipeline. We propose an integer linear programming formulation and a variable neighborhood search meta-heuristic in order to compare the performances of the exact and heuristic approaches to the problem. Computational tests in C language and MOSEL/XPRESS-MP language are performed over a real Brazilian pipeline system. (author)

Solving Large Clustering Problems with Meta-Heuristic Search

DEFF Research Database (Denmark)

Turkensteen, Marcel; Andersen, Kim Allan; Bang-Jensen, Jørgen

In Clustering Problems, groups of similar subjects are to be retrieved from data sets. In this paper, Clustering Problems with the frequently used Minimum Sum-of-Squares Criterion are solved using meta-heuristic search. Tabu search has proved to be a successful methodology for solving optimization...... problems, but applications to large clustering problems are rare. The simulated annealing heuristic has mainly been applied to relatively small instances. In this paper, we implement tabu search and simulated annealing approaches and compare them to the commonly used k-means approach. We find that the meta-heuristic...

A Computational Investigation of Heuristic Algorithms for 2-Edge-Connectivity Augmentation

DEFF Research Database (Denmark)

Bang-Jensen, Jørgen; Chiarandini, Marco; Morling, Peter

2010-01-01

an equivalent set covering   formulation.  The results indicate that exact solutions by means of a   basic integer programming model can be obtained in reasonably short   time even on networks with 800 vertices and around 287,000   edges. Alternatively, an advanced heuristic algorithm based on   subgradient...... programming, simple construction heuristics and   metaheuristics. As part of the design of heuristics, we consider   different neighborhood structures for local search, among which is a very   large scale neighborhood. In all cases, we exploit approaches through   the graph formulation as well as through...

General k-opt submoves for the Lin-Kernighan TSP heuristic

DEFF Research Database (Denmark)

Helsgaun, Keld

2009-01-01

Local search with k-exchange neighborhoods, k-opt, is the most widely used heuristic method for the traveling salesman problem (TSP). This paper presents an effective implementation of k-opt in LKH-2, a variant of the Lin–Kernighan TSP heuristic. The effectiveness of the implementation...

An Effective Implementation of K-opt Moves for the Lin-Kernighan TSP Heuristic

DEFF Research Database (Denmark)

Helsgaun, Keld

Local search with k-change neighborhoods, k-opt, is the most widely used heuristic method for the traveling salesman problem (TSP). This report presents an effective implementation of k-opt for the Lin- Kernighan TSP heuristic. The effectiveness of the implementation is demonstrated with extensive...

Efficient heuristics for maximum common substructure search.

Science.gov (United States)

Englert, Péter; Kovács, Péter

2015-05-26

Maximum common substructure search is a computationally hard optimization problem with diverse applications in the field of cheminformatics, including similarity search, lead optimization, molecule alignment, and clustering. Most of these applications have strict constraints on running time, so heuristic methods are often preferred. However, the development of an algorithm that is both fast enough and accurate enough for most practical purposes is still a challenge. Moreover, in some applications, the quality of a common substructure depends not only on its size but also on various topological features of the one-to-one atom correspondence it defines. Two state-of-the-art heuristic algorithms for finding maximum common substructures have been implemented at ChemAxon Ltd., and effective heuristics have been developed to improve both their efficiency and the relevance of the atom mappings they provide. The implementations have been thoroughly evaluated and compared with existing solutions (KCOMBU and Indigo). The heuristics have been found to greatly improve the performance and applicability of the algorithms. The purpose of this paper is to introduce the applied methods and present the experimental results.

Expected Fitness Gains of Randomized Search Heuristics for the Traveling Salesperson Problem.

Science.gov (United States)

Nallaperuma, Samadhi; Neumann, Frank; Sudholt, Dirk

2017-01-01

Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. The runtime analysis of randomized search heuristics has contributed tremendously to our theoretical understanding. Recently, randomized search heuristics have been examined regarding their achievable progress within a fixed-time budget. We follow this approach and present a fixed-budget analysis for an NP-hard combinatorial optimization problem. We consider the well-known Traveling Salesperson Problem (TSP) and analyze the fitness increase that randomized search heuristics are able to achieve within a given fixed-time budget. In particular, we analyze Manhattan and Euclidean TSP instances and Randomized Local Search (RLS), (1+1) EA and (1+[Formula: see text]) EA algorithms for the TSP in a smoothed complexity setting, and derive the lower bounds of the expected fitness gain for a specified number of generations.

A local search heuristic for the Multi-Commodity k-splittable Maximum Flow Problem

DEFF Research Database (Denmark)

Gamst, Mette

2014-01-01

, a local search heuristic for solving the problem is proposed. The heuristic is an iterative shortest path procedure on a reduced graph combined with a local search procedure to modify certain path flows and prioritize the different commodities. The heuristic is tested on benchmark instances from...

Heuristics for Relevancy Ranking of Earth Dataset Search Results

Science.gov (United States)

Lynnes, Christopher; Quinn, Patrick; Norton, James

2016-01-01

As the Variety of Earth science datasets increases, science researchers find it more challenging to discover and select the datasets that best fit their needs. The most common way of search providers to address this problem is to rank the datasets returned for a query by their likely relevance to the user. Large web page search engines typically use text matching supplemented with reverse link counts, semantic annotations and user intent modeling. However, this produces uneven results when applied to dataset metadata records simply externalized as a web page. Fortunately, data and search provides have decades of experience in serving data user communities, allowing them to form heuristics that leverage the structure in the metadata together with knowledge about the user community. Some of these heuristics include specific ways of matching the user input to the essential measurements in the dataset and determining overlaps of time range and spatial areas. Heuristics based on the novelty of the datasets can prioritize later, better versions of data over similar predecessors. And knowledge of how different user types and communities use data can be brought to bear in cases where characteristics of the user (discipline, expertise) or their intent (applications, research) can be divined. The Earth Observing System Data and Information System has begun implementing some of these heuristics in the relevancy algorithm of its Common Metadata Repository search engine.

A variable neighborhood descent based heuristic to solve the capacitated location-routing problem

Directory of Open Access Journals (Sweden)

M. S. Jabal-Ameli

2011-01-01

Full Text Available Location-routing problem (LRP is established as a new research area in the context of location analysis. The primary concern of LRP is on locating facilities and routing of vehicles among established facilities and existing demand points. In this work, we address the capacitated LRP which arises in many practical applications within logistics and supply chain management. The objective is to minimize the overall system costs which include the fixed costs of opening depots and using vehicles at each depot site, and the variable costs associated with delivery activities. A novel heuristic is proposed which is based on variable neighborhood descent (VND algorithm to solve the resulted problem. The computational study indicates that the proposed VND based heuristic is highly competitive with the existing solution algorithms in terms of solution quality.

Three hybridization models based on local search scheme for job shop scheduling problem

Science.gov (United States)

Balbi Fraga, Tatiana

2015-05-01

This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

A flow-first route-next heuristic for liner shipping network design

DEFF Research Database (Denmark)

Krogsgaard, Alexander; Pisinger, David; Thorsen, Jesper

2018-01-01

Having a well-designed liner shipping network is paramount to ensure competitive freight rates, adequate capacity on trade-lanes, and reasonable transportation times.The most successful algorithms for liner shipping network design make use of a two-phase approach, where they first design the routes...... different operators are used to modify the network. Since each iteration of the local search method involves solving a very complex multi-commodity flow problem to route the containers through the network, the flow problem is solved heuristically by use of a fast Lagrange heuristic. Although the Lagrange...... heuristic for flowing containers is 2–5% from the optimal solution, the solution quality is sufficiently good to guide the variable neighborhood search method in designing the network. Computational results are reported, showing that the developed heuristic is able to find improved solutions for large...

Perceived breast cancer risk: heuristic reasoning and search for a dominance structure.

Science.gov (United States)

Katapodi, Maria C; Facione, Noreen C; Humphreys, Janice C; Dodd, Marylin J

2005-01-01

Studies suggest that people construct their risk perceptions by using inferential rules called heuristics. The purpose of this study was to identify heuristics that influence perceived breast cancer risk. We examined 11 interviews from women of diverse ethnic/cultural backgrounds who were recruited from community settings. Narratives in which women elaborated about their own breast cancer risk were analyzed with Argument and Heuristic Reasoning Analysis methodology, which is based on applied logic. The availability, simulation, representativeness, affect, and perceived control heuristics, and search for a dominance structure were commonly used for making risk assessments. Risk assessments were based on experiences with an abnormal breast symptom, experiences with affected family members and friends, beliefs about living a healthy lifestyle, and trust in health providers. Assessment of the potential threat of a breast symptom was facilitated by the search for a dominance structure. Experiences with family members and friends were incorporated into risk assessments through the availability, simulation, representativeness, and affect heuristics. Mistrust in health providers led to an inappropriate dependence on the perceived control heuristic. Identified heuristics appear to create predictable biases and suggest that perceived breast cancer risk is based on common cognitive patterns.

Gaussian variable neighborhood search for the file transfer scheduling problem

Directory of Open Access Journals (Sweden)

Dražić Zorica

2016-01-01

Full Text Available This paper presents new modifications of Variable Neighborhood Search approach for solving the file transfer scheduling problem. To obtain better solutions in a small neighborhood of a current solution, we implement two new local search procedures. As Gaussian Variable Neighborhood Search showed promising results when solving continuous optimization problems, its implementation in solving the discrete file transfer scheduling problem is also presented. In order to apply this continuous optimization method to solve the discrete problem, mapping of uncountable set of feasible solutions into a finite set is performed. Both local search modifications gave better results for the large size instances, as well as better average performance for medium and large size instances. One local search modification achieved significant acceleration of the algorithm. The numerical experiments showed that the results obtained by Gaussian modifications are comparable with the results obtained by standard VNS based algorithms, developed for combinatorial optimization. In some cases Gaussian modifications gave even better results. [Projekat Ministarstava nauke Republike Srbije, br. 174010

A comparative study of the A* heuristic search algorithm used to solve efficiently a puzzle game

Science.gov (United States)

Iordan, A. E.

2018-01-01

The puzzle game presented in this paper consists in polyhedra (prisms, pyramids or pyramidal frustums) which can be moved using the free available spaces. The problem requires to be found the minimum number of movements in order the game reaches to a goal configuration starting from an initial configuration. Because the problem is enough complex, the principal difficulty in solving it is given by dimension of search space, that leads to necessity of a heuristic search. The improving of the search method consists into determination of a strong estimation by the heuristic function which will guide the search process to the most promising side of the search tree. The comparative study is realized among Manhattan heuristic and the Hamming heuristic using A* search algorithm implemented in Java. This paper also presents the necessary stages in object oriented development of a software used to solve efficiently this puzzle game. The modelling of the software is achieved through specific UML diagrams representing the phases of analysis, design and implementation, the system thus being described in a clear and practical manner. With the purpose to confirm the theoretical results which demonstrates that Manhattan heuristic is more efficient was used space complexity criterion. The space complexity was measured by the number of generated nodes from the search tree, by the number of the expanded nodes and by the effective branching factor. From the experimental results obtained by using the Manhattan heuristic, improvements were observed regarding space complexity of A* algorithm versus Hamming heuristic.

A novel heuristic algorithm for capacitated vehicle routing problem

Science.gov (United States)

Kır, Sena; Yazgan, Harun Reşit; Tüncel, Emre

2017-09-01

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic algorithm based on the tabu search and adaptive large neighborhood search (ALNS) with several specifically designed operators and features to solve the capacitated vehicle routing problem (CVRP). The effectiveness of the proposed algorithm was illustrated on the benchmark problems. The algorithm provides a better performance on large-scaled instances and gained advantage in terms of CPU time. In addition, we solved a real-life CVRP using the proposed algorithm and found the encouraging results by comparison with the current situation that the company is in.

Heuristic method for searching global maximum of multimodal unknown function

Energy Technology Data Exchange (ETDEWEB)

Kamei, K; Araki, Y; Inoue, K

1983-06-01

The method is composed of three kinds of searches. They are called g (grasping)-mode search, f (finding)-mode search and c (confirming)-mode search. In the g-mode search and the c-mode search, a heuristic method is used which was extracted from search behaviors of human subjects. In f-mode search, the simplex method is used which is well known as a search method for unimodal unknown function. Each mode search and its transitions are shown in the form of flowchart. The numerical results for one-dimensional through six-dimensional multimodal functions prove the proposed search method to be an effective one. 11 references.

A Heuristic Hierarchical Scheme for Academic Search and Retrieval

DEFF Research Database (Denmark)

Amolochitis, Emmanouil; Christou, Ioannis T.; Tan, Zheng-Hua

2013-01-01

and a graph-theoretic computed score that relates the paper’s index terms with each other. We designed and developed a meta-search engine that submits user queries to standard digital repositories of academic publications and re-ranks the repository results using the hierarchical heuristic scheme. We evaluate......, and by more than 907.5% in terms of LEX. We also re-rank the top-10 results of a subset of the original 58 user queries produced by Google Scholar, Microsoft Academic Search, and ArnetMiner; the results show that PubSearch compares very well against these search engines as well. The proposed scheme can...... be easily plugged in any existing search engine for retrieval of academic publications....

Pylogeny: an open-source Python framework for phylogenetic tree reconstruction and search space heuristics

Directory of Open Access Journals (Sweden)

Alexander Safatli

2015-06-01

Full Text Available Summary. Pylogeny is a cross-platform library for the Python programming language that provides an object-oriented application programming interface for phylogenetic heuristic searches. Its primary function is to permit both heuristic search and analysis of the phylogenetic tree search space, as well as to enable the design of novel algorithms to search this space. To this end, the framework supports the structural manipulation of phylogenetic trees, in particular using rearrangement operators such as NNI, SPR, and TBR, the scoring of trees using parsimony and likelihood methods, the construction of a tree search space graph, and the programmatic execution of a few existing heuristic programs. The library supports a range of common phylogenetic file formats and can be used for both nucleotide and protein data. Furthermore, it is also capable of supporting GPU likelihood calculation on nucleotide character data through the BEAGLE library.Availability. Existing development and source code is available for contribution and for download by the public from GitHub (http://github.com/AlexSafatli/Pylogeny. A stable release of this framework is available for download through PyPi (Python Package Index at http://pypi.python.org/pypi/pylogeny.

An Adaptive Large Neighborhood Search Algorithm for the Resource-constrained Project Scheduling Problem

DEFF Research Database (Denmark)

Muller, Laurent Flindt

2009-01-01

We present an application of an Adaptive Large Neighborhood Search (ALNS) algorithm to the Resource-constrained Project Scheduling Problem (RCPSP). The ALNS framework was first proposed by Pisinger and Røpke [19] and can be described as a large neighborhood search algorithm with an adaptive layer......, where a set of destroy/repair neighborhoods compete to modify the current solution in each iteration of the algorithm. Experiments are performed on the wellknown J30, J60 and J120 benchmark instances, which show that the proposed algorithm is competitive and confirms the strength of the ALNS framework...

Concentrated Hitting Times of Randomized Search Heuristics with Variable Drift

DEFF Research Database (Denmark)

Lehre, Per Kristian; Witt, Carsten

2014-01-01

Drift analysis is one of the state-of-the-art techniques for the runtime analysis of randomized search heuristics (RSHs) such as evolutionary algorithms (EAs), simulated annealing etc. The vast majority of existing drift theorems yield bounds on the expected value of the hitting time for a target...

Optimizing Linear Functions with Randomized Search Heuristics - The Robustness of Mutation

DEFF Research Database (Denmark)

Witt, Carsten

2012-01-01

The analysis of randomized search heuristics on classes of functions is fundamental for the understanding of the underlying stochastic process and the development of suitable proof techniques. Recently, remarkable progress has been made in bounding the expected optimization time of the simple (1...

A hybridised variable neighbourhood tabu search heuristic to increase security in a utility network

International Nuclear Information System (INIS)

Janssens, Jochen; Talarico, Luca; Sörensen, Kenneth

2016-01-01

We propose a decision model aimed at increasing security in a utility network (e.g., electricity, gas, water or communication network). The network is modelled as a graph, the edges of which are unreliable. We assume that all edges (e.g., pipes, cables) have a certain, not necessarily equal, probability of failure, which can be reduced by selecting edge-specific security strategies. We develop a mathematical programming model and a metaheuristic approach that uses a greedy random adaptive search procedure to find an initial solution and uses tabu search hybridised with iterated local search and a variable neighbourhood descend heuristic to improve this solution. The main goal is to reduce the risk of service failure between an origin and a destination node by selecting the right combination of security measures for each network edge given a limited security budget. - Highlights: • A decision model aimed at increasing security in a utility network is proposed. • The goal is to reduce the risk of service failure given a limited security budget. • An exact approach and a variable neighbourhood tabu search heuristic are developed. • A generator for realistic networks is built and used to test the solution methods. • The hybridised heuristic reduces the total risk on average with 32%.

Heuristic space diversity control for improved meta-hyper-heuristic performance

CSIR Research Space (South Africa)

Grobler, J

2015-04-01

Full Text Available This paper expands on the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm in search of greater performance benefits...

A Heuristic Design Information Sharing Framework for Hard Discrete Optimization Problems

National Research Council Canada - National Science Library

Jacobson, Sheldon H

2007-01-01

.... This framework has been used to gain new insights into neighborhood structure designs that allow different neighborhood functions to share information when using the same heuristic applied to the same problem...

A proposed heuristic methodology for searching reloading pattern

International Nuclear Information System (INIS)

Choi, K. Y.; Yoon, Y. K.

1993-01-01

A new heuristic method for loading pattern search has been developed to overcome shortcomings of the algorithmic approach. To reduce the size of vast solution space, general shuffling rules, a regionwise shuffling method, and a pattern grouping method were introduced. The entropy theory was applied to classify possible loading patterns into groups with similarity between them. The pattern search program was implemented with use of the PROLOG language. A two-group nodal code MEDIUM-2D was used for analysis of power distribution in the core. The above mentioned methodology has been tested to show effectiveness in reducing of solution space down to a few hundred pattern groups. Burnable poison rods were then arranged in each pattern group in accordance with burnable poison distribution rules, which led to further reduction of the solution space to several scores of acceptable pattern groups. The method of maximizing cycle length (MCL) and minimizing power-peaking factor (MPF) were applied to search for specific useful loading patterns from the acceptable pattern groups. Thus, several specific loading patterns that have low power-peaking factor and large cycle length were successfully searched from the selected pattern groups. (Author)

Using heuristic search for optimizing maintenance plans

International Nuclear Information System (INIS)

Mutanen, Teemu

2012-01-01

This work addresses the maintenance action selection process. Maintenance personnel need to evaluate maintenance actions and costs to keep the machines in working condition. Group of actions are evaluated together as maintenance plans. The maintenance plans as output provide information to the user about which actions to take if any and what future actions should be prepared for. The heuristic search method is implemented as part of general use toolbox for analysis of measurements from movable work machines. Impacts from machine's usage restrictions and maintenance activities are analysed. The results show that once put on a temporal perspective, the prioritized order of the actions is different and provide additional information to the user.

Structure optimization by heuristic algorithm in a coarse-grained off-lattice model

International Nuclear Information System (INIS)

Jing-Fa, Liu

2009-01-01

A heuristic algorithm is presented for a three-dimensional off-lattice AB model consisting of hydrophobic (A) and hydrophilic (B) residues in Fibonacci sequences. By incorporating extra energy contributions into the original potential function, we convert the constrained optimization problem of AB model into an unconstrained optimization problem which can be solved by the gradient method. After the gradient minimization leads to the basins of the local energy minima, the heuristic off-trap strategy and subsequent neighborhood search mechanism are then proposed to get out of local minima and search for the lower-energy configurations. Furthermore, in order to improve the efficiency of the proposed algorithm, we apply the improved version called the new PERM with importance sampling (nPERMis) of the chain-growth algorithm, pruned-enriched-Rosenbluth method (PERM), to face-centered-cubic (FCC)-lattice to produce the initial configurations. The numerical results show that the proposed methods are very promising for finding the ground states of proteins. In several cases, we found the ground state energies are lower than the best values reported in the present literature

Fitness levels with tail bounds for the analysis of randomized search heuristics

DEFF Research Database (Denmark)

Witt, Carsten

2014-01-01

The fitness-level method, also called the method of f-based partitions, is an intuitive and widely used technique for the running time analysis of randomized search heuristics. It was originally defined to prove upper and lower bounds on the expected running time. Recently, upper tail bounds were...

International Timetabling Competition 2011: An Adaptive Large Neighborhood Search algorithm

DEFF Research Database (Denmark)

Sørensen, Matias; Kristiansen, Simon; Stidsen, Thomas Riis

2012-01-01

An algorithm based on Adaptive Large Neighborhood Search (ALNS) for solving the generalized High School Timetabling problem in XHSTT-format (Post et al (2012a)) is presented. This algorithm was among the nalists of round 2 of the International Timetabling Competition 2011 (ITC2011). For problem...

AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search

Science.gov (United States)

1976-07-01

deficiency . The idea of "Intuitions" facets was a flop. Intuitions were meant to model reality, at least little pieces of it, so that AM could...Discovery in Mathematic, as Heuristic Search -323- s Tk2 ** Check examples of Single-ADD, because many examples have recently been found, but not yet

Intelligent System Design Using Hyper-Heuristics

Directory of Open Access Journals (Sweden)

Nelishia Pillay

2015-07-01

Full Text Available Determining the most appropriate search method or artificial intelligence technique to solve a problem is not always evident and usually requires implementation of the different approaches to ascertain this. In some instances a single approach may not be sufficient and hybridization of methods may be needed to find a solution. This process can be time consuming. The paper proposes the use of hyper-heuristics as a means of identifying which method or combination of approaches is needed to solve a problem. The research presented forms part of a larger initiative aimed at using hyper-heuristics to develop intelligent hybrid systems. As an initial step in this direction, this paper investigates this for classical artificial intelligence uninformed and informed search methods, namely depth first search, breadth first search, best first search, hill-climbing and the A* algorithm. The hyper-heuristic determines the search or combination of searches to use to solve the problem. An evolutionary algorithm hyper-heuristic is implemented for this purpose and its performance is evaluated in solving the 8-Puzzle, Towers of Hanoi and Blocks World problems. The hyper-heuristic employs a generational evolutionary algorithm which iteratively refines an initial population using tournament selection to select parents, which the mutation and crossover operators are applied to for regeneration. The hyper-heuristic was able to identify a search or combination of searches to produce solutions for the twenty 8-Puzzle, five Towers of Hanoi and five Blocks World problems. Furthermore, admissible solutions were produced for all problem instances.

An Adaptive Large Neighborhood Search Algorithm for the Multi-mode RCPSP

DEFF Research Database (Denmark)

Muller, Laurent Flindt

We present an Adaptive Large Neighborhood Search algorithm for the Multi-mode Resource-Constrained Project Scheduling Problem (MRCPSP). We incorporate techniques for deriving additional precedence relations and propose a new method, so-called mode-diminution, for removing modes during execution...

A learning heuristic for space mapping and searching self-organizing systems using adaptive mesh refinement

Science.gov (United States)

Phillips, Carolyn L.

2014-09-01

In a complex self-organizing system, small changes in the interactions between the system's components can result in different emergent macrostructures or macrobehavior. In chemical engineering and material science, such spontaneously self-assembling systems, using polymers, nanoscale or colloidal-scale particles, DNA, or other precursors, are an attractive way to create materials that are precisely engineered at a fine scale. Changes to the interactions can often be described by a set of parameters. Different contiguous regions in this parameter space correspond to different ordered states. Since these ordered states are emergent, often experiment, not analysis, is necessary to create a diagram of ordered states over the parameter space. By issuing queries to points in the parameter space (e.g., performing a computational or physical experiment), ordered states can be discovered and mapped. Queries can be costly in terms of resources or time, however. In general, one would like to learn the most information using the fewest queries. Here we introduce a learning heuristic for issuing queries to map and search a two-dimensional parameter space. Using a method inspired by adaptive mesh refinement, the heuristic iteratively issues batches of queries to be executed in parallel based on past information. By adjusting the search criteria, different types of searches (for example, a uniform search, exploring boundaries, sampling all regions equally) can be flexibly implemented. We show that this method will densely search the space, while preferentially targeting certain features. Using numerical examples, including a study simulating the self-assembly of complex crystals, we show how this heuristic can discover new regions and map boundaries more accurately than a uniformly distributed set of queries.

A reduced-cost iterated local search heuristic for the fixed-charge transportation problem

NARCIS (Netherlands)

Buson, Erika; Roberti, Roberto; Toth, Paolo

2014-01-01

The fixed-charge transportation problem (FCTP) is a generalization of the transportation problem where an additional fixed cost is paid for sending a flow from an origin to a destination. We propose an iterated local search heuristic based on the utilization of reduced costs for guiding the restart

Application of a heuristic search method for generation of fuel reload configurations

International Nuclear Information System (INIS)

Galperin, A.; Nissan, E.

1988-01-01

A computerized heuristic search method for the generation and optimization of fuel reload configurations is proposed and investigated. The heuristic knowledge is expressed modularly in the form of ''IF-THEN'' production rules. The method was implemented in a program coded in the Franz LISP programming language and executed under the UNIX operating system. A test problem was formulated, based on a typical light water reactor reload problem with a few simplifications assumed, in order to allow formulation of the reload strategy into a relatively small number of rules. A computer run of the problem was performed with a VAX-780 machine. A set of 312 solutions was generated in -- 20 min of execution time. Testing of a few arbitrarily chosen configurations demonstrated reasonably good performance for the computer-generated solutions. A computerized generator of reload configurations may be used for the fast generation or modification of reload patterns and as a tool for the formulation, tuning, and testing of the heuristic knowledge rules used by an ''expert'' fuel manager

A tabu-search heuristic for solving the multi-depot vehicle scheduling problem

Directory of Open Access Journals (Sweden)

Gilmar D'Agostini Oliveira Casalinho

2014-08-01

Full Text Available Currently the logistical problems are relying quite significantly on Operational Research in order to achieve greater efficiency in their operations. Among the problems related to the vehicles scheduling in a logistics system, the Multiple Depot Vehicle Scheduling Problem (MDVSP has been addressed in several studies. The MDVSP presupposes the existence of depots that affect the planning of sequences to which travel must be performed. Often, exact methods cannot solve large instances encountered in practice and in order to take them into account, several heuristic approaches are being developed. The aim of this study was thus to solve the MDVSP using a meta-heuristic based on tabu-search method. The main motivation for this work came from the indication that only recently the use of meta-heuristics is being applied to MDVSP context (Pepin et al. 2008 and, also, the limitations listed by Rohde (2008 in his study, which used the branch-and-bound in one of the steps of the heuristic presented to solve the problem, which has increased the time resolution. The research method for solving this problem was based on adaptations of traditional techniques of Operational Research, and provided resolutions presenting very competitive results for the MDVSP such as the cost of the objective function, number of vehicles used and computational time.

A Pareto-Based Adaptive Variable Neighborhood Search for Biobjective Hybrid Flow Shop Scheduling Problem with Sequence-Dependent Setup Time

Directory of Open Access Journals (Sweden)

Huixin Tian

2016-01-01

Full Text Available Different from most researches focused on the single objective hybrid flowshop scheduling (HFS problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.

Automatic Generation of Heuristics for Scheduling

Science.gov (United States)

Morris, Robert A.; Bresina, John L.; Rodgers, Stuart M.

1997-01-01

This paper presents a technique, called GenH, that automatically generates search heuristics for scheduling problems. The impetus for developing this technique is the growing consensus that heuristics encode advice that is, at best, useful in solving most, or typical, problem instances, and, at worst, useful in solving only a narrowly defined set of instances. In either case, heuristic problem solvers, to be broadly applicable, should have a means of automatically adjusting to the idiosyncrasies of each problem instance. GenH generates a search heuristic for a given problem instance by hill-climbing in the space of possible multi-attribute heuristics, where the evaluation of a candidate heuristic is based on the quality of the solution found under its guidance. We present empirical results obtained by applying GenH to the real world problem of telescope observation scheduling. These results demonstrate that GenH is a simple and effective way of improving the performance of an heuristic scheduler.

Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy.

Science.gov (United States)

Blumenthal-Barby, J S; Krieger, Heather

2015-05-01

The role of cognitive biases and heuristics in medical decision making is of growing interest. The purpose of this study was to determine whether studies on cognitive biases and heuristics in medical decision making are based on actual or hypothetical decisions and are conducted with populations that are representative of those who typically make the medical decision; to categorize the types of cognitive biases and heuristics found and whether they are found in patients or in medical personnel; and to critically review the studies based on standard methodological quality criteria. Data sources were original, peer-reviewed, empirical studies on cognitive biases and heuristics in medical decision making found in Ovid Medline, PsycINFO, and the CINAHL databases published in 1980-2013. Predefined exclusion criteria were used to identify 213 studies. During data extraction, information was collected on type of bias or heuristic studied, respondent population, decision type, study type (actual or hypothetical), study method, and study conclusion. Of the 213 studies analyzed, 164 (77%) were based on hypothetical vignettes, and 175 (82%) were conducted with representative populations. Nineteen types of cognitive biases and heuristics were found. Only 34% of studies (n = 73) investigated medical personnel, and 68% (n = 145) confirmed the presence of a bias or heuristic. Each methodological quality criterion was satisfied by more than 50% of the studies, except for sample size and validated instruments/questions. Limitations are that existing terms were used to inform search terms, and study inclusion criteria focused strictly on decision making. Most of the studies on biases and heuristics in medical decision making are based on hypothetical vignettes, raising concerns about applicability of these findings to actual decision making. Biases and heuristics have been underinvestigated in medical personnel compared with patients. © The Author(s) 2014.

Hierarchical heuristic search using a Gaussian mixture model for UAV coverage planning.

Science.gov (United States)

Lin, Lanny; Goodrich, Michael A

2014-12-01

During unmanned aerial vehicle (UAV) search missions, efficient use of UAV flight time requires flight paths that maximize the probability of finding the desired subject. The probability of detecting the desired subject based on UAV sensor information can vary in different search areas due to environment elements like varying vegetation density or lighting conditions, making it likely that the UAV can only partially detect the subject. This adds another dimension of complexity to the already difficult (NP-Hard) problem of finding an optimal search path. We present a new class of algorithms that account for partial detection in the form of a task difficulty map and produce paths that approximate the payoff of optimal solutions. The algorithms use the mode goodness ratio heuristic that uses a Gaussian mixture model to prioritize search subregions. The algorithms search for effective paths through the parameter space at different levels of resolution. We compare the performance of the new algorithms against two published algorithms (Bourgault's algorithm and LHC-GW-CONV algorithm) in simulated searches with three real search and rescue scenarios, and show that the new algorithms outperform existing algorithms significantly and can yield efficient paths that yield payoffs near the optimal.

Proximity search heuristics for wind farm optimal layout

DEFF Research Database (Denmark)

Fischetti, Martina; Monaci, Michele

2016-01-01

A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently...

Case-Based Reasoning as a Heuristic Selector in a Hyper-Heuristic for Course Timetabling Problems

OpenAIRE

Petrovic, Sanja; Qu, Rong

2002-01-01

This paper studies Knowledge Discovery (KD) using Tabu Search and Hill Climbing within Case-Based Reasoning (CBR) as a hyper-heuristic method for course timetabling problems. The aim of the hyper-heuristic is to choose the best heuristic(s) for given timetabling problems according to the knowledge stored in the case base. KD in CBR is a 2-stage iterative process on both case representation and the case base. Experimental results are analysed and related research issues for future work are dis...

Heuristic Search for Planning with Different Forced Goal-Ordering Constraints

Directory of Open Access Journals (Sweden)

Jiangfeng Luo

2013-01-01

Full Text Available Planning with forced goal-ordering (FGO constraints has been proposed many times over the years, but there are still major difficulties in realizing these FGOs in plan generation. In certain planning domains, all the FGOs exist in the initial state. No matter which approach is adopted to achieve a subgoal, all the subgoals should be achieved in a given sequence from the initial state. Otherwise, the planning may arrive at a deadlock. For some other planning domains, there is no FGO in the initial state. However, FGO may occur during the planning process if certain subgoal is achieved by an inappropriate approach. This paper contributes to illustrate that it is the excludable constraints among the goal achievement operations (GAO of different subgoals that introduce the FGOs into the planning problem, and planning with FGO is still a challenge for the heuristic search based planners. Then, a novel multistep forward search algorithm is proposed which can solve the planning problem with different FGOs efficiently.

Heuristic rules analysis on the fuel cells design using greedy search

International Nuclear Information System (INIS)

Ortiz, J. J.; Castillo, J. A.; Montes, J. L.; Hernandez, J. L.

2009-10-01

This work approaches the study of one of the heuristic rules of fuel cells design for boiling water nuclear reactors. This rule requires that the minor uranium enrichment is placed in the corners of the fuel cell. Also the search greedy is applied for the fuel cells design where explicitly does not take in count this rule, allowing the possibility to place any uranium enrichment with the condition that it does not contain gadolinium. Results are shown in the quality of the obtained cell by search greedy when it considers the rule and when not. The cell quality is measured with the value of the power pick factor obtained, as well as of the neutrons multiplication factor in an infinite medium. Cells were analyzed with 1 and 2 gadolinium concentrations low operation conditions at 120% of the nominal power of the reactors of the nuclear power plant of Laguna Verde. The results show that not to consider the rule in cells with a single gadolinium concentration, it has as repercussion that the greedy search has a minor performance. On the other hand with cells of two gadolinium concentrations, the performance of the greedy search was better. (Author)

Hyper-heuristics with low level parameter adaptation.

Science.gov (United States)

Ren, Zhilei; Jiang, He; Xuan, Jifeng; Luo, Zhongxuan

2012-01-01

Recent years have witnessed the great success of hyper-heuristics applying to numerous real-world applications. Hyper-heuristics raise the generality of search methodologies by manipulating a set of low level heuristics (LLHs) to solve problems, and aim to automate the algorithm design process. However, those LLHs are usually parameterized, which may contradict the domain independent motivation of hyper-heuristics. In this paper, we show how to automatically maintain low level parameters (LLPs) using a hyper-heuristic with LLP adaptation (AD-HH), and exemplify the feasibility of AD-HH by adaptively maintaining the LLPs for two hyper-heuristic models. Furthermore, aiming at tackling the search space expansion due to the LLP adaptation, we apply a heuristic space reduction (SAR) mechanism to improve the AD-HH framework. The integration of the LLP adaptation and the SAR mechanism is able to explore the heuristic space more effectively and efficiently. To evaluate the performance of the proposed algorithms, we choose the p-median problem as a case study. The empirical results show that with the adaptation of the LLPs and the SAR mechanism, the proposed algorithms are able to achieve competitive results over the three heterogeneous classes of benchmark instances.

A meta-heuristic method for solving scheduling problem: crow search algorithm

Science.gov (United States)

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

2018-04-01

Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.

Robust total energy demand estimation with a hybrid Variable Neighborhood Search – Extreme Learning Machine algorithm

International Nuclear Information System (INIS)

Sánchez-Oro, J.; Duarte, A.; Salcedo-Sanz, S.

2016-01-01

Highlights: • The total energy demand in Spain is estimated with a Variable Neighborhood algorithm. • Socio-economic variables are used, and one year ahead prediction horizon is considered. • Improvement of the prediction with an Extreme Learning Machine network is considered. • Experiments are carried out in real data for the case of Spain. - Abstract: Energy demand prediction is an important problem whose solution is evaluated by policy makers in order to take key decisions affecting the economy of a country. A number of previous approaches to improve the quality of this estimation have been proposed in the last decade, the majority of them applying different machine learning techniques. In this paper, the performance of a robust hybrid approach, composed of a Variable Neighborhood Search algorithm and a new class of neural network called Extreme Learning Machine, is discussed. The Variable Neighborhood Search algorithm is focused on obtaining the most relevant features among the set of initial ones, by including an exponential prediction model. While previous approaches consider that the number of macroeconomic variables used for prediction is a parameter of the algorithm (i.e., it is fixed a priori), the proposed Variable Neighborhood Search method optimizes both: the number of variables and the best ones. After this first step of feature selection, an Extreme Learning Machine network is applied to obtain the final energy demand prediction. Experiments in a real case of energy demand estimation in Spain show the excellent performance of the proposed approach. In particular, the whole method obtains an estimation of the energy demand with an error lower than 2%, even when considering the crisis years, which are a real challenge.

Modeling reproductive decisions with simple heuristics

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Peter Todd

2013-10-01

Full Text Available BACKGROUND Many of the reproductive decisions that humans make happen without much planning or forethought, arising instead through the use of simple choice rules or heuristics that involve relatively little information and processing. Nonetheless, these heuristic-guided decisions are typically beneficial, owing to humans' ecological rationality - the evolved fit between our constrained decision mechanisms and the adaptive problems we face. OBJECTIVE This paper reviews research on the ecological rationality of human decision making in the domain of reproduction, showing how fertility-related decisions are commonly made using various simple heuristics matched to the structure of the environment in which they are applied, rather than being made with information-hungry mechanisms based on optimization or rational economic choice. METHODS First, heuristics for sequential mate search are covered; these heuristics determine when to stop the process of mate search by deciding that a good-enough mate who is also mutually interested has been found, using a process of aspiration-level setting and assessing. These models are tested via computer simulation and comparison to demographic age-at-first-marriage data. Next, a heuristic process of feature-based mate comparison and choice is discussed, in which mate choices are determined by a simple process of feature-matching with relaxing standards over time. Parental investment heuristics used to divide resources among offspring are summarized. Finally, methods for testing the use of such mate choice heuristics in a specific population over time are then described.

Multiobjective Variable Neighborhood Search algorithm for scheduling independent jobs on computational grid

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S. Selvi

2015-07-01

Full Text Available Grid computing solves high performance and high-throughput computing problems through sharing resources ranging from personal computers to super computers distributed around the world. As the grid environments facilitate distributed computation, the scheduling of grid jobs has become an important issue. In this paper, an investigation on implementing Multiobjective Variable Neighborhood Search (MVNS algorithm for scheduling independent jobs on computational grid is carried out. The performance of the proposed algorithm has been evaluated with Min–Min algorithm, Simulated Annealing (SA and Greedy Randomized Adaptive Search Procedure (GRASP algorithm. Simulation results show that MVNS algorithm generally performs better than other metaheuristics methods.

A hybrid guided neighborhood search for the disjunctively constrained knapsack problem

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Mhand Hifi

2015-12-01

Full Text Available In this paper, we investigate the use of a hybrid guided neighborhood search for solving the disjunctively constrained knapsack problem. The studied problem may be viewed as a combination of two NP-hard combinatorial optimization problems: the weighted-independent set and the classical binary knapsack. The proposed algorithm is a hybrid approach that combines both deterministic and random local searches. The deterministic local search is based on a descent method, where both building and exploring procedures are alternatively used for improving the solution at hand. In order to escape from a local optima, a random local search strategy is introduced which is based on a modified ant colony optimization system. During the search process, the ant colony optimization system tries to diversify and to enhance the solutions using some informations collected from the previous iterations. Finally, the proposed algorithm is computationally analyzed on a set of benchmark instances available in the literature. The provided results are compared to those realized by both the Cplex solver and a recent algorithm of the literature. The computational part shows that the obtained results improve most existing solution values.

Sequence-based heuristics for faster annotation of non-coding RNA families.

Science.gov (United States)

Weinberg, Zasha; Ruzzo, Walter L

2006-01-01

Non-coding RNAs (ncRNAs) are functional RNA molecules that do not code for proteins. Covariance Models (CMs) are a useful statistical tool to find new members of an ncRNA gene family in a large genome database, using both sequence and, importantly, RNA secondary structure information. Unfortunately, CM searches are extremely slow. Previously, we created rigorous filters, which provably sacrifice none of a CM's accuracy, while making searches significantly faster for virtually all ncRNA families. However, these rigorous filters make searches slower than heuristics could be. In this paper we introduce profile HMM-based heuristic filters. We show that their accuracy is usually superior to heuristics based on BLAST. Moreover, we compared our heuristics with those used in tRNAscan-SE, whose heuristics incorporate a significant amount of work specific to tRNAs, where our heuristics are generic to any ncRNA. Performance was roughly comparable, so we expect that our heuristics provide a high-quality solution that--unlike family-specific solutions--can scale to hundreds of ncRNA families. The source code is available under GNU Public License at the supplementary web site.

The role of heuristics in automated theorem proving J.A Robinson's resolution principle

OpenAIRE

Coderschi, Roberto

1996-01-01

The aim of this paper is to show how J.A. Robinson's resolution principle was perceived and discussed in the AI community between the mid sixties and the first seventies. During this time the so called ``heuristic search paradigm" was still influential in the AI community, and both resolution principle and certain resolution based, apparently human-like, search strategies were matched with those problem solving heuristic procedures which were representative of the AI heuristic search paradigm.

Application of heuristic and machine-learning approach to engine model calibration

Science.gov (United States)

Cheng, Jie; Ryu, Kwang R.; Newman, C. E.; Davis, George C.

1993-03-01

Automation of engine model calibration procedures is a very challenging task because (1) the calibration process searches for a goal state in a huge, continuous state space, (2) calibration is often a lengthy and frustrating task because of complicated mutual interference among the target parameters, and (3) the calibration problem is heuristic by nature, and often heuristic knowledge for constraining a search cannot be easily acquired from domain experts. A combined heuristic and machine learning approach has, therefore, been adopted to improve the efficiency of model calibration. We developed an intelligent calibration program called ICALIB. It has been used on a daily basis for engine model applications, and has reduced the time required for model calibrations from many hours to a few minutes on average. In this paper, we describe the heuristic control strategies employed in ICALIB such as a hill-climbing search based on a state distance estimation function, incremental problem solution refinement by using a dynamic tolerance window, and calibration target parameter ordering for guiding the search. In addition, we present the application of a machine learning program called GID3* for automatic acquisition of heuristic rules for ordering target parameters.

A GENETIC ALGORITHM USING THE LOCAL SEARCH HEURISTIC IN FACILITIES LAYOUT PROBLEM: A MEMETİC ALGORİTHM APPROACH

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Orhan TÜRKBEY

2002-02-01

Full Text Available Memetic algorithms, which use local search techniques, are hybrid structured algorithms like genetic algorithms among evolutionary algorithms. In this study, for Quadratic Assignment Problem (QAP, a memetic structured algorithm using a local search heuristic like 2-opt is developed. Developed in the algorithm, a crossover operator that has not been used before for QAP is applied whereas, Eshelman procedure is used in order to increase thesolution variability. The developed memetic algorithm is applied on test problems taken from QAP-LIB, the results are compared with the present techniques in the literature.

An Elitist Multiobjective Tabu Search for Optimal Design of Groundwater Remediation Systems.

Science.gov (United States)

Yang, Yun; Wu, Jianfeng; Wang, Jinguo; Zhou, Zhifang

2017-11-01

This study presents a new multiobjective evolutionary algorithm (MOEA), the elitist multiobjective tabu search (EMOTS), and incorporates it with MODFLOW/MT3DMS to develop a groundwater simulation-optimization (SO) framework based on modular design for optimal design of groundwater remediation systems using pump-and-treat (PAT) technique. The most notable improvement of EMOTS over the original multiple objective tabu search (MOTS) lies in the elitist strategy, selection strategy, and neighborhood move rule. The elitist strategy is to maintain all nondominated solutions within later search process for better converging to the true Pareto front. The elitism-based selection operator is modified to choose two most remote solutions from current candidate list as seed solutions to increase the diversity of searching space. Moreover, neighborhood solutions are uniformly generated using the Latin hypercube sampling (LHS) in the bounded neighborhood space around each seed solution. To demonstrate the performance of the EMOTS, we consider a synthetic groundwater remediation example. Problem formulations consist of two objective functions with continuous decision variables of pumping rates while meeting water quality requirements. Especially, sensitivity analysis is evaluated through the synthetic case for determination of optimal combination of the heuristic parameters. Furthermore, the EMOTS is successfully applied to evaluate remediation options at the field site of the Massachusetts Military Reservation (MMR) in Cape Cod, Massachusetts. With both the hypothetical and the large-scale field remediation sites, the EMOTS-based SO framework is demonstrated to outperform the original MOTS in achieving the performance metrics of optimality and diversity of nondominated frontiers with desirable stability and robustness. © 2017, National Ground Water Association.

Perceived breast cancer risk: Heuristic reasoning and search for a dominance structure

OpenAIRE

Katapodi, M. C.; Facione, N. C.; Humphreys, J. C.; Dodd, MJ.

2005-01-01

Studies suggest that people construct their risk perceptions by using inferential rules called heuristics. The purpose of this study was to identify heuristics that influence perceived breast cancer risk. We examined 11 interviews from women of diverse ethnic/cultural backgrounds who were recruited from community settings. Narratives in which women elaborated about their own breast cancer risk were analyzed with Argument and Heuristic Reasoning Analysis methodology, which is based on applied ...

Comparison of Decisions Quality of Heuristic Methods with Limited Depth-First Search Techniques in the Graph Shortest Path Problem

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Vatutin Eduard

2017-12-01

Full Text Available The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.

Comparison of Decisions Quality of Heuristic Methods with Limited Depth-First Search Techniques in the Graph Shortest Path Problem

Science.gov (United States)

Vatutin, Eduard

2017-12-01

The article deals with the problem of analysis of effectiveness of the heuristic methods with limited depth-first search techniques of decision obtaining in the test problem of getting the shortest path in graph. The article briefly describes the group of methods based on the limit of branches number of the combinatorial search tree and limit of analyzed subtree depth used to solve the problem. The methodology of comparing experimental data for the estimation of the quality of solutions based on the performing of computational experiments with samples of graphs with pseudo-random structure and selected vertices and arcs number using the BOINC platform is considered. It also shows description of obtained experimental results which allow to identify the areas of the preferable usage of selected subset of heuristic methods depending on the size of the problem and power of constraints. It is shown that the considered pair of methods is ineffective in the selected problem and significantly inferior to the quality of solutions that are provided by ant colony optimization method and its modification with combinatorial returns.

An Adaptive Large Neighborhood Search-based Three-Stage Matheuristic for the Vehicle Routing Problem with Time Windows

DEFF Research Database (Denmark)

Christensen, Jonas Mark; Røpke, Stefan

that serves all the customers. The second stage usesan Adaptive Large Neighborhood Search (ALNS) algorithm to minimise the travel distance, during the second phase all of the generated routes are considered by solving a set cover problem. The ALNS algorithm uses 4 destroy operators, 2 repair operators...

Using tree diversity to compare phylogenetic heuristics.

Science.gov (United States)

Sul, Seung-Jin; Matthews, Suzanne; Williams, Tiffani L

2009-04-29

Evolutionary trees are family trees that represent the relationships between a group of organisms. Phylogenetic heuristics are used to search stochastically for the best-scoring trees in tree space. Given that better tree scores are believed to be better approximations of the true phylogeny, traditional evaluation techniques have used tree scores to determine the heuristics that find the best scores in the fastest time. We develop new techniques to evaluate phylogenetic heuristics based on both tree scores and topologies to compare Pauprat and Rec-I-DCM3, two popular Maximum Parsimony search algorithms. Our results show that although Pauprat and Rec-I-DCM3 find the trees with the same best scores, topologically these trees are quite different. Furthermore, the Rec-I-DCM3 trees cluster distinctly from the Pauprat trees. In addition to our heatmap visualizations of using parsimony scores and the Robinson-Foulds distance to compare best-scoring trees found by the two heuristics, we also develop entropy-based methods to show the diversity of the trees found. Overall, Pauprat identifies more diverse trees than Rec-I-DCM3. Overall, our work shows that there is value to comparing heuristics beyond the parsimony scores that they find. Pauprat is a slower heuristic than Rec-I-DCM3. However, our work shows that there is tremendous value in using Pauprat to reconstruct trees-especially since it finds identical scoring but topologically distinct trees. Hence, instead of discounting Pauprat, effort should go in improving its implementation. Ultimately, improved performance measures lead to better phylogenetic heuristics and will result in better approximations of the true evolutionary history of the organisms of interest.

In Search of Prototypes and Feminist Bank-Tellers: Exploring the Representativeness Heuristic

OpenAIRE

Nilsson, Håkan

2008-01-01

According to the heuristics and biases approach, the representativeness heuristic (RH) is one of the heuristics available for assessing subjective probabilities (A. Tversky & D. Kahneman, 1974). A subjective probability assessed by the RH is determined by how representative the target object is of the target category. Several aspects of the RH are argued to cause systematic biases, for example: (i) When the RH is used, the category is represented by one single prototypical exemplar. This ...

A grouping hyper-heuristic framework: application on graph colouring

OpenAIRE

Elhag, Anas; Özcan, Ender

2015-01-01

Grouping problems are hard to solve combinatorial optimisation problems which require partitioning of objects into a minimum number of subsets while a given objective is simultaneously optimised. Selection hyper-heuristics are high level general purpose search methodologies that operate on a space formed by a set of low level heuristics rather than solutions. Most of the recently proposed selection hyper-heuristics are iterative and make use of two key methods which are employed successively;...

Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

Directory of Open Access Journals (Sweden)

Wenming Cheng

2012-01-01

Full Text Available In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.

An analysis of generalised heuristics for vehicle routing and personnel rostering problems

OpenAIRE

Mustafa Misir; Pieter Smet; Greet Vanden Berghe

2015-01-01

The present study investigates the performance of heuristics while solving problems with routing and rostering characteristics. The target problems include scheduling and routing home care, security and maintenance personnel. In analysing the behaviour of the heuristics and determining the requirements for solving the aforementioned problems, the winning hyper-heuristic from the first International Cross-domain Heuristic Search Challenge (CHeSC 2011) is employed. The completely new applicatio...

Heuristic Inquiry: A Personal Journey of Acculturation and Identity Reconstruction

Science.gov (United States)

Djuraskovic, Ivana; Arthur, Nancy

2010-01-01

Heuristic methodology attempts to discover the nature and meaning of phenomenon through internal self-search, exploration, and discovery. Heuristic methodology encourages the researcher to explore and pursue the creative journey that begins inside one's being and ultimately uncovers its direction and meaning through internal discovery (Douglass &…

Exact and Heuristic Algorithms for Runway Scheduling

Science.gov (United States)

Malik, Waqar A.; Jung, Yoon C.

2016-01-01

This paper explores the Single Runway Scheduling (SRS) problem with arrivals, departures, and crossing aircraft on the airport surface. Constraints for wake vortex separations, departure area navigation separations and departure time window restrictions are explicitly considered. The main objective of this research is to develop exact and heuristic based algorithms that can be used in real-time decision support tools for Air Traffic Control Tower (ATCT) controllers. The paper provides a multi-objective dynamic programming (DP) based algorithm that finds the exact solution to the SRS problem, but may prove unusable for application in real-time environment due to large computation times for moderate sized problems. We next propose a second algorithm that uses heuristics to restrict the search space for the DP based algorithm. A third algorithm based on a combination of insertion and local search (ILS) heuristics is then presented. Simulation conducted for the east side of Dallas/Fort Worth International Airport allows comparison of the three proposed algorithms and indicates that the ILS algorithm performs favorably in its ability to find efficient solutions and its computation times.

Heuristic Artificial Bee Colony Algorithm for Uncovering Community in Complex Networks

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Yuquan Guo

2017-01-01

Full Text Available Community structure is important for us to understand the functions and structure of the complex networks. In this paper, Heuristic Artificial Bee Colony (HABC algorithm based on swarm intelligence is proposed for uncovering community. The proposed HABC includes initialization, employed bee searching, onlooker searching, and scout bee searching. In initialization stage, the nectar sources with simple community structure are generated through network dynamic algorithm associated with complete subgraph. In employed bee searching and onlooker searching stages, the searching function is redefined to address the community problem. The efficiency of searching progress can be improved by a heuristic function which is an average agglomerate probability of two neighbor communities. Experiments are carried out on artificial and real world networks, and the results demonstrate that HABC will have better performance in terms of comparing with the state-of-the-art algorithms.

Large neighborhood search for the double traveling salesman problem with multiple stacks

Energy Technology Data Exchange (ETDEWEB)

Bent, Russell W [Los Alamos National Laboratory; Van Hentenryck, Pascal [BROWN UNIV

2009-01-01

This paper considers a complex real-life short-haul/long haul pickup and delivery application. The problem can be modeled as double traveling salesman problem (TSP) in which the pickups and the deliveries happen in the first and second TSPs respectively. Moreover, the application features multiple stacks in which the items must be stored and the pickups and deliveries must take place in reserve (LIFO) order for each stack. The goal is to minimize the total travel time satisfying these constraints. This paper presents a large neighborhood search (LNS) algorithm which improves the best-known results on 65% of the available instances and is always within 2% of the best-known solutions.

Scheduling technicians and tasks in a telecommunications company

DEFF Research Database (Denmark)

Cordeau, J. F.; Laporte, G.; Pasin, F.

2010-01-01

This paper proposes a construction heuristic and an adaptive large neighborhood search heuristic for the technician and task scheduling problem arising in a large telecommunications company. This problem was solved within the framework of the 2007 challenge set up by the French Operational Research...

A Case Study of Controlling Crossover in a Selection Hyper-heuristic Framework Using the Multidimensional Knapsack Problem.

Science.gov (United States)

Drake, John H; Özcan, Ender; Burke, Edmund K

2016-01-01

Hyper-heuristics are high-level methodologies for solving complex problems that operate on a search space of heuristics. In a selection hyper-heuristic framework, a heuristic is chosen from an existing set of low-level heuristics and applied to the current solution to produce a new solution at each point in the search. The use of crossover low-level heuristics is possible in an increasing number of general-purpose hyper-heuristic tools such as HyFlex and Hyperion. However, little work has been undertaken to assess how best to utilise it. Since a single-point search hyper-heuristic operates on a single candidate solution, and two candidate solutions are required for crossover, a mechanism is required to control the choice of the other solution. The frameworks we propose maintain a list of potential solutions for use in crossover. We investigate the use of such lists at two conceptual levels. First, crossover is controlled at the hyper-heuristic level where no problem-specific information is required. Second, it is controlled at the problem domain level where problem-specific information is used to produce good-quality solutions to use in crossover. A number of selection hyper-heuristics are compared using these frameworks over three benchmark libraries with varying properties for an NP-hard optimisation problem: the multidimensional 0-1 knapsack problem. It is shown that allowing crossover to be managed at the domain level outperforms managing crossover at the hyper-heuristic level in this problem domain.

Meta-heuristic cuckoo search algorithm for the correction of faulty array antenna

International Nuclear Information System (INIS)

Khan, S.U.; Qureshi, I.M.

2015-01-01

In this article, we introduce a CSA (Cuckoo Search Algorithm) for compensation of faulty array antenna. It is assumed that the faulty elemental location is also known. When the sensor fails, it disturbs the power pattern, owing to which its SLL (Sidelobe Level) raises and nulls are shifted from their required positions. In this approach, the CSA optimizes the weights of the active elements for the reduction of SLL and null position in the desired direction. The meta-heuristic CSA is used for the control of SLL and steering of nulls at their required positions. The CSA is based on the necessitated kids bloodsucking behavior of cuckoo sort in arrangement with the Levy flight manners. The fitness function is used to reduce the error between the preferred and probable pattern along with null constraints. Imitational consequences for various scenarios are given to exhibit the validity and presentation of the proposed method. (author)

A Variable Neighborhood Search Algorithm for the Leather Nesting Problem

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Cláudio Alves

2012-01-01

Full Text Available The leather nesting problem is a cutting and packing optimization problem that consists in finding the best layout for a set of irregular pieces within a natural leather hide with an irregular surface and contour. In this paper, we address a real application of this problem related to the production of car seats in the automotive industry. The high quality requirements imposed on these products combined with the heterogeneity of the leather hides make the problem very complex to solve in practice. Very few results are reported in the literature for the leather nesting problem. Furthermore, the majority of the approaches impose some additional constraints to the layouts related to the particular application that is considered. In this paper, we describe a variable neighborhood search algorithm for the general leather nesting problem. To evaluate the performance of our approaches, we conducted an extensive set of computational experiments on real instances. The results of these experiments are reported at the end of the paper.

Dynamic Vehicle Routing Using an Improved Variable Neighborhood Search Algorithm

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Yingcheng Xu

2013-01-01

Full Text Available In order to effectively solve the dynamic vehicle routing problem with time windows, the mathematical model is established and an improved variable neighborhood search algorithm is proposed. In the algorithm, allocation customers and planning routes for the initial solution are completed by the clustering method. Hybrid operators of insert and exchange are used to achieve the shaking process, the later optimization process is presented to improve the solution space, and the best-improvement strategy is adopted, which make the algorithm can achieve a better balance in the solution quality and running time. The idea of simulated annealing is introduced to take control of the acceptance of new solutions, and the influences of arrival time, distribution of geographical location, and time window range on route selection are analyzed. In the experiment, the proposed algorithm is applied to solve the different sizes' problems of DVRP. Comparing to other algorithms on the results shows that the algorithm is effective and feasible.

Optimum energy re-establishment in distribution systems: a comparison between the search performance using fuzzy heuristics and genetic algorithms; Restabelecimento otimo de energia em sistemas de distribuicao: uma comparacao entre o desempenho de busca com heuristica fuzzy e algoritmos geneticos

Energy Technology Data Exchange (ETDEWEB)

Delbem, Alexandre C.B.; Bretas, Newton G. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Engenharia Eletrica; Carvalho, Andre C.P.L.F. [Sao Paulo Univ., Sao Carlos, SP (Brazil). Dept. de Ciencias de Computacao e Estatistica

1996-11-01

A search approach using fuzzy heuristics and a neural network parameter was developed for service restoration of a distribution system. The goal was to restore energy for an un-faulted zone after a fault had been identified and isolated. The restoration plan must be carried out in a very short period. However, the combinatorial feature of the problem constrained the application of automatic energy restoration planners. To overcome this problem, an heuristic search approach using fuzzy heuristics was proposed. As a result, a genetic algorithm approach was developed to achieve the optimal energy restoration plan. The effectiveness of these approaches were tested in a simplified distribution system based on the complex distribution system of Sao Carlos city, Sao Paulo State - southeast Brazil. It was noticed that the genetic algorithm provided better performance than the fuzzy heuristic search in this problem. 11 refs., 10 figs.

A simple heuristic for Internet-based evidence search in primary care: a randomized controlled trial

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Eberbach A

2016-08-01

Full Text Available Andreas Eberbach,1 Annette Becker,1 Justine Rochon,2 Holger Finkemeler,1Achim Wagner,3 Norbert Donner-Banzhoff1 1Department of Family and Community Medicine, Philipp University of Marburg, Marburg, Germany; 2Institute of Medical Biometry and Informatics, University of Heidelberg, Heidelberg, Germany; 3Department of Sport Medicine, Justus-Liebig-University of Giessen, Giessen, Germany Background: General practitioners (GPs are confronted with a wide variety of clinical questions, many of which remain unanswered. Methods: In order to assist GPs in finding quick, evidence-based answers, we developed a learning program (LP with a short interactive workshop based on a simple ­three-step-heuristic to improve their search and appraisal competence (SAC. We evaluated the LP ­effectiveness with a randomized controlled trial (RCT. Participants (intervention group [IG] n=20; ­control group [CG] n=31 rated acceptance and satisfaction and also answered 39 ­knowledge ­questions to assess their SAC. We controlled for previous knowledge in content areas covered by the test. Results: Main outcome – SAC: within both groups, the pre–post test shows significant (P=0.00 improvements in correctness (IG 15% vs CG 11% and confidence (32% vs 26% to find evidence-based answers. However, the SAC difference was not significant in the RCT. Other measures: Most workshop participants rated “learning atmosphere” (90%, “skills acquired” (90%, and “relevancy to my practice” (86% as good or very good. The ­LP-recommendations were implemented by 67% of the IG, whereas 15% of the CG already conformed to LP recommendations spontaneously (odds ratio 9.6, P=0.00. After literature search, the IG showed a (not significantly higher satisfaction regarding “time spent” (IG 80% vs CG 65%, “quality of information” (65% vs 54%, and “amount of information” (53% vs 47%.Conclusion: Long-standing established GPs have a good SAC. Despite high acceptance, strong

Conduct Disorder and Neighborhood Effects.

Science.gov (United States)

Jennings, Wesley G; Perez, Nicholas M; Reingle Gonzalez, Jennifer M

2018-05-07

There has been a considerable amount of scholarly attention to the relationship between neighborhood effects and conduct disorder, particularly in recent years. Having said this, it has been nearly two decades since a comprehensive synthesis of this literature has been conducted. Relying on a detailed and comprehensive search strategy and inclusion criteria, this article offers a systematic and interdisciplinary review of 47 empirical studies that have examined neighborhood effects and conduct disorder. Described results suggest that there are generally robust linkages between adverse neighborhood factors and conduct disorder and externalizing behavior problems, as 67 of the 93 (72.04%) effect sizes derived from these studies yielded statistically significant neighborhood effects. The review also identifies salient mediating and moderating influences. It discusses study limitations and directions for future research as well.

Exact and heuristic solutions to the Double TSP with Multiple Stacks

DEFF Research Database (Denmark)

Petersen, Hanne Løhmann; Archetti, Claudia; Madsen, Oli B.G.

-pallet, which can be loaded in 3 stacks in a standard 40 foot container. Different exact and heuristic solution approaches to the DTSPMS have been implemented and tested. The exact approaches are based on different mathematical formulations of the problem which are solved using branch-and-cut. One formulation...... instances. The implemented heuristics include tabu search, simulated annealing and large neighbourhood search. Particularly the LNS approach shows promising results. It finds the known optimal solution of smaller instances (15 orders) within 10 seconds in most cases, and in 3 minutes it finds solutions...

Heuristics for multiobjective multiple sequence alignment.

Science.gov (United States)

Abbasi, Maryam; Paquete, Luís; Pereira, Francisco B

2016-07-15

Aligning multiple sequences arises in many tasks in Bioinformatics. However, the alignments produced by the current software packages are highly dependent on the parameters setting, such as the relative importance of opening gaps with respect to the increase of similarity. Choosing only one parameter setting may provide an undesirable bias in further steps of the analysis and give too simplistic interpretations. In this work, we reformulate multiple sequence alignment from a multiobjective point of view. The goal is to generate several sequence alignments that represent a trade-off between maximizing the substitution score and minimizing the number of indels/gaps in the sum-of-pairs score function. This trade-off gives to the practitioner further information about the similarity of the sequences, from which she could analyse and choose the most plausible alignment. We introduce several heuristic approaches, based on local search procedures, that compute a set of sequence alignments, which are representative of the trade-off between the two objectives (substitution score and indels). Several algorithm design options are discussed and analysed, with particular emphasis on the influence of the starting alignment and neighborhood search definitions on the overall performance. A perturbation technique is proposed to improve the local search, which provides a wide range of high-quality alignments. The proposed approach is tested experimentally on a wide range of instances. We performed several experiments with sequences obtained from the benchmark database BAliBASE 3.0. To evaluate the quality of the results, we calculate the hypervolume indicator of the set of score vectors returned by the algorithms. The results obtained allow us to identify reasonably good choices of parameters for our approach. Further, we compared our method in terms of correctly aligned pairs ratio and columns correctly aligned ratio with respect to reference alignments. Experimental results show

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

Science.gov (United States)

Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique

2016-01-01

Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems.

A nuclear heuristic for application to metaheuristics in-core fuel management optimization

Energy Technology Data Exchange (ETDEWEB)

Meneses, Anderson Alvarenga de Moura, E-mail: ameneses@lmp.ufrj.b [COPPE/Federal University of Rio de Janeiro, RJ (Brazil). Nuclear Engineering Program; Dalle Molle Institute for Artificial Intelligence (IDSIA), Manno-Lugano, TI (Switzerland); Gambardella, Luca Maria, E-mail: luca@idsia.c [Dalle Molle Institute for Artificial Intelligence (IDSIA), Manno-Lugano, TI (Switzerland); Schirru, Roberto, E-mail: schirru@lmp.ufrj.b [COPPE/Federal University of Rio de Janeiro, RJ (Brazil). Nuclear Engineering Program

2009-07-01

The In-Core Fuel Management Optimization (ICFMO) is a well-known problem of nuclear engineering whose features are complexity, high number of feasible solutions, and a complex evaluation process with high computational cost, thus it is prohibitive to have a great number of evaluations during an optimization process. Heuristics are criteria or principles for deciding which among several alternative courses of action are more effective with respect to some goal. In this paper, we propose a new approach for the use of relational heuristics for the search in the ICFMO. The Heuristic is based on the reactivity of the fuel assemblies and their position into the reactor core. It was applied to random search, resulting in less computational effort concerning the number of evaluations of loading patterns during the search. The experiments demonstrate that it is possible to achieve results comparable to results in the literature, for future application to metaheuristics in the ICFMO. (author)

A nuclear heuristic for application to metaheuristics in-core fuel management optimization

International Nuclear Information System (INIS)

Meneses, Anderson Alvarenga de Moura; Gambardella, Luca Maria; Schirru, Roberto

2009-01-01

The In-Core Fuel Management Optimization (ICFMO) is a well-known problem of nuclear engineering whose features are complexity, high number of feasible solutions, and a complex evaluation process with high computational cost, thus it is prohibitive to have a great number of evaluations during an optimization process. Heuristics are criteria or principles for deciding which among several alternative courses of action are more effective with respect to some goal. In this paper, we propose a new approach for the use of relational heuristics for the search in the ICFMO. The Heuristic is based on the reactivity of the fuel assemblies and their position into the reactor core. It was applied to random search, resulting in less computational effort concerning the number of evaluations of loading patterns during the search. The experiments demonstrate that it is possible to achieve results comparable to results in the literature, for future application to metaheuristics in the ICFMO. (author)

Location, Allocation and Routing of Temporary Health Centers in Rural Areas in Crisis, Solved by Improved Harmony Search Algorithm

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Mahdi Alinaghian

2017-01-01

Full Text Available In this paper, an uncertain integrated model for simultaneously locating temporary health centers in the affected areas, allocating affected areas to these centers, and routing to transport their required good is considered. Health centers can be settled in one of the affected areas or in a place out of them; therefore, the proposed model offers the best relief operation policy when it is possible to supply the goods of affected areas (which are customers of goods directly or under coverage. Due to that the problem is NP-Hard, to solve the problem in large-scale, a meta-heuristic algorithm based on harmony search algorithm is presented and its performance has been compared with basic harmony search algorithm and neighborhood search algorithm in small and large scale test problems. The results show that the proposed harmony search algorithm has a suitable efficiency.

A heuristic algorithm for a multi-product four-layer capacitated location-routing problem

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Mohsen Hamidi

2014-01-01

Full Text Available The purpose of this study is to solve a complex multi-product four-layer capacitated location-routing problem (LRP in which two specific constraints are taken into account: 1 plants have limited production capacity, and 2 central depots have limited capacity for storing and transshipping products. The LRP represents a multi-product four-layer distribution network that consists of plants, central depots, regional depots, and customers. A heuristic algorithm is developed to solve the four-layer LRP. The heuristic uses GRASP (Greedy Randomized Adaptive Search Procedure and two probabilistic tabu search strategies of intensification and diversification to tackle the problem. Results show that the heuristic solves the problem effectively.

A Heuristic Dynamically Dimensioned Search with Sensitivity Information (HDDS-S and Application to River Basin Management

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Jinggang Chu

2015-05-01

Full Text Available River basin simulation and multi-reservoir optimal operation have been critical for river basin management. Due to the intense interaction between human activities and river basin systems, the river basin model and multi-reservoir operation model are complicated with a large number of parameters. Therefore, fast and stable optimization algorithms are required for river basin management under the changing conditions of climate and current human activities. This study presents a new global optimization algorithm, named as heuristic dynamically dimensioned search with sensitivity information (HDDS-S, to effectively perform river basin simulation and multi-reservoir optimal operation during river basin management. The HDDS-S algorithm is built on the dynamically dimensioned search (DDS algorithm; and has an improved computational efficiency while maintaining its search capacity compared to the original DDS algorithm. This is mainly due to the non-uniform probability assigned to each decision variable on the basis of its changing sensitivity to the optimization objectives during the adaptive change from global to local search with dimensionality reduced. This study evaluates the new algorithm by comparing its performance with the DDS algorithm on a river basin model calibration problem and a multi-reservoir optimal operation problem. The results obtained indicate that the HDDS-S algorithm outperforms the DDS algorithm in terms of search ability and computational efficiency in the two specific problems. In addition; similar to the DDS algorithm; the HDDS-S algorithm is easy to use as it does not require any parameter tuning and automatically adjusts its search to find good solutions given an available computational budget.

Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation.

Science.gov (United States)

Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia

2017-02-15

This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic Inertia Weight Binary Bat Algorithm with Neighborhood Search

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Xingwang Huang

2017-01-01

Full Text Available Binary bat algorithm (BBA is a binary version of the bat algorithm (BA. It has been proven that BBA is competitive compared to other binary heuristic algorithms. Since the update processes of velocity in the algorithm are consistent with BA, in some cases, this algorithm also faces the premature convergence problem. This paper proposes an improved binary bat algorithm (IBBA to solve this problem. To evaluate the performance of IBBA, standard benchmark functions and zero-one knapsack problems have been employed. The numeric results obtained by benchmark functions experiment prove that the proposed approach greatly outperforms the original BBA and binary particle swarm optimization (BPSO. Compared with several other heuristic algorithms on zero-one knapsack problems, it also verifies that the proposed algorithm is more able to avoid local minima.

Modified meta-heuristics using random mutation for truss topology optimization with static and dynamic constraints

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Vimal J. Savsani

2017-04-01

The static and dynamic responses to the TTO problems are challenging due to its search space, which is implicit, non-convex, non-linear, and often leading to divergence. Modified meta-heuristics are effective optimization methods to handle such problems in actual fact. In this paper, modified versions of Teaching–Learning-Based Optimization (TLBO, Heat Transfer Search (HTS, Water Wave Optimization (WWO, and Passing Vehicle Search (PVS are proposed by integrating the random mutation-based search technique with them. This paper compares the performance of four modified and four basic meta-heuristics to solve discrete TTO problems.

How the twain can meet: Prospect theory and models of heuristics in risky choice.

Science.gov (United States)

Pachur, Thorsten; Suter, Renata S; Hertwig, Ralph

2017-03-01

Two influential approaches to modeling choice between risky options are algebraic models (which focus on predicting the overt decisions) and models of heuristics (which are also concerned with capturing the underlying cognitive process). Because they rest on fundamentally different assumptions and algorithms, the two approaches are usually treated as antithetical, or even incommensurable. Drawing on cumulative prospect theory (CPT; Tversky & Kahneman, 1992) as the currently most influential instance of a descriptive algebraic model, we demonstrate how the two modeling traditions can be linked. CPT's algebraic functions characterize choices in terms of psychophysical (diminishing sensitivity to probabilities and outcomes) as well as psychological (risk aversion and loss aversion) constructs. Models of heuristics characterize choices as rooted in simple information-processing principles such as lexicographic and limited search. In computer simulations, we estimated CPT's parameters for choices produced by various heuristics. The resulting CPT parameter profiles portray each of the choice-generating heuristics in psychologically meaningful ways-capturing, for instance, differences in how the heuristics process probability information. Furthermore, CPT parameters can reflect a key property of many heuristics, lexicographic search, and track the environment-dependent behavior of heuristics. Finally, we show, both in an empirical and a model recovery study, how CPT parameter profiles can be used to detect the operation of heuristics. We also address the limits of CPT's ability to capture choices produced by heuristics. Our results highlight an untapped potential of CPT as a measurement tool to characterize the information processing underlying risky choice. Copyright © 2017 Elsevier Inc. All rights reserved.

Efficient heuristics for the Rural Postman Problem | Groves | ORiON

African Journals Online (AJOL)

A local search framework for the (undirected) Rural Postman Problem (RPP) is presented in this paper. The framework allows local search approaches that have been applied successfully to the well–known Travelling Salesman Problem also to be applied to the RPP. New heuristics for the RPP, based on this framework, ...

Hybridisations of Variable Neighbourhood Search and Modified Simplex Elements to Harmony Search and Shuffled Frog Leaping Algorithms for Process Optimisations

Science.gov (United States)

Aungkulanon, P.; Luangpaiboon, P.

2010-10-01

Nowadays, the engineering problem systems are large and complicated. An effective finite sequence of instructions for solving these problems can be categorised into optimisation and meta-heuristic algorithms. Though the best decision variable levels from some sets of available alternatives cannot be done, meta-heuristics is an alternative for experience-based techniques that rapidly help in problem solving, learning and discovery in the hope of obtaining a more efficient or more robust procedure. All meta-heuristics provide auxiliary procedures in terms of their own tooled box functions. It has been shown that the effectiveness of all meta-heuristics depends almost exclusively on these auxiliary functions. In fact, the auxiliary procedure from one can be implemented into other meta-heuristics. Well-known meta-heuristics of harmony search (HSA) and shuffled frog-leaping algorithms (SFLA) are compared with their hybridisations. HSA is used to produce a near optimal solution under a consideration of the perfect state of harmony of the improvisation process of musicians. A meta-heuristic of the SFLA, based on a population, is a cooperative search metaphor inspired by natural memetics. It includes elements of local search and global information exchange. This study presents solution procedures via constrained and unconstrained problems with different natures of single and multi peak surfaces including a curved ridge surface. Both meta-heuristics are modified via variable neighbourhood search method (VNSM) philosophy including a modified simplex method (MSM). The basic idea is the change of neighbourhoods during searching for a better solution. The hybridisations proceed by a descent method to a local minimum exploring then, systematically or at random, increasingly distant neighbourhoods of this local solution. The results show that the variant of HSA with VNSM and MSM seems to be better in terms of the mean and variance of design points and yields.

PENDEKATAN ACTIVITY-BASED COSTING DAN METODE PENCARIAN HEURISTIC UNTUK MENYELESAIKAN PROBLEM PEMILIHAN PERALATAN PADA FLEXIBLE MANUFACTURING SYSTEMS (FMS

Directory of Open Access Journals (Sweden)

Gregorius Satia Budhi

2002-01-01

Full Text Available The application of Activity Based Costing (ABC approach to select the set-machine that is used in the production of Flexible Manufacture System (FMS based on technical and economical criteria can be useful for producers to design FMS by considering the minimum production cost. In the other hand, Heuristic Search is known to have a short searching time. Algorithm Heuristic that using ABC approach as the weight in finding the solution to shorten the equipment selection time during the design / redesign process of the FMS in less than exponential time was designed in this research. The increasing speed is useful because with the faster time in design / redesign process, therefore the flexibility level of part variety that can be processed will become better. Theoretical and empirical analysis in Algorithm Heuristic shows that time searching to get appropriate set of equipment is not too long, so that we can assume that the designed Algorithm Heuristic can be implemented in the real world. By comparing the empirical result of Algorithm Heuristic to the Algorithm Exhaustive, we can also assume that Algorithm Heuristic that using ABC method as the weight for finding solution can optimise the equipment selection problem of FMS based on economical criteria too. Abstract in Bahasa Indonesia : Penggunaan pendekatan Activity Based Costing (ABC untuk memilih set mesin yang digunakan dalam produksi pada Flexible Manufacture Systems (FMS berdasar atas kriteria teknis dan ekonomis, dapat membantu pelaku produksi untuk mendisain FMS dengan pertimbangan minimalisasi biaya produksi. Sementara itu, Heuristic Search dikenal memiliki waktu pencarian yang singkat. Pada riset ini didisain sebuah Algoritma Heuristic yang menggunakan pendekatan ABC sebagai bobot dalam pencarian solusi, untuk mempersingkat waktu pemilihan peralatan saat desain/redisain FMS dalam waktu kurang dari waktu Eksponensial. Peningkatan kecepatan ini bermanfaat, karena dengan cepatnya waktu

A HYBRID HEURISTIC ALGORITHM FOR SOLVING THE RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM (RCPSP

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Juan Carlos Rivera

Full Text Available The Resource Constrained Project Scheduling Problem (RCPSP is a problem of great interest for the scientific community because it belongs to the class of NP-Hard problems and no methods are known that can solve it accurately in polynomial processing times. For this reason heuristic methods are used to solve it in an efficient way though there is no guarantee that an optimal solution can be obtained. This research presents a hybrid heuristic search algorithm to solve the RCPSP efficiently, combining elements of the heuristic Greedy Randomized Adaptive Search Procedure (GRASP, Scatter Search and Justification. The efficiency obtained is measured taking into account the presence of the new elements added to the GRASP algorithm taken as base: Justification and Scatter Search. The algorithms are evaluated using three data bases of instances of the problem: 480 instances of 30 activities, 480 of 60, and 600 of 120 activities respectively, taken from the library PSPLIB available online. The solutions obtained by the developed algorithm for the instances of 30, 60 and 120 are compared with results obtained by other researchers at international level, where a prominent place is obtained, according to Chen (2011.

Comparing Solution Approaches for a Complete Model of High School Timetabling

DEFF Research Database (Denmark)

Sørensen, Matias; Stidsen, Thomas Riis

of these formulations are NP-hard. A heuristic based on Adaptive Large Neighborhood Search is also applied. Using 100 real-life datasets, comprehensive computational results are provided which show that the ALNS heuristic outperforms the IP approaches. The ALNS heuristic has been incorporated in Lectio......, and is currently available to almost 200 dierent high schools in Denmark. Furthermore, a conversion of the datasets into the XHSTT format is described, and some datasets are made publicly available....

Memory-Based Decision-Making with Heuristics: Evidence for a Controlled Activation of Memory Representations

Science.gov (United States)

Khader, Patrick H.; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rosler, Frank

2011-01-01

Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by…

Black-Box Search by Unbiased Variation

DEFF Research Database (Denmark)

Lehre, Per Kristian; Witt, Carsten

2012-01-01

The complexity theory for black-box algorithms, introduced by Droste, Jansen, and Wegener (Theory Comput. Syst. 39:525–544, 2006), describes common limits on the efficiency of a broad class of randomised search heuristics. There is an obvious trade-off between the generality of the black-box model...... and the strength of the bounds that can be proven in such a model. In particular, the original black-box model provides for well-known benchmark problems relatively small lower bounds, which seem unrealistic in certain cases and are typically not met by popular search heuristics.In this paper, we introduce a more...... restricted black-box model for optimisation of pseudo-Boolean functions which we claim captures the working principles of many randomised search heuristics including simulated annealing, evolutionary algorithms, randomised local search, and others. The key concept worked out is an unbiased variation operator...

Heuristics for the Robust Coloring Problem

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Miguel Ángel Gutiérrez Andrade

2011-03-01

Full Text Available Let $G$ and $\\bar{G}$ be complementary graphs. Given a penalty function defined on the edges of $G$, we will say that the rigidity of a $k$-coloring of $G$ is the sum of the penalties of the edges of G joining vertices of the same color. Based on the previous definition, the Robust Coloring Problem (RCP is stated as the search of the minimum rigidity $k$-coloring. In this work a comparison of heuristics based on simulated annealing, GRASP and scatter search is presented. These are the best results for the RCP that have been obtained.

Simple heuristics and rules of thumb: where psychologists and behavioural biologists might meet.

Science.gov (United States)

Hutchinson, John M C; Gigerenzer, Gerd

2005-05-31

The Centre for Adaptive Behaviour and Cognition (ABC) has hypothesised that much human decision-making can be described by simple algorithmic process models (heuristics). This paper explains this approach and relates it to research in biology on rules of thumb, which we also review. As an example of a simple heuristic, consider the lexicographic strategy of Take The Best for choosing between two alternatives: cues are searched in turn until one discriminates, then search stops and all other cues are ignored. Heuristics consist of building blocks, and building blocks exploit evolved or learned abilities such as recognition memory; it is the complexity of these abilities that allows the heuristics to be simple. Simple heuristics have an advantage in making decisions fast and with little information, and in avoiding overfitting. Furthermore, humans are observed to use simple heuristics. Simulations show that the statistical structures of different environments affect which heuristics perform better, a relationship referred to as ecological rationality. We contrast ecological rationality with the stronger claim of adaptation. Rules of thumb from biology provide clearer examples of adaptation because animals can be studied in the environments in which they evolved. The range of examples is also much more diverse. To investigate them, biologists have sometimes used similar simulation techniques to ABC, but many examples depend on empirically driven approaches. ABC's theoretical framework can be useful in connecting some of these examples, particularly the scattered literature on how information from different cues is integrated. Optimality modelling is usually used to explain less detailed aspects of behaviour but might more often be redirected to investigate rules of thumb.

A fine-grained parallel algorithm for the cyclic flexible job shop problem

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Bożejko Wojciech

2017-06-01

Full Text Available In this paper there is considered a flexible job shop problem of operations scheduling. The new, very fast method of determination of cycle time is presented. In the design of heuristic algorithm there was the neighborhood inspired by the game of golf applied. Lower bound of the criterion function was used in the search of the neighborhood.

Simple heuristics in over-the-counter drug choices: a new hint for medical education and practice.

Science.gov (United States)

Riva, Silvia; Monti, Marco; Antonietti, Alessandro

2011-01-01

Over-the-counter (OTC) drugs are widely available and often purchased by consumers without advice from a health care provider. Many people rely on self-management of medications to treat common medical conditions. Although OTC medications are regulated by the National and the International Health and Drug Administration, many people are unaware of proper dosing, side effects, adverse drug reactions, and possible medication interactions. This study examined how subjects make their decisions to select an OTC drug, evaluating the role of cognitive heuristics which are simple and adaptive rules that help the decision-making process of people in everyday contexts. By analyzing 70 subjects' information-search and decision-making behavior when selecting OTC drugs, we examined the heuristics they applied in order to assess whether simple decision-making processes were also accurate and relevant. Subjects were tested with a sequence of two experimental tests based on a computerized Java system devised to analyze participants' choices in a virtual environment. We found that subjects' information-search behavior reflected the use of fast and frugal heuristics. In addition, although the heuristics which correctly predicted subjects' decisions implied significantly fewer cues on average than the subjects did in the information-search task, they were accurate in describing order of information search. A simple combination of a fast and frugal tree and a tallying rule predicted more than 78% of subjects' decisions. The current emphasis in health care is to shift some responsibility onto the consumer through expansion of self medication. To know which cognitive mechanisms are behind the choice of OTC drugs is becoming a relevant purpose of current medical education. These findings have implications both for the validity of simple heuristics describing information searches in the field of OTC drug choices and for current medical education, which has to prepare competent health

Heuristic decision making.

Science.gov (United States)

Gigerenzer, Gerd; Gaissmaier, Wolfgang

2011-01-01

As reflected in the amount of controversy, few areas in psychology have undergone such dramatic conceptual changes in the past decade as the emerging science of heuristics. Heuristics are efficient cognitive processes, conscious or unconscious, that ignore part of the information. Because using heuristics saves effort, the classical view has been that heuristic decisions imply greater errors than do "rational" decisions as defined by logic or statistical models. However, for many decisions, the assumptions of rational models are not met, and it is an empirical rather than an a priori issue how well cognitive heuristics function in an uncertain world. To answer both the descriptive question ("Which heuristics do people use in which situations?") and the prescriptive question ("When should people rely on a given heuristic rather than a complex strategy to make better judgments?"), formal models are indispensable. We review research that tests formal models of heuristic inference, including in business organizations, health care, and legal institutions. This research indicates that (a) individuals and organizations often rely on simple heuristics in an adaptive way, and (b) ignoring part of the information can lead to more accurate judgments than weighting and adding all information, for instance for low predictability and small samples. The big future challenge is to develop a systematic theory of the building blocks of heuristics as well as the core capacities and environmental structures these exploit.

examining the predictive power of the VRIO-Framework and the Recognition Heuristic

OpenAIRE

Powalla, Christian

2010-01-01

Boundedly rational managers regularly have to make complex strategic decisions under uncertainty. In this context heuristics can play an important supporting role. They are used to reasonably structure the decision making process, to reduce the information search, and to achieve a good solution with an acceptable problem-solving effort. This empirical research project analyzes the practical usefulness of several selected heuristic techniques, which can be used within strategic analysis, by...

Improving the Bin Packing Heuristic through Grammatical Evolution Based on Swarm Intelligence

Directory of Open Access Journals (Sweden)

Marco Aurelio Sotelo-Figueroa

2014-01-01

Full Text Available In recent years Grammatical Evolution (GE has been used as a representation of Genetic Programming (GP which has been applied to many optimization problems such as symbolic regression, classification, Boolean functions, constructed problems, and algorithmic problems. GE can use a diversity of searching strategies including Swarm Intelligence (SI. Particle Swarm Optimisation (PSO is an algorithm of SI that has two main problems: premature convergence and poor diversity. Particle Evolutionary Swarm Optimization (PESO is a recent and novel algorithm which is also part of SI. PESO uses two perturbations to avoid PSO’s problems. In this paper we propose using PESO and PSO in the frame of GE as strategies to generate heuristics that solve the Bin Packing Problem (BPP; it is possible however to apply this methodology to other kinds of problems using another Grammar designed for that problem. A comparison between PESO, PSO, and BPP’s heuristics is performed through the nonparametric Friedman test. The main contribution of this paper is proposing a Grammar to generate online and offline heuristics depending on the test instance trying to improve the heuristics generated by other grammars and humans; it also proposes a way to implement different algorithms as search strategies in GE like PESO to obtain better results than those obtained by PSO.

A Hybrid Tabu Search Heuristic for a Bilevel Competitive Facility Location Model

Science.gov (United States)

Küçükaydın, Hande; Aras, Necati; Altınel, I. Kuban

We consider a problem in which a firm or franchise enters a market by locating new facilities where there are existing facilities belonging to a competitor. The firm aims at finding the location and attractiveness of each facility to be opened so as to maximize its profit. The competitor, on the other hand, can react by adjusting the attractiveness of its existing facilities, opening new facilities and/or closing existing ones with the objective of maximizing its own profit. The demand is assumed to be aggregated at certain points in the plane and the facilities of the firm can be located at prespecified candidate sites. We employ Huff's gravity-based rule in modeling the behavior of the customers where the fraction of customers at a demand point that visit a certain facility is proportional to the facility attractiveness and inversely proportional to the distance between the facility site and demand point. We formulate a bilevel mixed-integer nonlinear programming model where the firm entering the market is the leader and the competitor is the follower. In order to find a feasible solution of this model, we develop a hybrid tabu search heuristic which makes use of two exact methods as subroutines: a gradient ascent method and a branch-and-bound algorithm with nonlinear programming relaxation.

Heuristic space diversity management in a meta-hyper-heuristic framework

CSIR Research Space (South Africa)

Grobler, J

2014-07-01

Full Text Available This paper introduces the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm. Evaluation on a diverse set of floating...

Two efficient heuristics to solve the integrated load distribution and production planning problem

International Nuclear Information System (INIS)

Gajpal, Yuvraj; Nourelfath, Mustapha

2015-01-01

This paper considers a multi-period production system where a set of machines are arranged in parallel. The machines are unreliable and the failure rate of machine depends on the load assigned to the machine. The expected production rate of the system is considered to be a non-monotonic function of its load. Because of the machine failure rate, the total production output depends on the combination of loads assigned to different machines. We consider the integration of load distribution decisions with production planning decision. The product demands are considered to be known in advance. The objective is to minimize the sum of holding costs, backorder costs, production costs, setup costs, capacity change costs and unused capacity costs while satisfying the demand over specified time horizon. The constraint is not to exceed available repair resources required to repair the machine breakdown. The paper develops two heuristics to solve the integrated load distribution and production planning problem. The first heuristic consists of a three-phase approach, while the second one is based on tabu search metaheuristic. The efficiency of the proposed heuristics is tested through the randomly generated problem instances. - Highlights: • The expected performance of the system is a non-monotonic function of its load. • We consider the integration of load distribution and production planning decisions. • The paper proposes three phase and tabu search based heuristics to solve the problem. • Lower bound has been developed for checking the effectiveness of the heuristics. • The efficiency of the heuristic is tested through randomly generated instances.

Generalised Adaptive Harmony Search: A Comparative Analysis of Modern Harmony Search

Directory of Open Access Journals (Sweden)

Jaco Fourie

2013-01-01

Full Text Available Harmony search (HS was introduced in 2001 as a heuristic population-based optimisation algorithm. Since then HS has become a popular alternative to other heuristic algorithms like simulated annealing and particle swarm optimisation. However, some flaws, like the need for parameter tuning, were identified and have been a topic of study for much research over the last 10 years. Many variants of HS were developed to address some of these flaws, and most of them have made substantial improvements. In this paper we compare the performance of three recent HS variants: exploratory harmony search, self-adaptive harmony search, and dynamic local-best harmony search. We compare the accuracy of these algorithms, using a set of well-known optimisation benchmark functions that include both unimodal and multimodal problems. Observations from this comparison led us to design a novel hybrid that combines the best attributes of these modern variants into a single optimiser called generalised adaptive harmony search.

A System for Automatically Generating Scheduling Heuristics

Science.gov (United States)

Morris, Robert

1996-01-01

The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.

A Slicing Tree Representation and QCP-Model-Based Heuristic Algorithm for the Unequal-Area Block Facility Layout Problem

Directory of Open Access Journals (Sweden)

Mei-Shiang Chang

2013-01-01

Full Text Available The facility layout problem is a typical combinational optimization problem. In this research, a slicing tree representation and a quadratically constrained program model are combined with harmony search to develop a heuristic method for solving the unequal-area block layout problem. Because of characteristics of slicing tree structure, we propose a regional structure of harmony memory to memorize facility layout solutions and two kinds of harmony improvisation to enhance global search ability of the proposed heuristic method. The proposed harmony search based heuristic is tested on 10 well-known unequal-area facility layout problems from the literature. The results are compared with the previously best-known solutions obtained by genetic algorithm, tabu search, and ant system as well as exact methods. For problems O7, O9, vC10Ra, M11*, and Nug12, new best solutions are found. For other problems, the proposed approach can find solutions that are very similar to previous best-known solutions.

An LP-based heuristic for the fixed charge transportation problem

DEFF Research Database (Denmark)

Klose, Andreas

2007-01-01

The fixed charge transportation problem consists in finding a minimum cost network flow from a set of suppliers to a set of customers. Beside costs proportional to quantities transported, transportation costs also include a fixed charge. The paper describes a linear programming based heuristic...... approach for computing lower and upper bounds on the minimal cost. To this end, the LP relaxation is iteratively strengthened by means of adding cuts; in each iteration the current LP solution is then used to guide a local search heuristic. In addition to standard polyhedral cuts as lifted cover...

Greedy Local Search and Vertex Cover in Sparse Random Graphs

DEFF Research Database (Denmark)

Witt, Carsten

2009-01-01

. This work starts with a rigorous explanation for this claim based on the refined analysis of the Karp-Sipser algorithm by Aronson et al. Subsequently, theoretical supplements are given to experimental studies of search heuristics on random graphs. For c 1, a greedy and randomized local-search heuristic...... finds an optimal cover in polynomial time with a probability arbitrarily close to 1. This behavior relies on the absence of a giant component. As an additional insight into the randomized search, it is shown that the heuristic fails badly also on graphs consisting of a single tree component of maximum......Recently, various randomized search heuristics have been studied for the solution of the minimum vertex cover problem, in particular for sparse random instances according to the G(n, c/n) model, where c > 0 is a constant. Methods from statistical physics suggest that the problem is easy if c

Path-Wise Test Data Generation Based on Heuristic Look-Ahead Methods

Directory of Open Access Journals (Sweden)

Ying Xing

2014-01-01

Full Text Available Path-wise test data generation is generally considered an important problem in the automation of software testing. In essence, it is a constraint optimization problem, which is often solved by search methods such as backtracking algorithms. In this paper, the backtracking algorithm branch and bound and state space search in artificial intelligence are introduced to tackle the problem of path-wise test data generation. The former is utilized to explore the space of potential solutions and the latter is adopted to construct the search tree dynamically. Heuristics are employed in the look-ahead stage of the search. Dynamic variable ordering is presented with a heuristic rule to break ties, values of a variable are determined by the monotonicity analysis on branching conditions, and maintaining path consistency is achieved through analysis on the result of interval arithmetic. An optimization method is also proposed to reduce the search space. The results of empirical experiments show that the search is conducted in a basically backtrack-free manner, which ensures both test data generation with promising performance and its excellence over some currently existing static and dynamic methods in terms of coverage. The results also demonstrate that the proposed method is applicable in engineering.

The use of a genetic algorithm-based search strategy in geostatistics: application to a set of anisotropic piezometric head data

Science.gov (United States)

Abedini, M. J.; Nasseri, M.; Burn, D. H.

2012-04-01

In any geostatistical study, an important consideration is the choice of an appropriate, repeatable, and objective search strategy that controls the nearby samples to be included in the location-specific estimation procedure. Almost all geostatistical software available in the market puts the onus on the user to supply search strategy parameters in a heuristic manner. These parameters are solely controlled by geographical coordinates that are defined for the entire area under study, and the user has no guidance as to how to choose these parameters. The main thesis of the current study is that the selection of search strategy parameters has to be driven by data—both the spatial coordinates and the sample values—and cannot be chosen beforehand. For this purpose, a genetic-algorithm-based ordinary kriging with moving neighborhood technique is proposed. The search capability of a genetic algorithm is exploited to search the feature space for appropriate, either local or global, search strategy parameters. Radius of circle/sphere and/or radii of standard or rotated ellipse/ellipsoid are considered as the decision variables to be optimized by GA. The superiority of GA-based ordinary kriging is demonstrated through application to the Wolfcamp Aquifer piezometric head data. Assessment of numerical results showed that definition of search strategy parameters based on both geographical coordinates and sample values improves cross-validation statistics when compared with that based on geographical coordinates alone. In the case of a variable search neighborhood for each estimation point, optimization of local search strategy parameters for an elliptical support domain—the orientation of which is dictated by anisotropic axes—via GA was able to capture the dynamics of piezometric head in west Texas/New Mexico in an efficient way.

An iterative bidirectional heuristic placement algorithm for solving the two-dimensional knapsack packing problem

Science.gov (United States)

Shiangjen, Kanokwatt; Chaijaruwanich, Jeerayut; Srisujjalertwaja, Wijak; Unachak, Prakarn; Somhom, Samerkae

2018-02-01

This article presents an efficient heuristic placement algorithm, namely, a bidirectional heuristic placement, for solving the two-dimensional rectangular knapsack packing problem. The heuristic demonstrates ways to maximize space utilization by fitting the appropriate rectangle from both sides of the wall of the current residual space layer by layer. The iterative local search along with a shift strategy is developed and applied to the heuristic to balance the exploitation and exploration tasks in the solution space without the tuning of any parameters. The experimental results on many scales of packing problems show that this approach can produce high-quality solutions for most of the benchmark datasets, especially for large-scale problems, within a reasonable duration of computational time.

A Geographical Heuristic Routing Protocol for VANETs

Science.gov (United States)

Urquiza-Aguiar, Luis; Tripp-Barba, Carolina; Aguilar Igartua, Mónica

2016-01-01

Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation). PMID:27669254

Automated detection of heuristics and biases among pathologists in a computer-based system.

Science.gov (United States)

Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Reitmeyer, Kayse; Tseytlin, Eugene; Castine, Melissa; Jukic, Drazen; Mello-Thoms, Claudia

2013-08-01

The purpose of this study is threefold: (1) to develop an automated, computer-based method to detect heuristics and biases as pathologists examine virtual slide cases, (2) to measure the frequency and distribution of heuristics and errors across three levels of training, and (3) to examine relationships of heuristics to biases, and biases to diagnostic errors. The authors conducted the study using a computer-based system to view and diagnose virtual slide cases. The software recorded participant responses throughout the diagnostic process, and automatically classified participant actions based on definitions of eight common heuristics and/or biases. The authors measured frequency of heuristic use and bias across three levels of training. Biases studied were detected at varying frequencies, with availability and search satisficing observed most frequently. There were few significant differences by level of training. For representativeness and anchoring, the heuristic was used appropriately as often or more often than it was used in biased judgment. Approximately half of the diagnostic errors were associated with one or more biases. We conclude that heuristic use and biases were observed among physicians at all levels of training using the virtual slide system, although their frequencies varied. The system can be employed to detect heuristic use and to test methods for decreasing diagnostic errors resulting from cognitive biases.

A Systematic Review of Neighborhood Disparities in Point-of-Sale Tobacco Marketing.

Science.gov (United States)

Lee, Joseph G L; Henriksen, Lisa; Rose, Shyanika W; Moreland-Russell, Sarah; Ribisl, Kurt M

2015-09-01

We systematically reviewed evidence of disparities in tobacco marketing at tobacco retailers by sociodemographic neighborhood characteristics. We identified 43 relevant articles from 893 results of a systematic search in 10 databases updated May 28, 2014. We found 148 associations of marketing (price, placement, promotion, or product availability) with a neighborhood demographic of interest (socioeconomic disadvantage, race, ethnicity, and urbanicity). Neighborhoods with lower income have more tobacco marketing. There is more menthol marketing targeting urban neighborhoods and neighborhoods with more Black residents. Smokeless tobacco products are targeted more toward rural neighborhoods and neighborhoods with more White residents. Differences in store type partially explain these disparities. There are more inducements to start and continue smoking in lower-income neighborhoods and in neighborhoods with more Black residents. Retailer marketing may contribute to disparities in tobacco use. Clinicians should be aware of the pervasiveness of these environmental cues.

A Systematic Review of Neighborhood Disparities in Point-of-Sale Tobacco Marketing

Science.gov (United States)

Henriksen, Lisa; Rose, Shyanika W.; Moreland-Russell, Sarah; Ribisl, Kurt M.

2015-01-01

We systematically reviewed evidence of disparities in tobacco marketing at tobacco retailers by sociodemographic neighborhood characteristics. We identified 43 relevant articles from 893 results of a systematic search in 10 databases updated May 28, 2014. We found 148 associations of marketing (price, placement, promotion, or product availability) with a neighborhood demographic of interest (socioeconomic disadvantage, race, ethnicity, and urbanicity). Neighborhoods with lower income have more tobacco marketing. There is more menthol marketing targeting urban neighborhoods and neighborhoods with more Black residents. Smokeless tobacco products are targeted more toward rural neighborhoods and neighborhoods with more White residents. Differences in store type partially explain these disparities. There are more inducements to start and continue smoking in lower-income neighborhoods and in neighborhoods with more Black residents. Retailer marketing may contribute to disparities in tobacco use. Clinicians should be aware of the pervasiveness of these environmental cues. PMID:26180986

A Heuristic Procedure for the Outbound Container Relocation Problem during Export Loading Operations

Directory of Open Access Journals (Sweden)

Roberto Guerra-Olivares

2015-01-01

Full Text Available During export ship loading operations, it is often necessary to perform relocation movements with containers that interfere with access to the desired container in the ship loading sequence. This paper presents a real-time heuristic procedure for the container relocation problem employing reachstacker vehicles as container handling equipment. The proposed heuristic searches for good relocation coordinates within a set of nearby bays. The heuristic has a parameter that determines how far from the original bay a container may be relocated. The tradeoff between reducing relocation movements and limiting vehicle travel distances is examined and the performance of the heuristic is compared with a common practice in the smaller container terminals in Chile and Mexico. Finally, a mathematical model for the container relocation problem is presented.

Iterated Local Search Algorithm with Strategic Oscillation for School Bus Routing Problem with Bus Stop Selection

Directory of Open Access Journals (Sweden)

Mohammad Saied Fallah Niasar

2017-02-01

Full Text Available he school bus routing problem (SBRP represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm and I-ILS (a variant of Insertion with Iterated Local Search algorithm are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBRP

Efficient heuristics for the Rural Postman Problem

Directory of Open Access Journals (Sweden)

GW Groves

2005-06-01

Full Text Available A local search framework for the (undirected Rural Postman Problem (RPP is presented in this paper. The framework allows local search approaches that have been applied successfully to the well–known Travelling Salesman Problem also to be applied to the RPP. New heuristics for the RPP, based on this framework, are introduced and these are capable of solving significantly larger instances of the RPP than have been reported in the literature. Test results are presented for a number of benchmark RPP instances in a bid to compare efficiency and solution quality against known methods.

Household food waste collection: Building service networks through neighborhood expansion.

Science.gov (United States)

Armington, William R; Chen, Roger B

2018-04-17

In this paper we develop a residential food waste collection analysis and modeling framework that captures transportation costs faced by service providers in their initial stages of service provision. With this framework and model, we gain insights into network transportation costs and investigate possible service expansion scenarios faced by these organizations. We solve a vehicle routing problem (VRP) formulated for the residential neighborhood context using a heuristic approach developed. The scenarios considered follow a narrative where service providers start with an initial neighborhood or community and expands to incorporate other communities and their households. The results indicate that increasing household participation, decreases the travel time and cost per household, up to a critical threshold, beyond which we see marginal time and cost improvements. Additionally, the results indicate different outcomes in expansion scenarios depending on the household density of incorporated neighborhoods. As household participation and density increases, the travel time per household in the network decreases. However, at approximately 10-20 households per km 2 , the decrease in travel time per household is marginal, suggesting a lowerbound household density threshold. Finally, we show in food waste collection, networks share common scaling effects with respect to travel time and costs, regardless of the number of nodes and links. Copyright © 2018 Elsevier Ltd. All rights reserved.

Characterizing web heuristics

NARCIS (Netherlands)

de Jong, Menno D.T.; van der Geest, Thea

2000-01-01

This article is intended to make Web designers more aware of the qualities of heuristics by presenting a framework for analyzing the characteristics of heuristics. The framework is meant to support Web designers in choosing among alternative heuristics. We hope that better knowledge of the

Comparison of Heuristics for Generating All-partition Arrays in the Style of Milton Babbitt

DEFF Research Database (Denmark)

Bemman, Brian; Meredith, David

2015-01-01

aggregate or an incomplete one that can be made complete by adding OARPs. It is noteworthy that, when constructing an all-partition array, Babbitt started out with a non-self-contained sequence of partitions. In this paper, we use a known self-contained sequence as a basis for forming two heuristics...... that select integer partitions likely to have been chosen by Babbitt. We suggest these heuristics will select integer partitions more likely to produce a self-contained sequence and we present it as a means for efficiently searching the space of possible sequences. We apply our heuristics to both types...

Simple heuristics in over-the-counter drug choices: a new hint for medical education and practice

Science.gov (United States)

Riva, Silvia; Monti, Marco; Antonietti, Alessandro

2011-01-01

Introduction Over-the-counter (OTC) drugs are widely available and often purchased by consumers without advice from a health care provider. Many people rely on self-management of medications to treat common medical conditions. Although OTC medications are regulated by the National and the International Health and Drug Administration, many people are unaware of proper dosing, side effects, adverse drug reactions, and possible medication interactions. Purpose This study examined how subjects make their decisions to select an OTC drug, evaluating the role of cognitive heuristics which are simple and adaptive rules that help the decision-making process of people in everyday contexts. Subjects and methods By analyzing 70 subjects’ information-search and decision-making behavior when selecting OTC drugs, we examined the heuristics they applied in order to assess whether simple decision-making processes were also accurate and relevant. Subjects were tested with a sequence of two experimental tests based on a computerized Java system devised to analyze participants’ choices in a virtual environment. Results We found that subjects’ information-search behavior reflected the use of fast and frugal heuristics. In addition, although the heuristics which correctly predicted subjects’ decisions implied significantly fewer cues on average than the subjects did in the information-search task, they were accurate in describing order of information search. A simple combination of a fast and frugal tree and a tallying rule predicted more than 78% of subjects’ decisions. Conclusion The current emphasis in health care is to shift some responsibility onto the consumer through expansion of self medication. To know which cognitive mechanisms are behind the choice of OTC drugs is becoming a relevant purpose of current medical education. These findings have implications both for the validity of simple heuristics describing information searches in the field of OTC drug choices and

Simultaneous determination of aquifer parameters and zone structures with fuzzy c-means clustering and meta-heuristic harmony search algorithm

Science.gov (United States)

Ayvaz, M. Tamer

2007-11-01

This study proposes an inverse solution algorithm through which both the aquifer parameters and the zone structure of these parameters can be determined based on a given set of observations on piezometric heads. In the zone structure identification problem fuzzy c-means ( FCM) clustering method is used. The association of the zone structure with the transmissivity distribution is accomplished through an optimization model. The meta-heuristic harmony search ( HS) algorithm, which is conceptualized using the musical process of searching for a perfect state of harmony, is used as an optimization technique. The optimum parameter zone structure is identified based on three criteria which are the residual error, parameter uncertainty, and structure discrimination. A numerical example given in the literature is solved to demonstrate the performance of the proposed algorithm. Also, a sensitivity analysis is performed to test the performance of the HS algorithm for different sets of solution parameters. Results indicate that the proposed solution algorithm is an effective way in the simultaneous identification of aquifer parameters and their corresponding zone structures.

Complex Sequencing Problems and Local Search Heuristics

NARCIS (Netherlands)

Brucker, P.; Hurink, Johann L.; Osman, I.H.; Kelly, J.P.

1996-01-01

Many problems can be formulated as complex sequencing problems. We will present problems in flexible manufacturing that have such a formulation and apply local search methods like iterative improvement, simulated annealing and tabu search to solve these problems. Computational results are reported.

Heuristic Synthesis of Reversible Logic – A Comparative Study

Directory of Open Access Journals (Sweden)

Chua Shin Cheng

2014-01-01

Full Text Available Reversible logic circuits have been historically motivated by theoretical research in low-power, and recently attracted interest as components of the quantum algorithm, optical computing and nanotechnology. However due to the intrinsic property of reversible logic, traditional irreversible logic design and synthesis methods cannot be carried out. Thus a new set of algorithms are developed correctly to synthesize reversible logic circuit. This paper presents a comprehensive literature review with comparative study on heuristic based reversible logic synthesis. It reviews a range of heuristic based reversible logic synthesis techniques reported by researchers (BDD-based, cycle-based, search-based, non-search-based, rule-based, transformation-based, and ESOP-based. All techniques are described in detail and summarized in a table based on their features, limitation, library used and their consideration metric. Benchmark comparison of gate count and quantum cost are analysed for each synthesis technique. Comparing the synthesis algorithm outputs over the years, it can be observed that different approach has been used for the synthesis of reversible circuit. However, the improvements are not significant. Quantum cost and gate count has improved over the years, but arguments and debates are still on certain issues such as the issue of garbage outputs that remain the same. This paper provides the information of all heuristic based synthesis of reversible logic method proposed over the years. All techniques are explained in detail and thus informative for new reversible logic researchers and bridging the knowledge gap in this area.

An efficient heuristic for the multi-compartment vehicle routing problem

OpenAIRE

Paulo Vitor Silvestrin

2016-01-01

We study a variant of the vehicle routing problem that allows vehicles with multiple compartments. The need for multiple compartments frequently arises in practical applications when there are several products of different quality or type, that must be kept or handled separately. The resulting problem is called the multi-compartment vehicle routing problem (MCVRP). We propose a tabu search heuristic and embed it into an iterated local search to solve the MCVRP. In several experiments we analy...

Establishing usability heuristics for heuristics evaluation in a specific domain: Is there a consensus?

Science.gov (United States)

Hermawati, Setia; Lawson, Glyn

2016-09-01

Heuristics evaluation is frequently employed to evaluate usability. While general heuristics are suitable to evaluate most user interfaces, there is still a need to establish heuristics for specific domains to ensure that their specific usability issues are identified. This paper presents a comprehensive review of 70 studies related to usability heuristics for specific domains. The aim of this paper is to review the processes that were applied to establish heuristics in specific domains and identify gaps in order to provide recommendations for future research and area of improvements. The most urgent issue found is the deficiency of validation effort following heuristics proposition and the lack of robustness and rigour of validation method adopted. Whether domain specific heuristics perform better or worse than general ones is inconclusive due to lack of validation quality and clarity on how to assess the effectiveness of heuristics for specific domains. The lack of validation quality also affects effort in improving existing heuristics for specific domain as their weaknesses are not addressed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heuristics for the economic dispatch problem

Energy Technology Data Exchange (ETDEWEB)

Flores, Benjamin Carpio [Centro Nacional de Controle de Energia (CENACE), Mexico, D.F. (Mexico). Dept. de Planificacion Economica de Largo Plazo], E-mail: benjamin.carpo@cfe.gob.mx; Laureano Cruces, A L; Lopez Bracho, R; Ramirez Rodriguez, J. [Universidad Autonoma Metropolitana (UAM), Mexico, D.F. (Brazil). Dept. de Sistemas], Emails: clc@correo.azc.uam.mx, rlb@correo.azc.uam.mx, jararo@correo.azc.uam.mx

2009-07-01

This paper presents GRASP (Greedy Randomized Adaptive Search Procedure), Simulated Annealing (SAA), Genetic (GA), and Hybrid Genetic (HGA) Algorithms for the economic dispatch problem (EDP), considering non-convex cost functions and dead zones the only restrictions, showing the results obtained. We also present parameter settings that are specifically applicable to the EDP, and a comparative table of results for each heuristic. It is shown that these methods outperform the classical methods without the need to assume convexity of the target function. (author)

NEIGHBORHOOD CHOICE AND NEIGHBORHOOD CHANGE

OpenAIRE

Bruch, Elizabeth; Mare, Robert D.

2006-01-01

This paper examines the relationships between the residential choices of individuals and aggregate patterns of neighborhood change. We investigate the conditions under which individuals’ preferences for the race-ethnic composition of their neighborhoods produce high levels of segregation. Using computational models, we find that high levels of segregation occur only when individuals’ preferences follow a threshold function. If individuals make finer-grained distinctions among neighborhoods th...

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

Science.gov (United States)

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

An improved exploratory search technique for pure integer linear programming problems

Science.gov (United States)

Fogle, F. R.

1990-01-01

The development is documented of a heuristic method for the solution of pure integer linear programming problems. The procedure draws its methodology from the ideas of Hooke and Jeeves type 1 and 2 exploratory searches, greedy procedures, and neighborhood searches. It uses an efficient rounding method to obtain its first feasible integer point from the optimal continuous solution obtained via the simplex method. Since this method is based entirely on simple addition or subtraction of one to each variable of a point in n-space and the subsequent comparison of candidate solutions to a given set of constraints, it facilitates significant complexity improvements over existing techniques. It also obtains the same optimal solution found by the branch-and-bound technique in 44 of 45 small to moderate size test problems. Two example problems are worked in detail to show the inner workings of the method. Furthermore, using an established weighted scheme for comparing computational effort involved in an algorithm, a comparison of this algorithm is made to the more established and rigorous branch-and-bound method. A computer implementation of the procedure, in PC compatible Pascal, is also presented and discussed.

A single cognitive heuristic process meets the complexity of domain-specific moral heuristics.

Science.gov (United States)

Dubljević, Veljko; Racine, Eric

2014-10-01

The inherence heuristic (a) offers modest insights into the complex nature of both the is-ought tension in moral reasoning and moral reasoning per se, and (b) does not reflect the complexity of domain-specific moral heuristics. Formal and general in nature, we contextualize the process described as "inherence heuristic" in a web of domain-specific heuristics (e.g., agent specific; action specific; consequences specific).

Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

Directory of Open Access Journals (Sweden)

Ruey-Maw Chen

2011-01-01

Full Text Available The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimode project scheduling are proposed to help in solving interesting scheduling problems. They are the best performance resource heuristic and the latest finish time heuristic. These two heuristics applied to the PSO scheme are for speeding up the search of the particle and improving the capability of finding a sound schedule. Moreover, both global communication topology and local ring communication topology are also investigated for efficient study of proposed scheme. Simulation results demonstrate that the proposed approach in this investigation can successfully solve the task-resource assignment problems in grid computing and similar scheduling problems.

Commercial Territory Design for a Distribution Firm with New Constructive and Destructive Heuristics

Directory of Open Access Journals (Sweden)

Jaime

2012-02-01

Full Text Available A commercial territory design problem with compactness maximization criterion subject to territory balancing and connectivity is addressed. Four new heuristics based on Greedy Randomized Adaptive Search Procedures within a location-allocation scheme for this NP-hard combinatorial optimization problem are proposed. The first three (named GRLH1, GRLH2, and GRDL build the territories simultaneously. Their construction phase consists of two parts: a location phase where territory seeds are identified, and an allocation phase where the remaining basic units are iteratively assigned to a territory. In contrast, the other heuristic (named SLA builds the territories one at a time. Empirical results reveals that GRLH1 and GRLH2 find near-optimal or optimal solutions to relatively small instances, where exact solutions could be found. The proposed procedures are relatively fast. We carried out a comparison between the proposed heuristic procedures and the existing method in larger instances. It was observed the proposed heuristic GRLH1 produced competitive results with respect to the existing approach.

Pitfalls in Teaching Judgment Heuristics

Science.gov (United States)

Shepperd, James A.; Koch, Erika J.

2005-01-01

Demonstrations of judgment heuristics typically focus on how heuristics can lead to poor judgments. However, exclusive focus on the negative consequences of heuristics can prove problematic. We illustrate the problem with the representativeness heuristic and present a study (N = 45) that examined how examples influence understanding of the…

An ordering heuristic for building Binary Decision Diagrams for fault-trees

International Nuclear Information System (INIS)

Bouissou, M.

1997-01-01

Binary Decision Diagrams (BDD) have recently made a noticeable entry in the RAMS field. This kind of representation for boolean functions makes possible the assessment of complex fault-trees, both qualitatively (minimal cut-sets search) and quantitatively (exact calculation of top event probability). The object of the paper is to present a pre-processing of the fault-tree which ensures that the results given by different heuristics on the 'optimized' fault-tree are not too sensitive to the way the tree is written. This property is based on a theoretical proof. In contrast with some well known heuristics, the method proposed is not based only on intuition and practical experiments. (author)

Prediction-based dynamic load-sharing heuristics

Science.gov (United States)

Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

1993-01-01

The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

Heuristic decision making in medicine

Science.gov (United States)

Marewski, Julian N.; Gigerenzer, Gerd

2012-01-01

Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care. PMID:22577307

Heuristic decision making in medicine.

Science.gov (United States)

Marewski, Julian N; Gigerenzer, Gerd

2012-03-01

Can less information be more helpful when it comes to making medical decisions? Contrary to the common intuition that more information is always better, the use of heuristics can help both physicians and patients to make sound decisions. Heuristics are simple decision strategies that ignore part of the available information, basing decisions on only a few relevant predictors. We discuss: (i) how doctors and patients use heuristics; and (ii) when heuristics outperform information-greedy methods, such as regressions in medical diagnosis. Furthermore, we outline those features of heuristics that make them useful in health care settings. These features include their surprising accuracy, transparency, and wide accessibility, as well as the low costs and little time required to employ them. We close by explaining one of the statistical reasons why heuristics are accurate, and by pointing to psychiatry as one area for future research on heuristics in health care.

Large Neighborhood Search and Adaptive Randomized Decompositions for Flexible Jobshop Scheduling

DEFF Research Database (Denmark)

Pacino, Dario; Van Hentenryck, Pascal

2011-01-01

This paper considers a constraint-based scheduling approach to the flexible jobshop, a generalization of the traditional jobshop scheduling where activities have a choice of machines. It studies both large neighborhood (LNS) and adaptive randomized de- composition (ARD) schemes, using random...

HEURISTICS IN DECISION MAKING

Directory of Open Access Journals (Sweden)

I PUTU SUDANA

2011-01-01

Full Text Available Prinsip heuristics tidak dapat dikatakan sebagai sebuah pendekatanpengambilan keputusan yang non-rasional, karena penerapan atau penggunaanyang unconscious atau subtle mind tidak dapat dianggap sebagai tindakanyang irrational. Dengan alasan tersebut, terdapat cukup alasan untukmenyatakan bahwa pengklasifikasian pendekatan-pendekatan keputusansemestinya menggunakan terminologi analytical dan experiential, dan bukanmemakai istilah rational dan non-rational seperti yang umumnya diikuti.Penerapan pendekatan heuristics dapat ditemukan pada berbagai disiplin,termasuk bisnis dan akuntansi. Topik heuristics semestinya mendapatperhatian yang cukup luas dari para periset di bidang akuntansi. Bidangbehavioral research in accounting menawarkan banyak kemungkinan untukdikaji, karena prinsip heuristics bertautan erat dengan aspek manusia sebagaipelaku dalam pengambilan keputusan.

The Effect of Incentive Structure on Heuristic Decision Making: The Proportion Heuristic

OpenAIRE

Robert Oxoby

2007-01-01

When making judgments, individuals often utilize heuristics to interpret information. We report on a series of experiments designed to test the ways in which incentive mechanisms influence the use of a particular heuristic in decision-making. Specifically, we demonstrate how information regarding the number of available practice problems influences the behaviors of individuals preparing for an exam (the proportion heuristic). More importantly the extent to which this information influences be...

Choosing a heuristic and root node for edge ordering in BDD-based network reliability analysis

International Nuclear Information System (INIS)

Mo, Yuchang; Xing, Liudong; Zhong, Farong; Pan, Zhusheng; Chen, Zhongyu

2014-01-01

In the Binary Decision Diagram (BDD)-based network reliability analysis, heuristics have been widely used to obtain a reasonably good ordering of edge variables. Orderings generated using different heuristics can lead to dramatically different sizes of BDDs, and thus dramatically different running times and memory usages for the analysis of the same network. Unfortunately, due to the nature of the ordering problem (i.e., being an NP-complete problem) no formal guidelines or rules are available for choosing a good heuristic or for choosing a high-performance root node to perform edge searching using a particular heuristic. In this work, we make novel contributions by proposing heuristic and root node selection methods based on the concept of boundary sets for the BDD-based network reliability analysis. Empirical studies show that the proposed selection methods can help to generate high-performance edge ordering for most of studied cases, enabling the efficient BDD-based reliability analysis of large-scale networks. The proposed methods are demonstrated on different types of networks, including square lattice networks, torus lattice networks and de Bruijn networks

Accelerated Profile HMM Searches.

Directory of Open Access Journals (Sweden)

Sean R Eddy

2011-10-01

Full Text Available Profile hidden Markov models (profile HMMs and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the "multiple segment Viterbi" (MSV algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call "sparse rescaling". These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches.

Subjective neighborhood assessment and physical inactivity: An examination of neighborhood-level variance.

Science.gov (United States)

Prochaska, John D; Buschmann, Robert N; Jupiter, Daniel; Mutambudzi, Miriam; Peek, M Kristen

2018-06-01

Research suggests a linkage between perceptions of neighborhood quality and the likelihood of engaging in leisure-time physical activity. Often in these studies, intra-neighborhood variance is viewed as something to be controlled for statistically. However, we hypothesized that intra-neighborhood variance in perceptions of neighborhood quality may be contextually relevant. We examined the relationship between intra-neighborhood variance of subjective neighborhood quality and neighborhood-level reported physical inactivity across 48 neighborhoods within a medium-sized city, Texas City, Texas using survey data from 2706 residents collected between 2004 and 2006. Neighborhoods where the aggregated perception of neighborhood quality was poor also had a larger proportion of residents reporting being physically inactive. However, higher degrees of disagreement among residents within neighborhoods about their neighborhood quality was significantly associated with a lower proportion of residents reporting being physically inactive (p=0.001). Our results suggest that intra-neighborhood variability may be contextually relevant in studies seeking to better understand the relationship between neighborhood quality and behaviors sensitive to neighborhood environments, like physical activity. Copyright © 2017 Elsevier Inc. All rights reserved.

An ordering heuristic for building Binary Decision Diagrams for fault-trees

Energy Technology Data Exchange (ETDEWEB)

Bouissou, M. [Electricite de France (EDF), 75 - Paris (France)

1997-12-31

Binary Decision Diagrams (BDD) have recently made a noticeable entry in the RAMS field. This kind of representation for boolean functions makes possible the assessment of complex fault-trees, both qualitatively (minimal cut-sets search) and quantitatively (exact calculation of top event probability). The object of the paper is to present a pre-processing of the fault-tree which ensures that the results given by different heuristics on the `optimized` fault-tree are not too sensitive to the way the tree is written. This property is based on a theoretical proof. In contrast with some well known heuristics, the method proposed is not based only on intuition and practical experiments. (author) 12 refs.

Neighborhood Factors and Dating Violence Among Youth: A Systematic Review.

Science.gov (United States)

Johnson, Renee M; Parker, Elizabeth M; Rinehart, Jenny; Nail, Jennifer; Rothman, Emily F

2015-09-01

The purpose of this review is to summarize the empirical research on neighborhood-level factors and dating violence among adolescents and emerging adults to guide future research and practice. In 2015, a total of 20 articles were identified through a search of the literature using PubMed. Eligible articles included those that (1) had been published in a peer-reviewed journal since 2005; (2) reported a measure of association between at least one neighborhood-level factor and dating violence; and (3) had a study population of youth aged dating violence and neighborhood factors, and measures of effect. Results were summarized into three categories based on the aspect of neighborhood that was the focus of the work: demographic and structural characteristics (n=11); neighborhood disorder (n=12); and social disorganization (n=8). There was some evidence to suggest that neighborhood disadvantage is associated with dating violence, but very little evidence to suggest that residence characteristics (e.g., racial heterogeneity) are associated with dating violence. Results do suggest that perceived neighborhood disorder is associated with physical dating violence perpetration, but do not suggest that it is associated with physical dating violence victimization. Social control and community connectedness are both associated with dating violence, but findings on collective efficacy are mixed. Existing research suggests that neighborhood factors may be associated with dating violence. However, there is a limited body of research on the neighborhood context of dating violence, and more rigorous research is needed. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

A variable neighborhood search for the multi-period collection of recyclable materials

DEFF Research Database (Denmark)

Andersen, Maria Elbek; Wøhlk, Sanne

2016-01-01

treatment facilities. We investigate how the scheduling of emptying and transportation should be done in order to minimize the operation cost, while providing a high service level and ensuring that capacity constraints are not violated. We develop a heuristic solution method for solving the daily planning...

Incorporating Neighborhood Choice in a Model of Neighborhood Effects on Income.

Science.gov (United States)

van Ham, Maarten; Boschman, Sanne; Vogel, Matt

2018-05-09

Studies of neighborhood effects often attempt to identify causal effects of neighborhood characteristics on individual outcomes, such as income, education, employment, and health. However, selection looms large in this line of research, and it has been argued that estimates of neighborhood effects are biased because people nonrandomly select into neighborhoods based on their preferences, income, and the availability of alternative housing. We propose a two-step framework to disentangle selection processes in the relationship between neighborhood deprivation and earnings. We model neighborhood selection using a conditional logit model, from which we derive correction terms. Driven by the recognition that most households prefer certain types of neighborhoods rather than specific areas, we employ a principle components analysis to reduce these terms into eight correction components. We use these to adjust parameter estimates from a model of subsequent neighborhood effects on individual income for the unequal probability that a household chooses to live in a particular type of neighborhood. We apply this technique to administrative data from the Netherlands. After we adjust for the differential sorting of households into certain types of neighborhoods, the effect of neighborhood income on individual income diminishes but remains significant. These results further emphasize that researchers need to be attuned to the role of selection bias when assessing the role of neighborhood effects on individual outcomes. Perhaps more importantly, the persistent effect of neighborhood deprivation on subsequent earnings suggests that neighborhood effects reflect more than the shared characteristics of neighborhood residents: place of residence partially determines economic well-being.

Neighborhood socioeconomic deprivation characteristics in child (0-18 years) health studies: a review.

Science.gov (United States)

van Vuuren, C Leontine; Reijneveld, Sijmen A; van der Wal, Marcel F; Verhoeff, Arnoud P

2014-09-01

Growing up in socioeconomically deprived neighborhoods has been shown to have negative health effects on children. However, the most recent review on which measures are used to investigate the association between neighborhood characteristics and child (0-18 year) health included studies only until 2004. Insight into more recent research is needed for the further development of these measures. To review neighborhood socioeconomic deprivation characteristics used in recent studies investigating the relationship between neighborhood socioeconomic deprivation and child health. Sensitive search in MEDLINE, Embase, PsycINFO, Sociological Abstracts databases (2004-2013). Ultimately, 19 studies were included. We found ten neighborhood socioeconomic deprivation constructs, of which income/wealth, employment, and education were most frequently used. The choice for neighborhood characteristics seemed independent of the health outcome and in most cases was not based on a specific theoretical background or earlier work. Studies vary regarding study designs, measures and outcomes. Researchers should clearly specify their choice of neighborhood socioeconomic deprivation characteristics; preferably, these should be theory-based and used consistently. Copyright © 2014 Elsevier Ltd. All rights reserved.

A heuristic approach for the evaluation of Physical Protection System effectiveness

International Nuclear Information System (INIS)

Zou, Bowen; Yang, Ming; Guo, Jia; Benjamin, Emi-Reybold; Wu, Wenfei

2017-01-01

Highlights: • A heuristic approach is applied for the evaluation of PPS effectiveness (HAPPS). • Import 2-D engineering drawings into the analysis application, identify the information contained in the model. Use the HAPPS method as search algorithm to seek the vulnerable adversary intrusion and escape path under certain conditions. • Redesign the PPS by the evaluation results. - Abstract: Physical Protection System (PPS) is essential for each nuclear power plant to safeguard its nuclear materials and nuclear facilities from theft, robbery, illegal transport and sabotage. This paper presents a novel method (HAPPS) combined with Estimate of Adversary Sequence Interruption (EASI) method and heuristic approach (Ant Colony Optimization, ACO) for analyzing and evaluating the PPS effectiveness of NPPs. Import 2-D engineering drawings into the analysis application, identify the information contained in the model, and use the HAPPS method as search algorithm to seek the vulnerable adversary intrusion and escape path under certain conditions. The results of PPS effectiveness analysis will provide a detailed technical feedback for redesigning PPS.

Heuristics for Multidimensional Packing Problems

DEFF Research Database (Denmark)

Egeblad, Jens

for a minimum height container required for the items. The main contributions of the thesis are three new heuristics for strip-packing and knapsack packing problems where items are both rectangular and irregular. In the two first papers we describe a heuristic for the multidimensional strip-packing problem...... that is based on a relaxed placement principle. The heuristic starts with a random overlapping placement of items and large container dimensions. From the overlapping placement overlap is reduced iteratively until a non-overlapping placement is found and a new problem is solved with a smaller container size...... of this heuristic are among the best published in the literature both for two- and three-dimensional strip-packing problems for irregular shapes. In the third paper, we introduce a heuristic for two- and three-dimensional rectangular knapsack packing problems. The two-dimensional heuristic uses the sequence pair...

Meta-Heuristics for Dynamic Lot Sizing: a review and comparison of solution approaches

NARCIS (Netherlands)

R.F. Jans (Raf); Z. Degraeve (Zeger)

2004-01-01

textabstractProofs from complexity theory as well as computational experiments indicate that most lot sizing problems are hard to solve. Because these problems are so difficult, various solution techniques have been proposed to solve them. In the past decade, meta-heuristics such as tabu search,

Social biases determine spatiotemporal sparseness of ciliate mating heuristics.

Science.gov (United States)

Clark, Kevin B

2012-01-01

Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate's initial subjective bias, responsiveness, or preparedness, as defined by Stevens' Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The present

Social biases determine spatiotemporal sparseness of ciliate mating heuristics

Science.gov (United States)

2012-01-01

Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate’s initial subjective bias, responsiveness, or preparedness, as defined by Stevens’ Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The

Heuristic rules analysis on the fuel cells design using greedy search;Analisis de reglas heuristicas en el diseno de celdas de combustible usando busqueda greedy

Energy Technology Data Exchange (ETDEWEB)

Ortiz, J. J.; Castillo, J. A.; Montes, J. L.; Hernandez, J. L., E-mail: juanjose.ortiz@inin.gob.m [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)

2009-10-15

This work approaches the study of one of the heuristic rules of fuel cells design for boiling water nuclear reactors. This rule requires that the minor uranium enrichment is placed in the corners of the fuel cell. Also the search greedy is applied for the fuel cells design where explicitly does not take in count this rule, allowing the possibility to place any uranium enrichment with the condition that it does not contain gadolinium. Results are shown in the quality of the obtained cell by search greedy when it considers the rule and when not. The cell quality is measured with the value of the power pick factor obtained, as well as of the neutrons multiplication factor in an infinite medium. Cells were analyzed with 1 and 2 gadolinium concentrations low operation conditions at 120% of the nominal power of the reactors of the nuclear power plant of Laguna Verde. The results show that not to consider the rule in cells with a single gadolinium concentration, it has as repercussion that the greedy search has a minor performance. On the other hand with cells of two gadolinium concentrations, the performance of the greedy search was better. (Author)

Neighborhood, Socioeconomic, and Racial Influence on Chronic Pain.

Science.gov (United States)

Maly, Angelika; Vallerand, April Hazard

2018-02-01

The purpose of this review is to highlight the neighborhood, socioeconomic, and racial influences on chronic pain. Negative influences on the experience of chronic pain are explored and defined as any adverse stressor common in low socioeconomic, urban neighborhoods that potentially contributes to health disparity in African Americans experiencing chronic pain. The multifactorial influences on chronic pain disparity in African Americans are explored and expounded upon in this review of existing evidence. Databases used for the search included CINAHL, PubMed, and PsycArticles. The experience of chronic pain is multifaceted, existing with multiple comorbidities and lasting consequences. To improve the burden of chronic pain requires a multifactorial assessment that considers neighborhood risk factors, emphasis on environmental stressors, limitations to support networks, barriers to physical activity, and access to primary care providers with whom communication is open and without bias. A comprehensive assessment of barriers will aid in the development of interventions that reach beyond the physical factors of chronic pain, also considering the psychosocial barriers to improving the burden of chronic pain in African Americans living in impoverished urban neighborhoods. Copyright © 2017 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.

Neighborhood level risk factors for type 1 diabetes in youth: the SEARCH case-control study

Directory of Open Access Journals (Sweden)

Liese Angela D

2012-01-01

Full Text Available Abstract Background European ecologic studies suggest higher socioeconomic status is associated with higher incidence of type 1 diabetes. Using data from a case-control study of diabetes among racially/ethnically diverse youth in the United States (U.S., we aimed to evaluate the independent impact of neighborhood characteristics on type 1 diabetes risk. Data were available for 507 youth with type 1 diabetes and 208 healthy controls aged 10-22 years recruited in South Carolina and Colorado in 2003-2006. Home addresses were used to identify Census tracts of residence. Neighborhood-level variables were obtained from 2000 U.S. Census. Multivariate generalized linear mixed models were applied. Results Controlling for individual risk factors (age, gender, race/ethnicity, infant feeding, birth weight, maternal age, number of household residents, parental education, income, state, higher neighborhood household income (p = 0.005, proportion of population in managerial jobs (p = 0.02, with at least high school education (p = 0.005, working outside the county (p = 0.04 and vehicle ownership (p = 0.03 were each independently associated with increased odds of type 1 diabetes. Conversely, higher percent minority population (p = 0.0003, income from social security (p = 0.002, proportion of crowded households (0.0497 and poverty (p = 0.008 were associated with a decreased odds. Conclusions Our study suggests that neighborhood characteristics related to greater affluence, occupation, and education are associated with higher type 1 diabetes risk. Further research is needed to understand mechanisms underlying the influence of neighborhood context.

Improving performances of suboptimal greedy iterative biclustering heuristics via localization.

Science.gov (United States)

Erten, Cesim; Sözdinler, Melih

2010-10-15

Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function. We provide a fast and simple pre-processing algorithm called localization that reorders the rows and columns of the input data matrix in such a way as to group correlated entries in small local neighborhoods within the matrix. The proposed localization algorithm takes its roots from effective use of graph-theoretical methods applied to problems exhibiting a similar structure to that of biclustering. In order to evaluate the effectivenesss of the localization pre-processing algorithm, we focus on three representative greedy iterative heuristic methods. We show how the localization pre-processing can be incorporated into each representative algorithm to improve biclustering performance. Furthermore, we propose a simple biclustering algorithm, Random Extraction After Localization (REAL) that randomly extracts submatrices from the localization pre-processed data matrix, eliminates those with low similarity scores, and provides the rest as correlated structures representing biclusters. We compare the proposed localization pre-processing with another pre-processing alternative, non-negative matrix factorization. We show that our fast and simple localization procedure provides similar or even better results than the computationally heavy matrix factorization pre-processing with regards to H-value tests. We next demonstrate that the performances of the three representative greedy iterative heuristic methods improve with localization pre-processing when biological correlations in the form of functional enrichment and PPI verification constitute the main performance

Active living neighborhoods: is neighborhood walkability a key element for Belgian adolescents?

Science.gov (United States)

De Meester, Femke; Van Dyck, Delfien; De Bourdeaudhuij, Ilse; Deforche, Benedicte; Sallis, James F; Cardon, Greet

2012-01-04

In adult research, neighborhood walkability has been acknowledged as an important construct among the built environmental correlates of physical activity. Research into this association has only recently been extended to adolescents and the current empirical evidence is not consistent. This study investigated whether neighborhood walkability and neighborhood socioeconomic status (SES) are associated with physical activity among Belgian adolescents and whether the association between neighborhood walkability and physical activity is moderated by neighborhood SES and gender. In Ghent (Belgium), 32 neighborhoods were selected based on GIS-based walkability and SES derived from census data. In total, 637 adolescents (aged 13-15 year, 49.6% male) participated in the study. Physical activity was assessed using accelerometers and the Flemish Physical Activity Questionnaire. To analyze the associations between neighborhood walkability, neighborhood SES and individual physical activity, multivariate multi-level regression analyses were conducted. Only in low-SES neighborhoods, neighborhood walkability was positively associated with accelerometer-based moderate to vigorous physical activity and the average activity level expressed in counts/minute. For active transport to and from school, cycling for transport during leisure time and sport during leisure time no association with neighborhood walkability nor, with neighborhood SES was found. For walking for transport during leisure time a negative association with neighborhood SES was found. Gender did not moderate the associations of neighborhood walkability and SES with adolescent physical activity. Neighborhood walkability was related to accelerometer-based physical activity only among adolescent boys and girls living in low-SES neighborhoods. The relation of built environment to adolescent physical activity may depend on the context.

A Tutorial on Heuristic Methods

DEFF Research Database (Denmark)

Vidal, Rene Victor Valqui; Werra, D. de; Silver, E.

1980-01-01

In this paper we define a heuristic method as a procedure for solving a well-defined mathematical problem by an intuitive approach in which the structure of the problem can be interpreted and exploited intelligently to obtain a reasonable solution. Issues discussed include: (i) the measurement...... of the quality of a heuristic method, (ii) different types of heuristic procedures, (iii) the interactive role of human beings and (iv) factors that may influence the choice or testing of heuristic methods. A large number of references are included....

An Empirical Comparison of Seven Iterative and Evolutionary Function Optimization Heuristics

Science.gov (United States)

Baluja, Shumeet

1995-01-01

This report is a repository of the results obtained from a large scale empirical comparison of seven iterative and evolution-based optimization heuristics. Twenty-seven static optimization problems, spanning six sets of problem classes which are commonly explored in genetic algorithm literature, are examined. The problem sets include job-shop scheduling, traveling salesman, knapsack, binpacking, neural network weight optimization, and standard numerical optimization. The search spaces in these problems range from 2368 to 22040. The results indicate that using genetic algorithms for the optimization of static functions does not yield a benefit, in terms of the final answer obtained, over simpler optimization heuristics. Descriptions of the algorithms tested and the encodings of the problems are described in detail for reproducibility.

A Combination of Meta-heuristic and Heuristic Algorithms for the VRP, OVRP and VRP with Simultaneous Pickup and Delivery

Directory of Open Access Journals (Sweden)

Maryam Ashouri

2017-07-01

Full Text Available Vehicle routing problem (VRP is a Nondeterministic Polynomial Hard combinatorial optimization problem to serve the consumers from central depots and returned back to the originated depots with given vehicles. Furthermore, two of the most important extensions of the VRPs are the open vehicle routing problem (OVRP and VRP with simultaneous pickup and delivery (VRPSPD. In OVRP, the vehicles have not return to the depot after last visit and in VRPSPD, customers require simultaneous delivery and pick-up service. The aim of this paper is to present a combined effective ant colony optimization (CEACO which includes sweep and several local search algorithms which is different with common ant colony optimization (ACO. An extensive numerical experiment is performed on benchmark problem instances addressed in the literature. The computational result shows that suggested CEACO approach not only presented a very satisfying scalability, but also was competitive with other meta-heuristic algorithms in the literature for solving VRP, OVRP and VRPSPD problems. Keywords: Meta-heuristic algorithms, Vehicle Routing Problem, Open Vehicle Routing Problem, Simultaneously Pickup and Delivery, Ant Colony Optimization.

Heuristics for NP-hard optimization problems - simpler is better!?

Directory of Open Access Journals (Sweden)

Žerovnik Janez

2015-11-01

Full Text Available We provide several examples showing that local search, the most basic metaheuristics, may be a very competitive choice for solving computationally hard optimization problems. In addition, generation of starting solutions by greedy heuristics should be at least considered as one of very natural possibilities. In this critical survey, selected examples discussed include the traveling salesman, the resource-constrained project scheduling, the channel assignment, and computation of bounds for the Shannon capacity.

Search on Rugged Landscapes

DEFF Research Database (Denmark)

Billinger, Stephan; Stieglitz, Nils; Schumacher, Terry

2014-01-01

This paper presents findings from a laboratory experiment on human decision-making in a complex combinatorial task. We find strong evidence for a behavioral model of adaptive search. Success narrows down search to the neighborhood of the status quo, while failure promotes gradually more explorative...... for local improvements too early. We derive stylized decision rules that generate the search behavior observed in the experiment and discuss the implications of our findings for individual decision-making and organizational search....

Active living neighborhoods: is neighborhood walkability a key element for Belgian adolescents?

Directory of Open Access Journals (Sweden)

De Meester Femke

2012-01-01

Full Text Available Abstract Background In adult research, neighborhood walkability has been acknowledged as an important construct among the built environmental correlates of physical activity. Research into this association has only recently been extended to adolescents and the current empirical evidence is not consistent. This study investigated whether neighborhood walkability and neighborhood socioeconomic status (SES are associated with physical activity among Belgian adolescents and whether the association between neighborhood walkability and physical activity is moderated by neighborhood SES and gender. Methods In Ghent (Belgium, 32 neighborhoods were selected based on GIS-based walkability and SES derived from census data. In total, 637 adolescents (aged 13-15 year, 49.6% male participated in the study. Physical activity was assessed using accelerometers and the Flemish Physical Activity Questionnaire. To analyze the associations between neighborhood walkability, neighborhood SES and individual physical activity, multivariate multi-level regression analyses were conducted. Results Only in low-SES neighborhoods, neighborhood walkability was positively associated with accelerometer-based moderate to vigorous physical activity and the average activity level expressed in counts/minute. For active transport to and from school, cycling for transport during leisure time and sport during leisure time no association with neighborhood walkability nor, with neighborhood SES was found. For walking for transport during leisure time a negative association with neighborhood SES was found. Gender did not moderate the associations of neighborhood walkability and SES with adolescent physical activity. Conclusions Neighborhood walkability was related to accelerometer-based physical activity only among adolescent boys and girls living in low-SES neighborhoods. The relation of built environment to adolescent physical activity may depend on the context.

Heuristic Evaluation of E-Learning Courses: A Comparative Analysis of Two E-Learning Heuristic Sets

Science.gov (United States)

Zaharias, Panagiotis; Koutsabasis, Panayiotis

2012-01-01

Purpose: The purpose of this paper is to discuss heuristic evaluation as a method for evaluating e-learning courses and applications and more specifically to investigate the applicability and empirical use of two customized e-learning heuristic protocols. Design/methodology/approach: Two representative e-learning heuristic protocols were chosen…

Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problem

Directory of Open Access Journals (Sweden)

Kanagasabai Lenin

2015-03-01

Full Text Available This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality  of wolf is  possessing  both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm .

Multiobjective hyper heuristic scheme for system design and optimization

Science.gov (United States)

Rafique, Amer Farhan

2012-11-01

As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.

Neighborhood choices, neighborhood effects and housing vouchers

OpenAIRE

Davis, Morris A.; Gregory, Jesse; Hartley, Daniel A.; Tan, Kegon T. K.

2017-01-01

We study how households choose neighborhoods, how neighborhoods affect child ability, and how housing vouchers influence neighborhood choices and child outcomes. We use two new panel data sets with tract-level detail for Los Angeles county to estimate a dynamic model of optimal tract-level location choice for renting households and, separately, the impact of living in a given tract on child test scores (which we call "child ability" throughout). We simulate optimal location choices and change...

Positive Neighborhood Norms Buffer Ethnic Diversity Effects on Neighborhood Dissatisfaction, Perceived Neighborhood Disadvantage, and Moving Intentions.

Science.gov (United States)

Van Assche, Jasper; Asbrock, Frank; Roets, Arne; Kauff, Mathias

2018-05-01

Positive neighborhood norms, such as strong local networks, are critical to people's satisfaction with, perceived disadvantage of, and intentions to stay in their neighborhood. At the same time, local ethnic diversity is said to be detrimental for these community outcomes. Integrating both frameworks, we tested whether the negative consequences of diversity occur even when perceived social norms are positive. Study 1 ( N = 1,760 German adults) showed that perceptions of positive neighborhood norms buffered against the effects of perceived diversity on moving intentions via neighborhood satisfaction and perceived neighborhood disadvantage. Study 2 ( N = 993 Dutch adults) replicated and extended this moderated mediation model using other characteristics of diversity (i.e., objective and estimated minority proportions). Multilevel analyses again revealed consistent buffering effects of positive neighborhood norms. Our findings are discussed in light of the ongoing public and political debate concerning diversity and social and communal life.

A review of parameters and heuristics for guiding metabolic pathfinding.

Science.gov (United States)

Kim, Sarah M; Peña, Matthew I; Moll, Mark; Bennett, George N; Kavraki, Lydia E

2017-09-15

Recent developments in metabolic engineering have led to the successful biosynthesis of valuable products, such as the precursor of the antimalarial compound, artemisinin, and opioid precursor, thebaine. Synthesizing these traditionally plant-derived compounds in genetically modified yeast cells introduces the possibility of significantly reducing the total time and resources required for their production, and in turn, allows these valuable compounds to become cheaper and more readily available. Most biosynthesis pathways used in metabolic engineering applications have been discovered manually, requiring a tedious search of existing literature and metabolic databases. However, the recent rapid development of available metabolic information has enabled the development of automated approaches for identifying novel pathways. Computer-assisted pathfinding has the potential to save biochemists time in the initial discovery steps of metabolic engineering. In this paper, we review the parameters and heuristics used to guide the search in recent pathfinding algorithms. These parameters and heuristics capture information on the metabolic network structure, compound structures, reaction features, and organism-specificity of pathways. No one metabolic pathfinding algorithm or search parameter stands out as the best to use broadly for solving the pathfinding problem, as each method and parameter has its own strengths and shortcomings. As assisted pathfinding approaches continue to become more sophisticated, the development of better methods for visualizing pathway results and integrating these results into existing metabolic engineering practices is also important for encouraging wider use of these pathfinding methods.

Familiarity and recollection in heuristic decision making.

Science.gov (United States)

Schwikert, Shane R; Curran, Tim

2014-12-01

Heuristics involve the ability to utilize memory to make quick judgments by exploiting fundamental cognitive abilities. In the current study we investigated the memory processes that contribute to the recognition heuristic and the fluency heuristic, which are both presumed to capitalize on the byproducts of memory to make quick decisions. In Experiment 1, we used a city-size comparison task while recording event-related potentials (ERPs) to investigate the potential contributions of familiarity and recollection to the 2 heuristics. ERPs were markedly different for recognition heuristic-based decisions and fluency heuristic-based decisions, suggesting a role for familiarity in the recognition heuristic and recollection in the fluency heuristic. In Experiment 2, we coupled the same city-size comparison task with measures of subjective preexperimental memory for each stimulus in the task. Although previous literature suggests the fluency heuristic relies on recognition speed alone, our results suggest differential contributions of recognition speed and recollected knowledge to these decisions, whereas the recognition heuristic relies on familiarity. Based on these results, we created a new theoretical framework that explains decisions attributed to both heuristics based on the underlying memory associated with the choice options. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A Hybrid Heuristic Optimization Approach for Leak Detection in Pipe Networks Using Ordinal Optimization Approach and the Symbiotic Organism Search

Directory of Open Access Journals (Sweden)

Chao-Chih Lin

2017-10-01

Full Text Available A new transient-based hybrid heuristic approach is developed to optimize a transient generation process and to detect leaks in pipe networks. The approach couples the ordinal optimization approach (OOA and the symbiotic organism search (SOS to solve the optimization problem by means of iterations. A pipe network analysis model (PNSOS is first used to determine steady-state head distribution and pipe flow rates. The best transient generation point and its relevant valve operation parameters are optimized by maximizing the objective function of transient energy. The transient event is created at the chosen point, and the method of characteristics (MOC is used to analyze the transient flow. The OOA is applied to sift through the candidate pipes and the initial organisms with leak information. The SOS is employed to determine the leaks by minimizing the sum of differences between simulated and computed head at the observation points. Two synthetic leaking scenarios, a simple pipe network and a water distribution network (WDN, are chosen to test the performance of leak detection ordinal symbiotic organism search (LDOSOS. Leak information can be accurately identified by the proposed approach for both of the scenarios. The presented technique makes a remarkable contribution to the success of leak detection in the pipe networks.

Time constrained liner shipping network design

DEFF Research Database (Denmark)

Karsten, Christian Vad; Brouer, Berit Dangaard; Desaulniers, Guy

2017-01-01

We present a mathematical model and a solution method for the liner shipping network design problem. The model takes into account coordination between vessels and transit time restrictions on the cargo flow. The solution method is an improvement heuristic, where an integer program is solved...... iteratively to perform moves in a large neighborhood search. Our improvement heuristic is applicable as a real-time decision support tool for a liner shipping company. It can be used to find improvements to the network when evaluating changes in operating conditions or testing different scenarios...

Choice Neighborhood Grantees

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Department of Housing and Urban Development — Choice Neighborhoods grants transform distressed neighborhoods, public and assisted projects into viable and sustainable mixed-income neighborhoods by linking...

A greedy heuristic using adjoint functions for the optimization of seed and needle configurations in prostate seed implant

Energy Technology Data Exchange (ETDEWEB)

Yoo, Sua [Department of Radiation Oncology, Duke University Medical Center, Box 3295, Durham, NC 27710 (United States); Kowalok, Michael E [Department of Radiation Oncology, Virginia Commonwealth University Health System, 401 College St., PO Box 980058, Richmond, VA 23298-0058 (United States); Thomadsen, Bruce R [Department of Medical Physics, University of Wisconsin-Madison, 1530 MSC, 1300 University Ave., Madison, WI 53706 (United States); Henderson, Douglass L [Department of Engineering Physics, University of Wisconsin-Madison, 153 Engineering Research Bldg., 1500 Engineering Dr., Madison, WI 53706 (United States)

2007-02-07

We continue our work on the development of an efficient treatment-planning algorithm for prostate seed implants by incorporation of an automated seed and needle configuration routine. The treatment-planning algorithm is based on region of interest (ROI) adjoint functions and a greedy heuristic. As defined in this work, the adjoint function of an ROI is the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic uses a ratio of target and critical structure adjoint functions to rank seed positions according to their ability to irradiate the target ROI while sparing critical structure ROIs. Because seed positions are ranked in advance and because the greedy heuristic does not modify previously selected seed positions, the greedy heuristic constructs a complete seed configuration quickly. Isodose surface constraints determine the search space and the needle constraint limits the number of needles. This study additionally includes a methodology that scans possible combinations of these constraint values automatically. This automated selection scheme saves the user the effort of manually searching constraint values. With this method, clinically acceptable treatment plans are obtained in less than 2 min. For comparison, the branch-and-bound method used to solve a mixed integer-programming model took close to 2.5 h to arrive at a feasible solution. Both methods achieved good treatment plans, but the speedup provided by the greedy heuristic was a factor of approximately 100. This attribute makes this algorithm suitable for intra-operative real-time treatment planning.

A greedy heuristic using adjoint functions for the optimization of seed and needle configurations in prostate seed implant

International Nuclear Information System (INIS)

Yoo, Sua; Kowalok, Michael E; Thomadsen, Bruce R; Henderson, Douglass L

2007-01-01

We continue our work on the development of an efficient treatment-planning algorithm for prostate seed implants by incorporation of an automated seed and needle configuration routine. The treatment-planning algorithm is based on region of interest (ROI) adjoint functions and a greedy heuristic. As defined in this work, the adjoint function of an ROI is the sensitivity of the average dose in the ROI to a unit-strength brachytherapy source at any seed position. The greedy heuristic uses a ratio of target and critical structure adjoint functions to rank seed positions according to their ability to irradiate the target ROI while sparing critical structure ROIs. Because seed positions are ranked in advance and because the greedy heuristic does not modify previously selected seed positions, the greedy heuristic constructs a complete seed configuration quickly. Isodose surface constraints determine the search space and the needle constraint limits the number of needles. This study additionally includes a methodology that scans possible combinations of these constraint values automatically. This automated selection scheme saves the user the effort of manually searching constraint values. With this method, clinically acceptable treatment plans are obtained in less than 2 min. For comparison, the branch-and-bound method used to solve a mixed integer-programming model took close to 2.5 h to arrive at a feasible solution. Both methods achieved good treatment plans, but the speedup provided by the greedy heuristic was a factor of approximately 100. This attribute makes this algorithm suitable for intra-operative real-time treatment planning

Perceptions as the crucial link? The mediating role of neighborhood perceptions in the relationship between the neighborhood context and neighborhood cohesion.

Science.gov (United States)

Laméris, Joran; Hipp, John R; Tolsma, Jochem

2018-05-01

This study examines the effects of neighborhood racial in-group size, economic deprivation and the prevalence of crime on neighborhood cohesion among U.S. whites. We explore to what extent residents' perceptions of their neighborhood mediate these macro-micro relationships. We use a recent individual-level data set, the American Social Fabric Study (2012/2013), enriched with contextual-level data from the U.S. Census Bureau (2010) and employ multi-level structural equation models. We show that the racial in-group size is positively related to neighborhood cohesion and that neighborhood cohesion is lower in communities with a high crime rate. Individuals' perceptions of the racial in-group size partly mediate the relationship between the objective racial in-group size and neighborhood cohesion. Residents' perceptions of unsafety from crime also appear to be a mediating factor, not only for the objective crime rate but also for the objective racial in-group size. This is in line with our idea that racial stereotypes link racial minorities to crime whereby neighborhoods with a large non-white population are perceived to be more unsafe. Residents of the same neighborhood differ in how they perceive the degree of economic decay of the neighborhood and this causes them to evaluate neighborhood cohesion differently, however perceptions of neighborhood economic decay do not explain the link between the objective neighborhood context and neighborhood cohesion. Copyright © 2018. Published by Elsevier Inc.

Heuristic approach to train rescheduling

Directory of Open Access Journals (Sweden)

Mladenović Snežana

2007-01-01

Full Text Available Starting from the defined network topology and the timetable assigned beforehand, the paper considers a train rescheduling in respond to disturbances that have occurred. Assuming that the train trips are jobs, which require the elements of infrastructure - resources, it was done by the mapping of the initial problem into a special case of job shop scheduling problem. In order to solve the given problem, a constraint programming approach has been used. A support to fast finding "enough good" schedules is offered by original separation, bound and search heuristic algorithms. In addition, to improve the time performance, instead of the actual objective function with a large domain, a surrogate objective function is used with a smaller domain, if there is such. .

Neighborhood solutions for neighborhood problems: an empirically based violence prevention collaboration.

Science.gov (United States)

Randall, J; Swenson, C C; Henggeler, S W

1999-12-01

Youth antisocial behavior is influenced, in part, by neighborhood context. Yet, rather than attempting to ameliorate factors contributing to youth antisocial behavior, service dollars are primarily devoted to expensive and often ineffective out-of-home placements. This article describes the development and implementation of a collaborative partnership designed to empower an economically disadvantaged neighborhood to address violent criminal behavior, substance abuse, and other serious antisocial problems of its youth while maintaining youth in the neighborhood. Through a collaboration between a university research center and neighborhood stakeholders, services are being provided to address the key priorities identified by neighborhood residents, and extensive efforts are being made to develop family and neighborhood contexts that are conducive to prosocial youth behavior.

Job shop scheduling by local search

NARCIS (Netherlands)

Vaessens, R.J.M.; Aarts, E.H.L.; Lenstra, J.K.

1994-01-01

We survey solution methods for the job shop scheduling problem with an emphasis on local search. We discuss both cleterministic and randomized local search methods as well as the applied neighborhoods. We compare the computational performance of the various methods in terms of their effectiveness

A Novel Approach for Bi-Level Segmentation of Tuberculosis Bacilli Based on Meta-Heuristic Algorithms

Directory of Open Access Journals (Sweden)

AYAS, S.

2018-02-01

Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.

Heuristic errors in clinical reasoning.

Science.gov (United States)

Rylander, Melanie; Guerrasio, Jeannette

2016-08-01

Errors in clinical reasoning contribute to patient morbidity and mortality. The purpose of this study was to determine the types of heuristic errors made by third-year medical students and first-year residents. This study surveyed approximately 150 clinical educators inquiring about the types of heuristic errors they observed in third-year medical students and first-year residents. Anchoring and premature closure were the two most common errors observed amongst third-year medical students and first-year residents. There was no difference in the types of errors observed in the two groups. Errors in clinical reasoning contribute to patient morbidity and mortality Clinical educators perceived that both third-year medical students and first-year residents committed similar heuristic errors, implying that additional medical knowledge and clinical experience do not affect the types of heuristic errors made. Further work is needed to help identify methods that can be used to reduce heuristic errors early in a clinician's education. © 2015 John Wiley & Sons Ltd.

A synergetic combination of small and large neighborhood schemes in developing an effective procedure for solving the job shop scheduling problem.

Science.gov (United States)

Amirghasemi, Mehrdad; Zamani, Reza

2014-01-01

This paper presents an effective procedure for solving the job shop problem. Synergistically combining small and large neighborhood schemes, the procedure consists of four components, namely (i) a construction method for generating semi-active schedules by a forward-backward mechanism, (ii) a local search for manipulating a small neighborhood structure guided by a tabu list, (iii) a feedback-based mechanism for perturbing the solutions generated, and (iv) a very large-neighborhood local search guided by a forward-backward shifting bottleneck method. The combination of shifting bottleneck mechanism and tabu list is used as a means of the manipulation of neighborhood structures, and the perturbation mechanism employed diversifies the search. A feedback mechanism, called repeat-check, detects consequent repeats and ignites a perturbation when the total number of consecutive repeats for two identical makespan values reaches a given threshold. The results of extensive computational experiments on the benchmark instances indicate that the combination of these four components is synergetic, in the sense that they collectively make the procedure fast and robust.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

Directory of Open Access Journals (Sweden)

Tashkova Katerina

2011-10-01

Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

Science.gov (United States)

Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

2011-10-11

We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and

The use of meta-heuristics for airport gate assignment

DEFF Research Database (Denmark)

Cheng, Chun-Hung; Ho, Sin C.; Kwan, Cheuk-Lam

2012-01-01

proposed to generate good solutions within a reasonable timeframe. In this work, we attempt to assess the performance of three meta-heuristics, namely, genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and a hybrid approach based on SA and TS. Flight data from Incheon International Airport...... are collected to carry out the computational comparison. Although the literature has documented these algorithms, this work may be a first attempt to evaluate their performance using a set of realistic flight data....

A Pareto archive floating search procedure for solving multi-objective flexible job shop scheduling problem

Directory of Open Access Journals (Sweden)

J. S. Sadaghiani

2014-04-01

Full Text Available Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.

Algorithm for shortest path search in Geographic Information Systems by using reduced graphs.

Science.gov (United States)

Rodríguez-Puente, Rafael; Lazo-Cortés, Manuel S

2013-01-01

The use of Geographic Information Systems has increased considerably since the eighties and nineties. As one of their most demanding applications we can mention shortest paths search. Several studies about shortest path search show the feasibility of using graphs for this purpose. Dijkstra's algorithm is one of the classic shortest path search algorithms. This algorithm is not well suited for shortest path search in large graphs. This is the reason why various modifications to Dijkstra's algorithm have been proposed by several authors using heuristics to reduce the run time of shortest path search. One of the most used heuristic algorithms is the A* algorithm, the main goal is to reduce the run time by reducing the search space. This article proposes a modification of Dijkstra's shortest path search algorithm in reduced graphs. It shows that the cost of the path found in this work, is equal to the cost of the path found using Dijkstra's algorithm in the original graph. The results of finding the shortest path, applying the proposed algorithm, Dijkstra's algorithm and A* algorithm, are compared. This comparison shows that, by applying the approach proposed, it is possible to obtain the optimal path in a similar or even in less time than when using heuristic algorithms.

Hydro-Thermal-Wind Generation Scheduling Considering Economic and Environmental Factors Using Heuristic Algorithms

Directory of Open Access Journals (Sweden)

Suresh K. Damodaran

2018-02-01

Full Text Available Hydro-thermal-wind generation scheduling (HTWGS with economic and environmental factors is a multi-objective complex nonlinear power system optimization problem with many equality and inequality constraints. The objective of the problem is to generate an hour-by-hour optimum schedule of hydro-thermal-wind power plants to attain the least emission of pollutants from thermal plants and a reduced generation cost of thermal and wind plants for a 24-h period, satisfying the system constraints. The paper presents a detailed framework of the HTWGS problem and proposes a modified particle swarm optimization (MPSO algorithm for evolving a solution. The competency of selected heuristic algorithms, representing different heuristic groups, viz. the binary coded genetic algorithm (BCGA, particle swarm optimization (PSO, improved harmony search (IHS, and JAYA algorithm, for searching for an optimal solution to HTWGS considering economic and environmental factors was investigated in a trial system consisting of a multi-stream cascaded system with four reservoirs, three thermal plants, and two wind plants. Appropriate mathematical models were used for representing the water discharge, generation cost, and pollutant emission of respective power plants incorporated in the system. Statistical analysis was performed to check the consistency and reliability of the proposed algorithm. The simulation results indicated that the proposed MPSO algorithm provided a better solution to the problem of HTWGS, with a reduced generation cost and the least emission, when compared with the other heuristic algorithms considered.

Non-uniform cosine modulated filter banks using meta-heuristic algorithms in CSD space

Directory of Open Access Journals (Sweden)

Shaeen Kalathil

2015-11-01

Full Text Available This paper presents an efficient design of non-uniform cosine modulated filter banks (CMFB using canonic signed digit (CSD coefficients. CMFB has got an easy and efficient design approach. Non-uniform decomposition can be easily obtained by merging the appropriate filters of a uniform filter bank. Only the prototype filter needs to be designed and optimized. In this paper, the prototype filter is designed using window method, weighted Chebyshev approximation and weighted constrained least square approximation. The coefficients are quantized into CSD, using a look-up-table. The finite precision CSD rounding, deteriorates the filter bank performances. The performances of the filter bank are improved using suitably modified meta-heuristic algorithms. The different meta-heuristic algorithms which are modified and used in this paper are Artificial Bee Colony algorithm, Gravitational Search algorithm, Harmony Search algorithm and Genetic algorithm and they result in filter banks with less implementation complexity, power consumption and area requirements when compared with those of the conventional continuous coefficient non-uniform CMFB.

An integral heuristic

International Nuclear Information System (INIS)

Kauffman, L.H.

1990-01-01

This paper gives a heuristic derivation of the skein relation for the Homfly polynomial in an integral formalism. The derivation is formally correct but highly simplified. In the light of Witten's proposal for invariants of links via functional integrals, it is useful to have a formal pattern to compare with the complexities of the full approach. The formalism is a heuristic. However, it is closely related to the actual structure of the Witten functional integral

Further heuristics for $k$-means: The merge-and-split heuristic and the $(k,l)$-means

OpenAIRE

Nielsen, Frank; Nock, Richard

2014-01-01

Finding the optimal $k$-means clustering is NP-hard in general and many heuristics have been designed for minimizing monotonically the $k$-means objective. We first show how to extend Lloyd's batched relocation heuristic and Hartigan's single-point relocation heuristic to take into account empty-cluster and single-point cluster events, respectively. Those events tend to increasingly occur when $k$ or $d$ increases, or when performing several restarts. First, we show that those special events ...

Reconsidering "evidence" for fast-and-frugal heuristics.

Science.gov (United States)

Hilbig, Benjamin E

2010-12-01

In several recent reviews, authors have argued for the pervasive use of fast-and-frugal heuristics in human judgment. They have provided an overview of heuristics and have reiterated findings corroborating that such heuristics can be very valid strategies leading to high accuracy. They also have reviewed previous work that implies that simple heuristics are actually used by decision makers. Unfortunately, concerning the latter point, these reviews appear to be somewhat incomplete. More important, previous conclusions have been derived from investigations that bear some noteworthy methodological limitations. I demonstrate these by proposing a new heuristic and provide some novel critical findings. Also, I review some of the relevant literature often not-or only partially-considered. Overall, although some fast-and-frugal heuristics indeed seem to predict behavior at times, there is little to no evidence for others. More generally, the empirical evidence available does not warrant the conclusion that heuristics are pervasively used.

Monte-Carlo Tree Search for Poly-Y

NARCIS (Netherlands)

Wevers, L.; te Brinke, Steven

2014-01-01

Monte-Carlo tree search (MCTS) is a heuristic search algorithm that has recently been very successful in the games of Go and Hex. In this paper, we describe an MCTS player for the game of Poly-Y, which is a connection game similar to Hex. Our player won the CodeCup 2014 AI programming competition.

Combined heuristic with fuzzy system to transmission system expansion planning

Energy Technology Data Exchange (ETDEWEB)

Silva Sousa, Aldir; Asada, Eduardo N. [University of Sao Paulo, Sao Carlos School of Engineering, Department of Electrical Engineering Av. Trabalhador Sao-carlense, 400, 13566-590 Sao Carlos, SP (Brazil)

2011-01-15

A heuristic algorithm that employs fuzzy logic is proposed to the power system transmission expansion planning problem. The algorithm is based on the divide to conquer strategy, which is controlled by the fuzzy system. The algorithm provides high quality solutions with the use of fuzzy decision making, which is based on nondeterministic criteria to guide the search. The fuzzy system provides a self-adjusting mechanism that eliminates the manual adjustment of parameters to each system being solved. (author)

Augmented neural networks and problem structure-based heuristics for the bin-packing problem

Science.gov (United States)

Kasap, Nihat; Agarwal, Anurag

2012-08-01

In this article, we report on a research project where we applied augmented-neural-networks (AugNNs) approach for solving the classical bin-packing problem (BPP). AugNN is a metaheuristic that combines a priority rule heuristic with the iterative search approach of neural networks to generate good solutions fast. This is the first time this approach has been applied to the BPP. We also propose a decomposition approach for solving harder BPP, in which subproblems are solved using a combination of AugNN approach and heuristics that exploit the problem structure. We discuss the characteristics of problems on which such problem structure-based heuristics could be applied. We empirically show the effectiveness of the AugNN and the decomposition approach on many benchmark problems in the literature. For the 1210 benchmark problems tested, 917 problems were solved to optimality and the average gap between the obtained solution and the upper bound for all the problems was reduced to under 0.66% and computation time averaged below 33 s per problem. We also discuss the computational complexity of our approach.

Simulated parallel annealing within a neighborhood for optimization of biomechanical systems.

Science.gov (United States)

Higginson, J S; Neptune, R R; Anderson, F C

2005-09-01

Optimization problems for biomechanical systems have become extremely complex. Simulated annealing (SA) algorithms have performed well in a variety of test problems and biomechanical applications; however, despite advances in computer speed, convergence to optimal solutions for systems of even moderate complexity has remained prohibitive. The objective of this study was to develop a portable parallel version of a SA algorithm for solving optimization problems in biomechanics. The algorithm for simulated parallel annealing within a neighborhood (SPAN) was designed to minimize interprocessor communication time and closely retain the heuristics of the serial SA algorithm. The computational speed of the SPAN algorithm scaled linearly with the number of processors on different computer platforms for a simple quadratic test problem and for a more complex forward dynamic simulation of human pedaling.

Elective course student sectioning at Danish high schools

DEFF Research Database (Denmark)

Kristiansen, Simon; Stidsen, Thomas Riis

2016-01-01

. This paper presents an Adaptive Large Neighborhood Search heuristic for the ESCC. The algorithm is applied to 80 real-life instances from Danish high schools and compared with solutions found by using the state-of-the-art MIP solver Gurobi. The algorithm has been implemented in the commercial product Lectio......, and is thereby available for approximately 200 high schools in Denmark....

Modelling antibody side chain conformations using heuristic database search.

Science.gov (United States)

Ritchie, D W; Kemp, G J

1997-01-01

We have developed a knowledge-based system which models the side chain conformations of residues in the variable domains of antibody Fv fragments. The system is written in Prolog and uses an object-oriented database of aligned antibody structures in conjunction with a side chain rotamer library. The antibody database provides 3-dimensional clusters of side chain conformations which can be copied en masse into the model structure. The object-oriented database architecture facilitates a navigational style of database access, necessary to assemble side chains clusters. Around 60% of the model is built using side chain clusters and this eliminates much of the combinatorial complexity associated with many other side chain placement algorithms. Construction and placement of side chain clusters is guided by a heuristic cost function based on a simple model of side chain packing interactions. Even with a simple model, we find that a large proportion of side chain conformations are modelled accurately. We expect our approach could be used with other homologous protein families, in addition to antibodies, both to improve the quality of model structures and to give a "smart start" to the side chain placement problem.

Heuristics Reasoning in Diagnostic Judgment.

Science.gov (United States)

O'Neill, Eileen S.

1995-01-01

Describes three heuristics--short-cut mental strategies that streamline information--relevant to diagnostic reasoning: accessibility, similarity, and anchoring and adjustment. Analyzes factors thought to influence heuristic reasoning and presents interventions to be tested for nursing practice and education. (JOW)

Heuristic thinking makes a chemist smart.

Science.gov (United States)

Graulich, Nicole; Hopf, Henning; Schreiner, Peter R

2010-05-01

We focus on the virtually neglected use of heuristic principles in understanding and teaching of organic chemistry. As human thinking is not comparable to computer systems employing factual knowledge and algorithms--people rarely make decisions through careful considerations of every possible event and its probability, risks or usefulness--research in science and teaching must include psychological aspects of the human decision making processes. Intuitive analogical and associative reasoning and the ability to categorize unexpected findings typically demonstrated by experienced chemists should be made accessible to young learners through heuristic concepts. The psychology of cognition defines heuristics as strategies that guide human problem-solving and deciding procedures, for example with patterns, analogies, or prototypes. Since research in the field of artificial intelligence and current studies in the psychology of cognition have provided evidence for the usefulness of heuristics in discovery, the status of heuristics has grown into something useful and teachable. In this tutorial review, we present a heuristic analysis of a familiar fundamental process in organic chemistry--the cyclic six-electron case, and we show that this approach leads to a more conceptual insight in understanding, as well as in teaching and learning.

Neighborhood context and health: How neighborhood social capital affects individual health

NARCIS (Netherlands)

Mohnen, S.M.

2012-01-01

Does it matter for my health in which neighborhood I live? The fact is, health is determined not only by individual characteristics but also by the neighborhood in which someone lives. This thesis shows that health clusters in Dutch neighborhoods and that this is not only a composition effect (that

Heuristic Approach for Balancing Shift Schedules

International Nuclear Information System (INIS)

Kim, Dae Ho; Yun, Young Su; Lee, Yong Hee

2005-01-01

In this paper, a heuristic approach for balancing shift schedules is proposed. For the shift schedules, various constraints which have usually been considered in realworld industry are used, and the objective is to minimize the differences of the workloads in each workgroup. The constraints and objective function are implemented in the proposed heuristic approach. Using a simple instance, the efficiency of the proposed heuristic approach is proved

Optimization of Charge/Discharge Coordination to Satisfy Network Requirements Using Heuristic Algorithms in Vehicle-to-Grid Concept

Directory of Open Access Journals (Sweden)

DOGAN, A.

2018-02-01

Full Text Available Image thresholding is the most crucial step in microscopic image analysis to distinguish bacilli objects causing of tuberculosis disease. Therefore, several bi-level thresholding algorithms are widely used to increase the bacilli segmentation accuracy. However, bi-level microscopic image thresholding problem has not been solved using optimization algorithms. This paper introduces a novel approach for the segmentation problem using heuristic algorithms and presents visual and quantitative comparisons of heuristic and state-of-art thresholding algorithms. In this study, well-known heuristic algorithms such as Firefly Algorithm, Particle Swarm Optimization, Cuckoo Search, Flower Pollination are used to solve bi-level microscopic image thresholding problem, and the results are compared with the state-of-art thresholding algorithms such as K-Means, Fuzzy C-Means, Fast Marching. Kapur's entropy is chosen as the entropy measure to be maximized. Experiments are performed to make comparisons in terms of evaluation metrics and execution time. The quantitative results are calculated based on ground truth segmentation. According to the visual results, heuristic algorithms have better performance and the quantitative results are in accord with the visual results. Furthermore, experimental time comparisons show the superiority and effectiveness of the heuristic algorithms over traditional thresholding algorithms.

Adaptive switching gravitational search algorithm: an attempt to ...

Indian Academy of Sciences (India)

Nor Azlina Ab Aziz

An adaptive gravitational search algorithm (GSA) that switches between synchronous and ... genetic algorithm (GA), bat-inspired algorithm (BA) and grey wolf optimizer (GWO). ...... heuristic with applications in applied electromagnetics. Prog.

A discrete firefly meta-heuristic with local search for makespan minimization in permutation flow shop scheduling problems

Directory of Open Access Journals (Sweden)

Nader Ghaffari-Nasab

2010-07-01

Full Text Available During the past two decades, there have been increasing interests on permutation flow shop with different types of objective functions such as minimizing the makespan, the weighted mean flow-time etc. The permutation flow shop is formulated as a mixed integer programming and it is classified as NP-Hard problem. Therefore, a direct solution is not available and meta-heuristic approaches need to be used to find the near-optimal solutions. In this paper, we present a new discrete firefly meta-heuristic to minimize the makespan for the permutation flow shop scheduling problem. The results of implementation of the proposed method are compared with other existing ant colony optimization technique. The preliminary results indicate that the new proposed method performs better than the ant colony for some well known benchmark problems.

HEURISTIC APPROACHES FOR PORTFOLIO OPTIMIZATION

OpenAIRE

Manfred Gilli, Evis Kellezi

2000-01-01

The paper first compares the use of optimization heuristics to the classical optimization techniques for the selection of optimal portfolios. Second, the heuristic approach is applied to problems other than those in the standard mean-variance framework where the classical optimization fails.

Ecological neighborhoods as a framework for umbrella species selection

Science.gov (United States)

Stuber, Erica F.; Fontaine, Joseph J.

2018-01-01

Umbrella species are typically chosen because they are expected to confer protection for other species assumed to have similar ecological requirements. Despite its popularity and substantial history, the value of the umbrella species concept has come into question because umbrella species chosen using heuristic methods, such as body or home range size, are not acting as adequate proxies for the metrics of interest: species richness or population abundance in a multi-species community for which protection is sought. How species associate with habitat across ecological scales has important implications for understanding population size and species richness, and therefore may be a better proxy for choosing an umbrella species. We determined the spatial scales of ecological neighborhoods important for predicting abundance of 8 potential umbrella species breeding in Nebraska using Bayesian latent indicator scale selection in N-mixture models accounting for imperfect detection. We compare the conservation value measured as collective avian abundance under different umbrella species selected following commonly used criteria and selected based on identifying spatial land cover characteristics within ecological neighborhoods that maximize collective abundance. Using traditional criteria to select an umbrella species resulted in sub-maximal expected collective abundance in 86% of cases compared to selecting an umbrella species based on land cover characteristics that maximized collective abundance directly. We conclude that directly assessing the expected quantitative outcomes, rather than ecological proxies, is likely the most efficient method to maximize the potential for conservation success under the umbrella species concept.

Heuristic learning parameter identification for surveillance and diagnostics of nuclear power plants

International Nuclear Information System (INIS)

Machado, E.L.

1983-01-01

A new method of heuristic reinforcement learning was developed for parameter identification purposes. In essence, this new parameter identification technique is based on the idea of breaking a multidimensional search for the minimum of a given functional into a set of unidirectional searches in parameter space. Each search situation is associated with one block in a memory organized into cells, where the information learned about the situations is stored (e.g. the optimal directions in parameter space). Whenever the search falls into an existing memory cell, the system chooses the learned direction. For new search situations, the system creates additional memory cells. This algorithm imitates the following cognitive process: 1) characterize a situation, 2) select an optimal action, 3) evaluate the consequences of the action, and 4) memorize the results for future use. As a result, this algorithm is trainable in the sense that it can learn from previous experience within a specific class of parameter identification problems

Proposing New Heuristic Approaches for Preventive Maintenance Scheduling

Directory of Open Access Journals (Sweden)

majid Esmailian

2013-08-01

Full Text Available The purpose of preventive maintenance management is to perform a series of tasks that prevent or minimize production breakdowns and improve reliability of production facilities. An important objective of preventive maintenance management is to minimize downtime of production facilities. In order to accomplish this objective, personnel should efficiently allocate resources and determine an effective maintenance schedule. Gopalakrishnan (1997 developed a mathematical model and four heuristic approaches to solve the preventive maintenance scheduling problem of assigning skilled personnel to work with tasks that require a set of corresponding skills. However, there are several limitations in the prior work in this area of research. The craft combination problem has not been solved because the craft combination is assumed as given. The craft combination problem concerns the computation of all combinations of assigning multi skilled workers to accomplishment of a particular task. In fact, determining craft combinations is difficult because of the exponential number of craft combinations that are possible. This research provides a heuristic approach for determining the craft combination and four new heuristic approach solution for the preventive maintenance scheduling problem with multi skilled workforce constraints. In order to examine the new heuristic approach and to compare the new heuristic approach with heuristic approach of Gopalakrishnan (1997, 81 standard problems have been generated based on the criterion suggested by from Gopalakrishnan (1997. The average solution quality (SQ of the new heuristic approaches is 1.86% and in old heuristic approaches is 8.32%. The solution time of new heuristic approaches are shorter than old heuristic approaches. The solution time of new heuristic approaches is 0.78 second and old heuristic approaches is 6.43 second, but the solution time of mathematical model provided by Gopalakrishnan (1997 is 152 second. �

Ant colony system (ACS with hybrid local search to solve vehicle routing problems

Directory of Open Access Journals (Sweden)

Suphan Sodsoon

2016-02-01

Full Text Available This research applied an Ant Colony System algorithm with a Hybrid Local Search to solve Vehicle Routing Problems (VRP from a single depot when the customers’ requirements are known. VRP is an NP-hard optimization problem and has usually been successfully solved optimum by heuristics. A fleet of vehicles of a specific capacity are used to serve a number of customers at minimum cost, without violating the constraints of vehicle capacity. There are meta-heuristic approaches to solve these problems, such as Simulated Annealing, Genetic Algorithm, Tabu Search and the Ant Colony System algorithm. In this case a hybrid local search was used (Cross-Exchange, Or-Opt and 2-Opt algorithm with an Ant Colony System algorithm. The Experimental Design was tested on 7 various problems from the data set online in the OR-Library. There are five different problems in which customers are randomly distributed with the depot in an approximately central location. The customers were grouped into clusters. The results are evaluated in terms of optimal routes using optimal distances. The experimental results are compared with those obtained from meta-heuristics and they show that the proposed method outperforms six meta-heuristics in the literature.

Learning process mapping heuristics under stochastic sampling overheads

Science.gov (United States)

Ieumwananonthachai, Arthur; Wah, Benjamin W.

1991-01-01

A statistical method was developed previously for improving process mapping heuristics. The method systematically explores the space of possible heuristics under a specified time constraint. Its goal is to get the best possible heuristics while trading between the solution quality of the process mapping heuristics and their execution time. The statistical selection method is extended to take into consideration the variations in the amount of time used to evaluate heuristics on a problem instance. The improvement in performance is presented using the more realistic assumption along with some methods that alleviate the additional complexity.

Cultural heuristics in risk assessment of HIV/AIDS.

Science.gov (United States)

Bailey, Ajay; Hutter, Inge

2006-01-01

Behaviour change models in HIV prevention tend to consider that risky sexual behaviours reflect risk assessments and that by changing risk assessments behaviour can be changed. Risk assessment is however culturally constructed. Individuals use heuristics or bounded cognitive devices derived from broader cultural meaning systems to rationalize uncertainty. In this study, we identify some of the cultural heuristics used by migrant men in Goa, India to assess their risk of HIV infection from different sexual partners. Data derives from a series of in-depth interviews and a locally informed survey. Cultural heuristics identified include visual heuristics, heuristics of gender roles, vigilance and trust. The paper argues that, for more culturally informed HIV/AIDS behaviour change interventions, knowledge of cultural heuristics is essential.

Durham Neighborhood Compass Neighborhoods

Data.gov (United States)

City and County of Durham, North Carolina — The Durham Neighborhood Compass is a quantitative indicators project with qualitative values, integrating data from local government, the Census Bureau and other...

Comparison of Heuristics for Inhibitory Rule Optimization

KAUST Repository

Alsolami, Fawaz; Chikalov, Igor; Moshkov, Mikhail

2014-01-01

Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.

Paranoid thinking as a heuristic.

Science.gov (United States)

Preti, Antonio; Cella, Matteo

2010-08-01

Paranoid thinking can be viewed as a human heuristic used by individuals to deal with uncertainty during stressful situations. Under stress, individuals are likely to emphasize the threatening value of neutral stimuli and increase the reliance on paranoia-based heuristic to interpreter events and guide their decisions. Paranoid thinking can also be activated by stress arising from the possibility of losing a good opportunity; this may result in an abnormal allocation of attentional resources to social agents. A better understanding of the interplay between cognitive heuristics and emotional processes may help to detect situations in which paranoid thinking is likely to exacerbate and improve intervention for individuals with delusional disorders.

Perceptions as the crucial link? The mediating role of neighborhood perceptions in the relationship between the neighborhood context and neighborhood cohesion

NARCIS (Netherlands)

Lamé ris, J.G.; Hipp, J.R.; Tolsma, J.

2018-01-01

This study examines the effects of neighborhood racial in-group size, economic deprivation and the prevalence of crime on neighborhood cohesion among U.S. whites. We explore to what extent residents' perceptions of their neighborhood mediate these macro-micro relationships. We use a recent

Heuristics Made Easy: An Effort-Reduction Framework

Science.gov (United States)

Shah, Anuj K.; Oppenheimer, Daniel M.

2008-01-01

In this article, the authors propose a new framework for understanding and studying heuristics. The authors posit that heuristics primarily serve the purpose of reducing the effort associated with a task. As such, the authors propose that heuristics can be classified according to a small set of effort-reduction principles. The authors use this…

A hybrid heuristic algorithm for the open-pit-mining operational planning problem.

OpenAIRE

Souza, Marcone Jamilson Freitas; Coelho, Igor Machado; Ribas, Sabir; Santos, Haroldo Gambini; Merschmann, Luiz Henrique de Campos

2010-01-01

This paper deals with the Open-Pit-Mining Operational Planning problem with dynamic truck allocation. The objective is to optimize mineral extraction in the mines by minimizing the number of mining trucks used to meet production goals and quality requirements. According to the literature, this problem is NPhard, so a heuristic strategy is justified. We present a hybrid algorithm that combines characteristics of two metaheuristics: Greedy Randomized Adaptive Search Procedures and General Varia...

Tabu search for target-radar assignment

DEFF Research Database (Denmark)

Hindsberger, Magnus; Vidal, Rene Victor Valqui

2000-01-01

In the paper the problem of assigning air-defense illumination radars to enemy targets is presented. A tabu search metaheuristic solution is described and the results achieved are compared to those of other heuristic approaches, implementation and experimental aspects are discussed. It is argued ...

Making decisions at the end of life when caring for a person with dementia: a literature review to explore the potential use of heuristics in difficult decision-making.

Science.gov (United States)

Mathew, R; Davies, N; Manthorpe, J; Iliffe, S

2016-07-19

Decision-making, when providing care and treatment for a person with dementia at the end of life, can be complex and challenging. There is a lack of guidance available to support practitioners and family carers, and even those experienced in end of life dementia care report a lack of confidence in decision-making. It is thought that the use of heuristics (rules of thumb) may aid decision-making. The aim of this study is to identify whether heuristics are used in end of life dementia care, and if so, to identify the context in which they are being used. A narrative literature review was conducted taking a systematic approach to the search strategy, using the Centre for Reviews and Dissemination guidelines. Rapid appraisal methodology was used in order to source specific and relevant literature regarding the use of heuristics in end of life dementia care. A search using terms related to dementia, palliative care and decision-making was conducted across 4 English language electronic databases (MEDLINE, EMBASE, PsycINFO and CINAHL) in 2015. The search identified 12 papers that contained an algorithm, guideline, decision tool or set of principles that we considered compatible with heuristic decision-making. The papers addressed swallowing and feeding difficulties, the treatment of pneumonia, management of pain and agitation, rationalising medication, ending life-sustaining treatment, and ensuring a good death. The use of heuristics in palliative or end of life dementia care is not described in the research literature. However, this review identified important decision-making principles, which are largely a reflection of expert opinion. These principles may have the potential to be developed into simple heuristics that could be used in practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

A comparative analysis of meta-heuristic methods for power management of a dual energy storage system for electric vehicles

International Nuclear Information System (INIS)

Trovão, João P.; Antunes, Carlos Henggeler

2015-01-01

Highlights: • Two meta-heuristic approaches are evaluated for multi-ESS management in electric vehicles. • An online global energy management strategy with two different layers is studied. • Meta-heuristic techniques are used to define optimized energy sharing mechanisms. • A comparative analysis for ARTEMIS driving cycle is addressed. • The effectiveness of the double-layer management with meta-heuristic is presented. - Abstract: This work is focused on the performance evaluation of two meta-heuristic approaches, simulated annealing and particle swarm optimization, to deal with power management of a dual energy storage system for electric vehicles. The proposed strategy is based on a global energy management system with two layers: long-term (energy) and short-term (power) management. A rule-based system deals with the long-term (strategic) layer and for the short-term (action) layer meta-heuristic techniques are developed to define optimized online energy sharing mechanisms. Simulations have been made for several driving cycles to validate the proposed strategy. A comparative analysis for ARTEMIS driving cycle is presented evaluating three performance indicators (computation time, final value of battery state of charge, and minimum value of supercapacitors state of charge) as a function of input parameters. The results show the effectiveness of an implementation based on a double-layer management system using meta-heuristic methods for online power management supported by a rule set that restricts the search space

Reexamining Our Bias against Heuristics

Science.gov (United States)

McLaughlin, Kevin; Eva, Kevin W.; Norman, Geoff R.

2014-01-01

Using heuristics offers several cognitive advantages, such as increased speed and reduced effort when making decisions, in addition to allowing us to make decision in situations where missing data do not allow for formal reasoning. But the traditional view of heuristics is that they trade accuracy for efficiency. Here the authors discuss sources…

Cooperative heuristic multi-agent planning

NARCIS (Netherlands)

De Weerdt, M.M.; Tonino, J.F.M.; Witteveen, C.

2001-01-01

In this paper we will use the framework to study cooperative heuristic multi-agent planning. During the construction of their plans, the agents use a heuristic function inspired by the FF planner (l3l). At any time in the process of planning the agents may exchange available resources, or they may

Towards improving searches for optimal phylogenies.

Science.gov (United States)

Ford, Eric; St John, Katherine; Wheeler, Ward C

2015-01-01

Finding the optimal evolutionary history for a set of taxa is a challenging computational problem, even when restricting possible solutions to be "tree-like" and focusing on the maximum-parsimony optimality criterion. This has led to much work on using heuristic tree searches to find approximate solutions. We present an approach for finding exact optimal solutions that employs and complements the current heuristic methods for finding optimal trees. Given a set of taxa and a set of aligned sequences of characters, there may be subsets of characters that are compatible, and for each such subset there is an associated (possibly partially resolved) phylogeny with edges corresponding to each character state change. These perfect phylogenies serve as anchor trees for our constrained search space. We show that, for sequences with compatible sites, the parsimony score of any tree [Formula: see text] is at least the parsimony score of the anchor trees plus the number of inferred changes between [Formula: see text] and the anchor trees. As the maximum-parsimony optimality score is additive, the sum of the lower bounds on compatible character partitions provides a lower bound on the complete alignment of characters. This yields a region in the space of trees within which the best tree is guaranteed to be found; limiting the search for the optimal tree to this region can significantly reduce the number of trees that must be examined in a search of the space of trees. We analyze this method empirically using four different biological data sets as well as surveying 400 data sets from the TreeBASE repository, demonstrating the effectiveness of our technique in reducing the number of steps in exact heuristic searches for trees under the maximum-parsimony optimality criterion. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Harmony Search for Balancing Two-sided Assembly Lines

Directory of Open Access Journals (Sweden)

Hindriyanto Dwi Purnomo

2012-01-01

Full Text Available Two-sided assembly lines balancing problems are important problem for large-sized products such as cars and buses, in which, tasks operations can be performed in the two sides of the line. In this paper, Harmony Search algorithm is proposed to solve two-sided assembly lines balancing problems type-I (TALBP-I. The proposed method adopts the COMSOAL heuristic and specific features of TALBP in the Harmony operators – the harmony memory consideration, random selection and pitch adjustment – in order to maintain the local and global search. The proposed method is evaluated based on 6 benchmark problems that are commonly used in TALBP. The experiment results show that the proposed method work well and produces better solution than the heuristic method and genetic algorithm.

One visual search, many memory searches: An eye-tracking investigation of hybrid search.

Science.gov (United States)

Drew, Trafton; Boettcher, Sage E P; Wolfe, Jeremy M

2017-09-01

Suppose you go to the supermarket with a shopping list of 10 items held in memory. Your shopping expedition can be seen as a combination of visual search and memory search. This is known as "hybrid search." There is a growing interest in understanding how hybrid search tasks are accomplished. We used eye tracking to examine how manipulating the number of possible targets (the memory set size [MSS]) changes how observers (Os) search. We found that dwell time on each distractor increased with MSS, suggesting a memory search was being executed each time a new distractor was fixated. Meanwhile, although the rate of refixation increased with MSS, it was not nearly enough to suggest a strategy that involves repeatedly searching visual space for subgroups of the target set. These data provide a clear demonstration that hybrid search tasks are carried out via a "one visual search, many memory searches" heuristic in which Os examine items in the visual array once with a very low rate of refixations. For each item selected, Os activate a memory search that produces logarithmic response time increases with increased MSS. Furthermore, the percentage of distractors fixated was strongly modulated by the MSS: More items in the MSS led to a higher percentage of fixated distractors. Searching for more potential targets appears to significantly alter how Os approach the task, ultimately resulting in more eye movements and longer response times.

China’s Neighborhood Environment and Options for Neighborhood Strategy

Institute of Scientific and Technical Information of China (English)

ZHOU FANGYIN

2016-01-01

Since the 18th CPC National Congress,especially since the Central Conference on Work Relating to Neighborhood Diplomacy held in October 2013,China’s neighborhood diplomacy has been energetic,proactive and promising,achieving important results in several aspects.At the same time,it is also in face of challenges

Neighborhood Quality and Labor Market Outcomes: Evidence from Quasi-Random Neighborhood Assignment of Immigrants

DEFF Research Database (Denmark)

Damm, Anna Piil

2012-01-01

of men living in the neighborhood, but positively affected by the employment rate of non-Western immigrant men and co-national men living in the neighborhood. This is strong evidence that immigrants find jobs in part through their employed immigrant and co-ethnic contacts in the neighborhood of residence...... successfully addresses the methodological problem of endogenous neighborhood selection. Taking account of location sorting, living in a socially deprived neighborhood does not affect labor market outcomes of refugee men. Furthermore, their labor market outcomes are not affected by the overall employment rate...

Modeling and Solving the Train Pathing Problem

Directory of Open Access Journals (Sweden)

Chuen-Yih Chen

2009-04-01

Full Text Available In a railroad system, train pathing is concerned with the assignment of trains to links and tracks, and train timetabling allocates time slots to trains. In this paper, we present an optimization heuristic to solve the train pathing and timetabling problem. This heuristic allows the dwell time of trains in a station or link to be dependent on the assigned tracks. It also allows the minimum clearance time between the trains to depend on their relative status. The heuristic generates a number of alternative paths for each train service in the initialization phase. Then it uses a neighborhood search approach to find good feasible combinations of these paths. A linear program is developed to evaluate the quality of each combination that is encountered. Numerical examples are provided.

Heuristics Miner for E-Commerce Visitor Access Pattern Representation

Directory of Open Access Journals (Sweden)

Kartina Diah Kesuma Wardhani

2017-06-01

Full Text Available E-commerce click stream data can form a certain pattern that describe visitor behavior while surfing the e-commerce website. This pattern can be used to initiate a design to determine alternative access sequence on the website. This research use heuristic miner algorithm to determine the pattern. σ-Algorithm and Genetic Mining are methods used for pattern recognition with frequent sequence item set approach. Heuristic Miner is an evolved form of those methods. σ-Algorithm assume that an activity in a website, that has been recorded in the data log, is a complete sequence from start to finish, without any tolerance to incomplete data or data with noise. On the other hand, Genetic Mining is a method that tolerate incomplete data or data with noise, so it can generate a more detailed e-commerce visitor access pattern. In this study, the same sequence of events obtained from six-generated patterns. The resulting pattern of visitor access is that visitors are often access the home page and then the product category page or the home page and then the full text search page.

Neighborhood socioeconomic deprivation, perceived neighborhood factors, and cortisol responses to induced stress among healthy adults.

Science.gov (United States)

Barrington, Wendy E; Stafford, Mai; Hamer, Mark; Beresford, Shirley A A; Koepsell, Thomas; Steptoe, Andrew

2014-05-01

Associations between measures of neighborhood socioeconomic deprivation and health have been identified, yet work is needed to uncover explanatory mechanisms. One hypothesized pathway is through stress, yet the few studies that have evaluated associations between characteristics of deprived neighborhoods and biomarkers of stress are mixed. This study evaluated whether objectively measured neighborhood socioeconomic deprivation and individual perceived neighborhood characteristics (i.e. social control and fear of crime) impacted cortisol responses to an induced stressor among older healthy adults. Data from Heart Scan, a sub-study of the Whitehall II cohort, were used to generate multilevel piecewise growth-curve models of cortisol trajectories after a laboratory stressor accounting for neighborhood and demographic characteristics. Neighborhood socioeconomic deprivation was significantly associated with individual perceptions of social control and fear of crime in the neighborhood while an association with blunted cortisol reactivity was only evidence among women. Social control was significantly associated with greater cortisol reactivity and mediation between neighborhood socioeconomic deprivation and cortisol reactivity was suggested among women. These findings support a gender-dependent role of neighborhood in stress process models of health. Published by Elsevier Ltd.

Fuel lattice design using heuristics and new strategies

Energy Technology Data Exchange (ETDEWEB)

Ortiz S, J. J.; Castillo M, J. A.; Torres V, M.; Perusquia del Cueto, R. [ININ, Carretera Mexico-Toluca s/n, Ocoyoacac 52750, Estado de Mexico (Mexico); Pelta, D. A. [ETS Ingenieria Informatica y Telecomunicaciones, Universidad de Granada, Daniel Saucedo Aranda s/n, 18071 Granada (Spain); Campos S, Y., E-mail: juanjose.ortiz@inin.gob.m [IPN, Escuela Superior de Fisica y Matematicas, Unidad Profesional Adolfo Lopez Mateos, Edif. 9, 07738 Mexico D. F. (Mexico)

2010-10-15

This work show some results of the fuel lattice design in BWRs when some allocation pin rod rules are not taking into account. Heuristics techniques like Path Re linking and Greedy to design fuel lattices were used. The scope of this work is to search about how do classical rules in design fuel lattices affect the heuristics techniques results and the fuel lattice quality. The fuel lattices quality is measured by Power Peaking Factor and Infinite Multiplication Factor at the beginning of the fuel lattice life. CASMO-4 code to calculate these parameters was used. The analyzed rules are the following: pin rods with lowest uranium enrichment are only allocated in the fuel lattice corner, and pin rods with gadolinium cannot allocated in the fuel lattice edge. Fuel lattices with and without gadolinium in the main diagonal were studied. Some fuel lattices were simulated in an equilibrium cycle fuel reload, using Simulate-3 to verify their performance. So, the effective multiplication factor and thermal limits can be verified. The obtained results show a good performance in some fuel lattices designed, even thought, the knowing rules were not implemented. A fuel lattice performance and fuel lattice design characteristics analysis was made. To the realized tests, a dell workstation was used, under Li nux platform. (Author)

Fuel lattice design using heuristics and new strategies

International Nuclear Information System (INIS)

Ortiz S, J. J.; Castillo M, J. A.; Torres V, M.; Perusquia del Cueto, R.; Pelta, D. A.; Campos S, Y.

2010-10-01

This work show some results of the fuel lattice design in BWRs when some allocation pin rod rules are not taking into account. Heuristics techniques like Path Re linking and Greedy to design fuel lattices were used. The scope of this work is to search about how do classical rules in design fuel lattices affect the heuristics techniques results and the fuel lattice quality. The fuel lattices quality is measured by Power Peaking Factor and Infinite Multiplication Factor at the beginning of the fuel lattice life. CASMO-4 code to calculate these parameters was used. The analyzed rules are the following: pin rods with lowest uranium enrichment are only allocated in the fuel lattice corner, and pin rods with gadolinium cannot allocated in the fuel lattice edge. Fuel lattices with and without gadolinium in the main diagonal were studied. Some fuel lattices were simulated in an equilibrium cycle fuel reload, using Simulate-3 to verify their performance. So, the effective multiplication factor and thermal limits can be verified. The obtained results show a good performance in some fuel lattices designed, even thought, the knowing rules were not implemented. A fuel lattice performance and fuel lattice design characteristics analysis was made. To the realized tests, a dell workstation was used, under Li nux platform. (Author)

A systematic review of relations between neighborhoods and mental health.

Science.gov (United States)

Truong, Khoa D; Ma, Sai

2006-09-01

The relationship between neighborhood characteristics and resident mental health has been widely investigated in individual studies in recent years, but this literature is not adequately reviewed. To systematically review relevant individual research of the relation between neighborhoods and adult mental health by identifying and synthesizing all relevant studies in this literature. We conducted an electronic search with PubMed and PsycINFO, and manual reference-checking, resulting in 8,562 screened studies of which 29 were selected. Studies were included in the main synthesis if they (i) were published in English in peer reviewed journals; (ii) had relevant definitions and measures of neighborhood characteristics; (iii) utilized standardized measures of adult mental health; (iv) controlled for individual characteristics; (v) reported quantitative results; and, (vi) studied a population in a developed country. We focused on two key areas within this literature: the methodologies utilized to study neighborhood effects and quantitative results. With regard to the former, we examined five major issues: (i) definitions and measures of neighborhoods; (ii) definitions and measures of mental health; (iii) controls for individual level characteristics; (iv) conceptual models; and (v) analytical models. As for quantitative results, the relation was reviewed by types of neighborhood characteristics. We summarized general quantitative findings and drew common conclusions across groups of studies. 27/29 studies found statistically significant association between mental health and at least one measure of neighborhood characteristics, after adjusting for individual factors. This association was evident for all types of neighborhood features, varying from sociodemographic characteristics to physical environment, and from objective to subjective measures. Neighborhood effects were weakened when adding individual-level characteristics into the regression models, and were generally

Adaptive selection of heuristics for improving exam timetables

OpenAIRE

Burke, Edmund; Qu, Rong; Soghier, Amr

2014-01-01

This paper presents a hyper-heuristic approach which hybridises low-level heuristic moves to improve timetables. Exams which cause a soft-constraint violation in the timetable are ordered and rescheduled to produce a better timetable. It is observed that both the order in which exams are rescheduled and the heuristic moves used to reschedule the exams and improve the timetable affect the quality of the solution produced. After testing different combinations in a hybrid hyper-heuristic approac...

Comparison of Heuristics for Inhibitory Rule Optimization

KAUST Repository

Alsolami, Fawaz

2014-09-13

Knowledge representation and extraction are very important tasks in data mining. In this work, we proposed a variety of rule-based greedy algorithms that able to obtain knowledge contained in a given dataset as a series of inhibitory rules containing an expression “attribute ≠ value” on the right-hand side. The main goal of this paper is to determine based on rule characteristics, rule length and coverage, whether the proposed rule heuristics are statistically significantly different or not; if so, we aim to identify the best performing rule heuristics for minimization of rule length and maximization of rule coverage. Friedman test with Nemenyi post-hoc are used to compare the greedy algorithms statistically against each other for length and coverage. The experiments are carried out on real datasets from UCI Machine Learning Repository. For leading heuristics, the constructed rules are compared with optimal ones obtained based on dynamic programming approach. The results seem to be promising for the best heuristics: the average relative difference between length (coverage) of constructed and optimal rules is at most 2.27% (7%, respectively). Furthermore, the quality of classifiers based on sets of inhibitory rules constructed by the considered heuristics are compared against each other, and the results show that the three best heuristics from the point of view classification accuracy coincides with the three well-performed heuristics from the point of view of rule length minimization.

Identifying product development crises: The potential of adaptive heuristics

DEFF Research Database (Denmark)

Münzberger, C.; Stingl, Verena; Oehmen, Josef

2017-01-01

This paper introduces adaptive heuristics as a tool to identify crises in design projects and highlights potential applications of these heuristics as decision support tool for crisis identification. Crises may emerge slowly or suddenly, and often have ambiguous signals. Thus the identification...... for the application of heuristics in design sciences. To achieve this, the paper compares crises to 'business as usual', and presents sixteen indicators for emerging crises. These indicators are potential cues for adaptive heuristics. Specifically three adaptive heuristics, One-single-cue, Fast-and-Frugal-Trees...

A Variable-Selection Heuristic for K-Means Clustering.

Science.gov (United States)

Brusco, Michael J.; Cradit, J. Dennis

2001-01-01

Presents a variable selection heuristic for nonhierarchical (K-means) cluster analysis based on the adjusted Rand index for measuring cluster recovery. Subjected the heuristic to Monte Carlo testing across more than 2,200 datasets. Results indicate that the heuristic is extremely effective at eliminating masking variables. (SLD)

Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning

Science.gov (United States)

Payne, Velma L.; Crowley, Rebecca S.

2008-01-01

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors. PMID:18999140

Connecting Schools to Neighborhood Revitalization: The Case of the Maple Heights Neighborhood Association

Science.gov (United States)

Pesch, Lawrence P.

2014-01-01

This case study focuses on the way a neighborhood association connects schools to broad change in an urban neighborhood of a large Midwestern city. The first section provides a review of the literature on community involvement in school and neighborhood reform. It reviews the historical origins of the current school-community relationship, the…

New insights into diversification of hyper-heuristics.

Science.gov (United States)

Ren, Zhilei; Jiang, He; Xuan, Jifeng; Hu, Yan; Luo, Zhongxuan

2014-10-01

There has been a growing research trend of applying hyper-heuristics for problem solving, due to their ability of balancing the intensification and the diversification with low level heuristics. Traditionally, the diversification mechanism is mostly realized by perturbing the incumbent solutions to escape from local optima. In this paper, we report our attempt toward providing a new diversification mechanism, which is based on the concept of instance perturbation. In contrast to existing approaches, the proposed mechanism achieves the diversification by perturbing the instance under solving, rather than the solutions. To tackle the challenge of incorporating instance perturbation into hyper-heuristics, we also design a new hyper-heuristic framework HIP-HOP (recursive acronym of HIP-HOP is an instance perturbation-based hyper-heuristic optimization procedure), which employs a grammar guided high level strategy to manipulate the low level heuristics. With the expressive power of the grammar, the constraints, such as the feasibility of the output solution could be easily satisfied. Numerical results and statistical tests over both the Ising spin glass problem and the p -median problem instances show that HIP-HOP is able to achieve promising performances. Furthermore, runtime distribution analysis reveals that, although being relatively slow at the beginning, HIP-HOP is able to achieve competitive solutions once given sufficient time.

Heuristics for no-wait flow shop scheduling problem

Directory of Open Access Journals (Sweden)

Kewal Krishan Nailwal

2016-09-01

Full Text Available No-wait flow shop scheduling refers to continuous flow of jobs through different machines. The job once started should have the continuous processing through the machines without wait. This situation occurs when there is a lack of an intermediate storage between the processing of jobs on two consecutive machines. The problem of no-wait with the objective of minimizing makespan in flow shop scheduling is NP-hard; therefore the heuristic algorithms are the key to solve the problem with optimal solution or to approach nearer to optimal solution in simple manner. The paper describes two heuristics, one constructive and an improvement heuristic algorithm obtained by modifying the constructive one for sequencing n-jobs through m-machines in a flow shop under no-wait constraint with the objective of minimizing makespan. The efficiency of the proposed heuristic algorithms is tested on 120 Taillard’s benchmark problems found in the literature against the NEH under no-wait and the MNEH heuristic for no-wait flow shop problem. The improvement heuristic outperforms all heuristics on the Taillard’s instances by improving the results of NEH by 27.85%, MNEH by 22.56% and that of the proposed constructive heuristic algorithm by 24.68%. To explain the computational process of the proposed algorithm, numerical illustrations are also given in the paper. Statistical tests of significance are done in order to draw the conclusions.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics.

Science.gov (United States)

Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-08-01

RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of [Formula: see text]. Subsequently, numerous faster 'Sankoff-style' approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity ([Formula: see text] quartic time). Breaking this barrier, we introduce the novel Sankoff-style algorithm 'sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)', which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff's original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. © The Author 2015. Published by Oxford University Press.

Intelligent process mapping through systematic improvement of heuristics

Science.gov (United States)

Ieumwananonthachai, Arthur; Aizawa, Akiko N.; Schwartz, Steven R.; Wah, Benjamin W.; Yan, Jerry C.

1992-01-01

The present system for automatic learning/evaluation of novel heuristic methods applicable to the mapping of communication-process sets on a computer network has its basis in the testing of a population of competing heuristic methods within a fixed time-constraint. The TEACHER 4.1 prototype learning system implemented or learning new postgame analysis heuristic methods iteratively generates and refines the mappings of a set of communicating processes on a computer network. A systematic exploration of the space of possible heuristic methods is shown to promise significant improvement.

Heuristics, biases and traps in managerial decision making

Directory of Open Access Journals (Sweden)

Peter Gál

2013-01-01

Full Text Available The aim of the paper is to demonstrate the impact of heuristics, biases and psychological traps on the decision making. Heuristics are unconscious routines people use to cope with the complexity inherent in most decision situations. They serve as mental shortcuts that help people to simplify and structure the information encountered in the world. These heuristics could be quite useful in some situations, while in others they can lead to severe and systematic errors, based on significant deviations from the fundamental principles of statistics, probability and sound judgment. This paper focuses on illustrating the existence of the anchoring, availability, and representativeness heuristics, originally described by Tversky & Kahneman in the early 1970’s. The anchoring heuristic is a tendency to focus on the initial information, estimate or perception (even random or irrelevant number as a starting point. People tend to give disproportionate weight to the initial information they receive. The availability heuristic explains why highly imaginable or vivid information have a disproportionate effect on people’s decisions. The representativeness heuristic causes that people rely on highly specific scenarios, ignore base rates, draw conclusions based on small samples and neglect scope. Mentioned phenomena are illustrated and supported by evidence based on the statistical analysis of the results of a questionnaire.

Automated generation of constructive ordering heuristics for educational timetabling

OpenAIRE

Pillay, Nelishia; Özcan, Ender

2017-01-01

Construction heuristics play an important role in solving combinatorial optimization problems. These heuristics are usually used to create an initial solution to the problem which is improved using optimization techniques such as metaheuristics. For examination timetabling and university course timetabling problems essentially graph colouring heuristics have been used for this purpose. The process of deriving heuristics manually for educational timetabling is a time consuming task. Furthermor...

Effective Heuristics for New Venture Formation

NARCIS (Netherlands)

Kraaijenbrink, Jeroen

2010-01-01

Entrepreneurs are often under time pressure and may only have a short window of opportunity to launch their new venture. This means they often have no time for rational analytical decisions and rather rely on heuristics. Past research on entrepreneurial heuristics has primarily focused on predictive

Measuring physical neighborhood quality related to health.

Science.gov (United States)

Rollings, Kimberly A; Wells, Nancy M; Evans, Gary W

2015-04-29

Although sociodemographic factors are one aspect of understanding the effects of neighborhood environments on health, equating neighborhood quality with socioeconomic status ignores the important role of physical neighborhood attributes. Prior work on neighborhood environments and health has relied primarily on level of socioeconomic disadvantage as the indicator of neighborhood quality without attention to physical neighborhood quality. A small but increasing number of studies have assessed neighborhood physical characteristics. Findings generally indicate that there is an association between living in deprived neighborhoods and poor health outcomes, but rigorous evidence linking specific physical neighborhood attributes to particular health outcomes is lacking. This paper discusses the methodological challenges and limitations of measuring physical neighborhood environments relevant to health and concludes with proposed directions for future work.

Heuristic hybrid game approach for fleet condition-based maintenance planning

International Nuclear Information System (INIS)

Feng, Qiang; Bi, Xiong; Zhao, Xiujie; Chen, Yiran; Sun, Bo

2017-01-01

The condition-based maintenance (CBM) method is commonly used to select appropriate maintenance opportunities according to equipment status over a period of time. The CBM of aircraft fleets is a fleet maintenance planning problem. In this problem, mission requirements, resource constraints, and aircraft statuses are considered to find an optimal strategy set. Given that the maintenance strategies for each aircraft are finite, fleet CBM can be treated as a combinatorial optimization problem. In this study, the process of making a decision on the CBM of military fleets is analyzed. The fleet CBM problem is treated as a two-stage dynamic decision-making problem. Aircraft are divided into dispatch and standby sets; thus, the problem scale is significantly reduced. A heuristic hybrid game (HHG) approach comprising a competition game and a cooperative game is proposed on the basis of heuristic rule. In the dispatch set, a competition game approach is proposed to search for a local optimal strategy matrix. A cooperative game method for the two sets is also proposed to ensure global optimization. Finally, a case study regarding a fleet comprising 20 aircraft is conducted, with the results proving that the approach efficiently generates outcomes that meet the mission risk-oriented schedule requirement. - Highlights: • A new heuristic hybrid game method for fleet condition-based maintenance is proposed. • The problem is simplified by hierarchical solving based on dispatch and standby set. • The local optimal solution is got by competition game algorithm for dispatch set. • The global optimal solution is got by cooperative game algorithm between two sets.

Need for closure and heuristic information processing: the moderating role of the ability to achieve the need for closure.

Science.gov (United States)

Kossowska, Małgorzata; Bar-Tal, Yoram

2013-11-01

In contrast to the ample research that shows a positive relationship between the need for closure (NFC) and heuristic information processing, this research examines the hypothesis that this relationship is moderated by the ability to achieve closure (AAC), that is, the ability to use information-processing strategies consistent with the level of NFC. Three different operationalizations of heuristic information processing were used: recall of information consistent with the impression (Study 1); pre-decisional information search (Study 2); and stereotypic impression formation (Study 3). The results of the studies showed that there were positive relationships between NFC and heuristic information processing when participants assessed themselves as being able to use cognitive strategies consistent with their level of NFC (high AAC). For individuals with low AAC, the relationships were negative. Our data show that motivation-cognition interactions influence the information-processing style. © 2012 The British Psychological Society.

Assessing Use of Cognitive Heuristic Representativeness in Clinical Reasoning

OpenAIRE

Payne, Velma L.; Crowley, Rebecca S.

2008-01-01

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as ca...

Heuristic reasoning and relative incompleteness

OpenAIRE

Treur, J.

1993-01-01

In this paper an approach is presented in which heuristic reasoning is interpreted as strategic reasoning. This type of reasoning enables one to derive which hypothesis to investigate, and which observable information to acquire next (to be able to verify the chosen hypothesis). A compositional architecture for reasoning systems that perform such heuristic reasoning is introduced, called SIX (for Strategic Interactive eXpert systems). This compositional architecture enables user interaction a...

Heuristic Portfolio Trading Rules with Capital Gain Taxes

DEFF Research Database (Denmark)

Fischer, Marcel; Gallmeyer, Michael

in some cases. Overlaying simple tax trading heuristics on these trading strategies improves out-of-sample performance. In particular, the 1/N trading strategy's welfare gains improve when a variety of tax trading heuristics are also imposed. For medium to large transaction costs, no trading strategy can...... outperform a 1/N trading strategy augmented with a tax heuristic, not even the most tax- and transaction-cost efficient buy-and-hold strategy. Overall, the best strategy is 1/N augmented with a heuristic that allows for a fixed deviation in absolute portfolio weights. Our results show that the best trading...

Searching remote homology with spectral clustering with symmetry in neighborhood cluster kernels.

Directory of Open Access Journals (Sweden)

Ujjwal Maulik

Full Text Available Remote homology detection among proteins utilizing only the unlabelled sequences is a central problem in comparative genomics. The existing cluster kernel methods based on neighborhoods and profiles and the Markov clustering algorithms are currently the most popular methods for protein family recognition. The deviation from random walks with inflation or dependency on hard threshold in similarity measure in those methods requires an enhancement for homology detection among multi-domain proteins. We propose to combine spectral clustering with neighborhood kernels in Markov similarity for enhancing sensitivity in detecting homology independent of "recent" paralogs. The spectral clustering approach with new combined local alignment kernels more effectively exploits the unsupervised protein sequences globally reducing inter-cluster walks. When combined with the corrections based on modified symmetry based proximity norm deemphasizing outliers, the technique proposed in this article outperforms other state-of-the-art cluster kernels among all twelve implemented kernels. The comparison with the state-of-the-art string and mismatch kernels also show the superior performance scores provided by the proposed kernels. Similar performance improvement also is found over an existing large dataset. Therefore the proposed spectral clustering framework over combined local alignment kernels with modified symmetry based correction achieves superior performance for unsupervised remote homolog detection even in multi-domain and promiscuous domain proteins from Genolevures database families with better biological relevance. Source code available upon request.sarkar@labri.fr.

Religion, Heuristics, and Intergenerational Risk Management

OpenAIRE

Rupert Read; Nassim Nicholas Taleb

2014-01-01

Religions come with risk-​managing interdicts and heuristics, and they carry such interdicts and heuristics across generations. We remark on such facets of religion in relation to a propensity among some decision scientists and others to regard practices that they cannot understand as being irrational, biased, and so on.

Neighborhood spaces

OpenAIRE

D. C. Kent; Won Keun Min

2002-01-01

Neighborhood spaces, pretopological spaces, and closure spaces are topological space generalizations which can be characterized by means of their associated interior (or closure) operators. The category NBD of neighborhood spaces and continuous maps contains PRTOP as a bicoreflective subcategory and CLS as a bireflective subcategory, whereas TOP is bireflectively embedded in PRTOP and bicoreflectively embedded in CLS. Initial and final structures are described in these categories, and it is s...

A solution to energy and environmental problems of electric power system using hybrid harmony search-random search optimization algorithm

Directory of Open Access Journals (Sweden)

Vikram Kumar Kamboj

2016-04-01

Full Text Available In recent years, global warming and carbon dioxide (CO2 emission reduction have become important issues in India, as CO2 emission levels are continuing to rise in accordance with the increased volume of Indian national energy consumption under the pressure of global warming, it is crucial for Indian government to impose the effective policy to promote CO2 emission reduction. Challenge of supplying the nation with high quality and reliable electrical energy at a reasonable cost, converted government policy into deregulation and restructuring environment. This research paper presents aims to presents an effective solution for energy and environmental problems of electric power using an efficient and powerful hybrid optimization algorithm: Hybrid Harmony search-random search algorithm. The proposed algorithm is tested for standard IEEE-14 bus, -30 bus and -56 bus system. The effectiveness of proposed hybrid algorithm is compared with others well known evolutionary, heuristics and meta-heuristics search algorithms. For multi-objective unit commitment, it is found that as there are conflicting relationship between cost and emission, if the performance in cost criterion is improved, performance in the emission is seen to deteriorate.

"The Gaze Heuristic:" Biography of an Adaptively Rational Decision Process.

Science.gov (United States)

Hamlin, Robert P

2017-04-01

This article is a case study that describes the natural and human history of the gaze heuristic. The gaze heuristic is an interception heuristic that utilizes a single input (deviation from a constant angle of approach) repeatedly as a task is performed. Its architecture, advantages, and limitations are described in detail. A history of the gaze heuristic is then presented. In natural history, the gaze heuristic is the only known technique used by predators to intercept prey. In human history the gaze heuristic was discovered accidentally by Royal Air Force (RAF) fighter command just prior to World War II. As it was never discovered by the Luftwaffe, the technique conferred a decisive advantage upon the RAF throughout the war. After the end of the war in America, German technology was combined with the British heuristic to create the Sidewinder AIM9 missile, the most successful autonomous weapon ever built. There are no plans to withdraw it or replace its guiding gaze heuristic. The case study demonstrates that the gaze heuristic is a specific heuristic type that takes a single best input at the best time (take the best 2 ). Its use is an adaptively rational response to specific, rapidly evolving decision environments that has allowed those animals/humans/machines who use it to survive, prosper, and multiply relative to those who do not. Copyright © 2017 Cognitive Science Society, Inc.

How Neighborhood Disadvantage Reduces Birth Weight

Directory of Open Access Journals (Sweden)

Emily Moiduddin

2008-06-01

Full Text Available In this analysis we connect structural neighborhood conditions to birth outcomes through their intermediate effects on mothers’ perceptions of neighborhood danger and their tendency to abuse substances during pregnancy. We hypothesize that neighborhood poverty and racial/ethnic concentration combine to produce environments that mothers perceive as unsafe, thereby increasing the likelihood of negative coping behaviors (substance abuse. We expect these behaviors, in turn, to produce lower birth weights. Using data from the Fragile Families and Child Wellbeing Study, a survey of a cohort of children born between 1998 and 2000 and their mothers in large cities in the United States, we find little evidence to suggest that neighborhood circumstances have strong, direct effects on birth weight. Living in a neighborhood with more foreigners had a positive effect on birth weight. To the extent that neighborhood conditions influence birth weight, the effect mainly occurs through an association with perceived neighborhood danger and subsequent negative coping behaviors. Poverty and racial/ethnic concentration increase a mother’s sense that her neighborhood is unsafe. The perception of an unsafe neighborhood, in turn, associates with a greater likelihood of smoking cigarettes and using illegal drugs, and these behaviors have strong and significant effects in reducing birth weight. However, demographic characteristics, rather than perceived danger or substance abuse, mediate the influence of neighborhood characteristics on birth weight.

Community, Democracy, and Neighborhood News.

Science.gov (United States)

Hindman, Elizabeth Blanks

1998-01-01

Contributes to scholarship on democracy, community, and journalism by examining the interplay between communication, democracy, and community at an inner-city neighborhood newspaper. Concludes that, through its focus on neighborhood culture, acknowledgment of conflict, and attempts to provide a forum for the neighborhood's self-definition, the…

Fast Optimal Replica Placement with Exhaustive Search Using Dynamically Reconfigurable Processor

Directory of Open Access Journals (Sweden)

Hidetoshi Takeshita

2011-01-01

Full Text Available This paper proposes a new replica placement algorithm that expands the exhaustive search limit with reasonable calculation time. It combines a new type of parallel data-flow processor with an architecture tuned for fast calculation. The replica placement problem is to find a replica-server set satisfying service constraints in a content delivery network (CDN. It is derived from the set cover problem which is known to be NP-hard. It is impractical to use exhaustive search to obtain optimal replica placement in large-scale networks, because calculation time increases with the number of combinations. To reduce calculation time, heuristic algorithms have been proposed, but it is known that no heuristic algorithm is assured of finding the optimal solution. The proposed algorithm suits parallel processing and pipeline execution and is implemented on DAPDNA-2, a dynamically reconfigurable processor. Experiments show that the proposed algorithm expands the exhaustive search limit by the factor of 18.8 compared to the conventional algorithm search limit running on a Neumann-type processor.

Quantifying Heuristic Bias: Anchoring, Availability, and Representativeness.

Science.gov (United States)

Richie, Megan; Josephson, S Andrew

2018-01-01

Construct: Authors examined whether a new vignette-based instrument could isolate and quantify heuristic bias. Heuristics are cognitive shortcuts that may introduce bias and contribute to error. There is no standardized instrument available to quantify heuristic bias in clinical decision making, limiting future study of educational interventions designed to improve calibration of medical decisions. This study presents validity data to support a vignette-based instrument quantifying bias due to the anchoring, availability, and representativeness heuristics. Participants completed questionnaires requiring assignment of probabilities to potential outcomes of medical and nonmedical scenarios. The instrument randomly presented scenarios in one of two versions: Version A, encouraging heuristic bias, and Version B, worded neutrally. The primary outcome was the difference in probability judgments for Version A versus Version B scenario options. Of 167 participants recruited, 139 enrolled. Participants assigned significantly higher mean probability values to Version A scenario options (M = 9.56, SD = 3.75) than Version B (M = 8.98, SD = 3.76), t(1801) = 3.27, p = .001. This result remained significant analyzing medical scenarios alone (Version A, M = 9.41, SD = 3.92; Version B, M = 8.86, SD = 4.09), t(1204) = 2.36, p = .02. Analyzing medical scenarios by heuristic revealed a significant difference between Version A and B for availability (Version A, M = 6.52, SD = 3.32; Version B, M = 5.52, SD = 3.05), t(404) = 3.04, p = .003, and representativeness (Version A, M = 11.45, SD = 3.12; Version B, M = 10.67, SD = 3.71), t(396) = 2.28, p = .02, but not anchoring. Stratifying by training level, students maintained a significant difference between Version A and B medical scenarios (Version A, M = 9.83, SD = 3.75; Version B, M = 9.00, SD = 3.98), t(465) = 2.29, p = .02, but not residents or attendings. Stratifying by heuristic and training level, availability maintained

A Novel Spatial-Temporal Voronoi Diagram-Based Heuristic Approach for Large-Scale Vehicle Routing Optimization with Time Constraints

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Wei Tu

2015-10-01

Full Text Available Vehicle routing optimization (VRO designs the best routes to reduce travel cost, energy consumption, and carbon emission. Due to non-deterministic polynomial-time hard (NP-hard complexity, many VROs involved in real-world applications require too much computing effort. Shortening computing time for VRO is a great challenge for state-of-the-art spatial optimization algorithms. From a spatial-temporal perspective, this paper presents a spatial-temporal Voronoi diagram-based heuristic approach for large-scale vehicle routing problems with time windows (VRPTW. Considering time constraints, a spatial-temporal Voronoi distance is derived from the spatial-temporal Voronoi diagram to find near neighbors in the space-time searching context. A Voronoi distance decay strategy that integrates a time warp operation is proposed to accelerate local search procedures. A spatial-temporal feature-guided search is developed to improve unpromising micro route structures. Experiments on VRPTW benchmarks and real-world instances are conducted to verify performance. The results demonstrate that the proposed approach is competitive with state-of-the-art heuristics and achieves high-quality solutions for large-scale instances of VRPTWs in a short time. This novel approach will contribute to spatial decision support community by developing an effective vehicle routing optimization method for large transportation applications in both public and private sectors.

Assessing the use of cognitive heuristic representativeness in clinical reasoning.

Science.gov (United States)

Payne, Velma L; Crowley, Rebecca S; Crowley, Rebecca

2008-11-06

We performed a pilot study to investigate use of the cognitive heuristic Representativeness in clinical reasoning. We tested a set of tasks and assessments to determine whether subjects used the heuristics in reasoning, to obtain initial frequencies of heuristic use and related cognitive errors, and to collect cognitive process data using think-aloud techniques. The study investigates two aspects of the Representativeness heuristic - judging by perceived frequency and representativeness as causal beliefs. Results show that subjects apply both aspects of the heuristic during reasoning, and make errors related to misapplication of these heuristics. Subjects in this study rarely used base rates, showed significant variability in their recall of base rates, demonstrated limited ability to use provided base rates, and favored causal data in diagnosis. We conclude that the tasks and assessments we have developed provide a suitable test-bed to study the cognitive processes underlying heuristic errors.

SPARSE: quadratic time simultaneous alignment and folding of RNAs without sequence-based heuristics

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Will, Sebastian; Otto, Christina; Miladi, Milad; Möhl, Mathias; Backofen, Rolf

2015-01-01

Motivation: RNA-Seq experiments have revealed a multitude of novel ncRNAs. The gold standard for their analysis based on simultaneous alignment and folding suffers from extreme time complexity of O(n6). Subsequently, numerous faster ‘Sankoff-style’ approaches have been suggested. Commonly, the performance of such methods relies on sequence-based heuristics that restrict the search space to optimal or near-optimal sequence alignments; however, the accuracy of sequence-based methods breaks down for RNAs with sequence identities below 60%. Alignment approaches like LocARNA that do not require sequence-based heuristics, have been limited to high complexity (≥ quartic time). Results: Breaking this barrier, we introduce the novel Sankoff-style algorithm ‘sparsified prediction and alignment of RNAs based on their structure ensembles (SPARSE)’, which runs in quadratic time without sequence-based heuristics. To achieve this low complexity, on par with sequence alignment algorithms, SPARSE features strong sparsification based on structural properties of the RNA ensembles. Following PMcomp, SPARSE gains further speed-up from lightweight energy computation. Although all existing lightweight Sankoff-style methods restrict Sankoff’s original model by disallowing loop deletions and insertions, SPARSE transfers the Sankoff algorithm to the lightweight energy model completely for the first time. Compared with LocARNA, SPARSE achieves similar alignment and better folding quality in significantly less time (speedup: 3.7). At similar run-time, it aligns low sequence identity instances substantially more accurate than RAF, which uses sequence-based heuristics. Availability and implementation: SPARSE is freely available at http://www.bioinf.uni-freiburg.de/Software/SPARSE. Contact: backofen@informatik.uni-freiburg.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25838465

Multi-objective flexible job shop scheduling problem using variable neighborhood evolutionary algorithm

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Wang, Chun; Ji, Zhicheng; Wang, Yan

2017-07-01

In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) was studied with the objects to minimize makespan, total workload and critical workload. A variable neighborhood evolutionary algorithm (VNEA) was proposed to obtain a set of Pareto optimal solutions. First, two novel crowded operators in terms of the decision space and object space were proposed, and they were respectively used in mating selection and environmental selection. Then, two well-designed neighborhood structures were used in local search, which consider the problem characteristics and can hold fast convergence. Finally, extensive comparison was carried out with the state-of-the-art methods specially presented for solving MOFJSP on well-known benchmark instances. The results show that the proposed VNEA is more effective than other algorithms in solving MOFJSP.

Heuristic algorithms for joint optimization of unicast and anycast traffic in elastic optical network–based large–scale computing systems

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Markowski Marcin

2017-09-01

Full Text Available In recent years elastic optical networks have been perceived as a prospective choice for future optical networks due to better adjustment and utilization of optical resources than is the case with traditional wavelength division multiplexing networks. In the paper we investigate the elastic architecture as the communication network for distributed data centers. We address the problems of optimization of routing and spectrum assignment for large-scale computing systems based on an elastic optical architecture; particularly, we concentrate on anycast user to data center traffic optimization. We assume that computational resources of data centers are limited. For this offline problems we formulate the integer linear programming model and propose a few heuristics, including a meta-heuristic algorithm based on a tabu search method. We report computational results, presenting the quality of approximate solutions and efficiency of the proposed heuristics, and we also analyze and compare some data center allocation scenarios.

Perceived School and Neighborhood Safety, Neighborhood Violence and Academic Achievement in Urban School Children

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AJ, Milam; CDM, Furr-Holden; PJ, Leaf

2010-01-01

Community and school violence continue to be a major public health problem, especially among urban children and adolescents. Little research has focused on the effect of school safety and neighborhood violence on academic performance. This study examines the effect of the school and neighborhood climate on academic achievement among a population of 3rd-5th grade students in an urban public school system. Community and school safety were assessed using the School Climate Survey, an annual city-wide assessment of student’s perception of school and community safety. Community violence was measured using the Neighborhood Inventory for Environmental Typology, an objective observational assessment of neighborhood characteristics. Academic achievement was measured using the Maryland State Assessment (MSA), a standardized exam given to all Maryland 3rd-8th graders. School Climate Data and MSA data were aggregated by school and grade. Objective assessments of neighborhood environment and students’ self-reported school and neighborhood safety were both strongly associated with academic performance. Increasing neighborhood violence was associated with statistically significant decreases from 4.2%-8.7% in math and reading achievement; increasing perceived safety was associated with significant increases in achievement from 16%-22%. These preliminary findings highlight the adverse impact of perceived safety and community violence exposure on primary school children’s academic performance. PMID:21197388

A Hybrid Model Ranking Search Result for Research Paper Searching on Social Bookmarking

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pijitra jomsri

2015-11-01

Full Text Available Social bookmarking and publication sharing systems are essential tools for web resource discovery. The performance and capabilities of search results from research paper bookmarking system are vital. Many researchers use social bookmarking for searching papers related to their topics of interest. This paper proposes a combination of similarity based indexing “tag title and abstract” and static ranking to improve search results. In this particular study, the year of the published paper and type of research paper publication are combined with similarity ranking called (HybridRank. Different weighting scores are employed. The retrieval performance of these weighted combination rankings are evaluated using mean values of NDCG. The results suggest that HybridRank and similarity rank with weight 75:25 has the highest NDCG scores. From the preliminary result of experiment, the combination ranking technique provide more relevant research paper search results. Furthermore the chosen heuristic ranking can improve the efficiency of research paper searching on social bookmarking websites.

Maximizing the nurses' preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm

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Jafari, Hamed; Salmasi, Nasser

2015-09-01

The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital's demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses' preferences for working shifts and weekends off by considering several important factors such as hospital's policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49 % compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.

A Hybrid Symbiotic Organisms Search Algorithm with Variable Neighbourhood Search for Solving Symmetric and Asymmetric Traveling Salesman Problem

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Umam, M. I. H.; Santosa, B.

2018-04-01

Combinatorial optimization has been frequently used to solve both problems in science, engineering, and commercial applications. One combinatorial problems in the field of transportation is to find a shortest travel route that can be taken from the initial point of departure to point of destination, as well as minimizing travel costs and travel time. When the distance from one (initial) node to another (destination) node is the same with the distance to travel back from destination to initial, this problems known to the Traveling Salesman Problem (TSP), otherwise it call as an Asymmetric Traveling Salesman Problem (ATSP). The most recent optimization techniques is Symbiotic Organisms Search (SOS). This paper discuss how to hybrid the SOS algorithm with variable neighborhoods search (SOS-VNS) that can be applied to solve the ATSP problem. The proposed mechanism to add the variable neighborhoods search as a local search is to generate the better initial solution and then we modify the phase of parasites with adapting mechanism of mutation. After modification, the performance of the algorithm SOS-VNS is evaluated with several data sets and then the results is compared with the best known solution and some algorithm such PSO algorithm and SOS original algorithm. The SOS-VNS algorithm shows better results based on convergence, divergence and computing time.

A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

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Hart, Emma; Sim, Kevin

2016-01-01

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

An adaptive random search for short term generation scheduling with network constraints.

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J A Marmolejo

Full Text Available This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.

Neighborhood Quality and Labor Market Outcomes

DEFF Research Database (Denmark)

Damm, Anna Piil

of men living in the neighborhood, but positively affected by the employment rate of non-Western immigrant men and co-national men living in the neighborhood. This is strong evidence that immigrants find jobs in part through their employed immigrant and co-ethnic contacts in the neighborhood of residence...... successfully addresses the methodological problem of endogenous neighborhood selection. Taking account of location sorting, living in a socially deprived neighborhood does not affect labor market outcomes of refugee men. Furthermore, their labor market outcomes are not affected by the overall employment rate...

Neighborhood cohesion, neighborhood disorder, and cardiometabolic risk.

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Robinette, Jennifer W; Charles, Susan T; Gruenewald, Tara L

2018-02-01

Perceptions of neighborhood disorder (trash, vandalism) and cohesion (neighbors trust one another) are related to residents' health. Affective and behavioral factors have been identified, but often in studies using geographically select samples. We use a nationally representative sample (n = 9032) of United States older adults from the Health and Retirement Study to examine cardiometabolic risk in relation to perceptions of neighborhood cohesion and disorder. Lower cohesion is significantly related to greater cardiometabolic risk in 2006/2008 and predicts greater risk four years later (2010/2012). The longitudinal relation is partially accounted for by anxiety and physical activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Who Gentrifies Low-Income Neighborhoods?

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McKinnish, Terra; Walsh, Randall; White, T Kirk

2010-03-01

This paper uses confidential Census data, specifically the 1990 and 2000 Census Long Form data, to study demographic processes in neighborhoods that gentrified during the 1990's. In contrast to previous studies, the analysis is conducted at the more refined census-tract level, with a narrower definition of gentrification and more closely matched comparison neighborhoods. Furthermore, our access to individual-level data with census tract identifiers allows us to separately identify recent in-migrants and long-term residents. Our results indicate that, on average, the demographic flows associated with the gentrification of urban neighborhoods during the 1990's are not consistent with displacement and harm to minority households. In fact, taken as a whole, our results suggest that gentrification of predominantly black neighborhoods creates neighborhoods that are attractive to middle-class black households.

Neighborhood-Specific and General Social Support: Which Buffers the Effect of Neighborhood Disorder on Depression?

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Kim, Joongbaeck; Ross, Catherine E.

2009-01-01

Is neighborhood-specific social support the most effective type of social support for buffering the effect of neighborhood disorder on depression? Matching theory suggests that it is. The authors extend the research on neighborhood disorder and adult depression by showing that individuals who have higher levels of both general and…

A Longitudinal Analysis of the Influence of the Neighborhood Environment on Recreational Walking within the Neighborhood: Results from RESIDE.

Science.gov (United States)

Christian, Hayley; Knuiman, Matthew; Divitini, Mark; Foster, Sarah; Hooper, Paula; Boruff, Bryan; Bull, Fiona; Giles-Corti, Billie

2017-07-12

There is limited longitudinal evidence confirming the role of neighborhood environment attributes in encouraging people to walk more or if active people simply choose to live in activity-friendly neighborhoods. Natural experiments of policy changes to create more walkable communities provide stronger evidence for a causal effect of neighborhood environments on residents' walking. We aimed to investigate longitudinal associations between objective and perceived neighborhood environment measures and neighborhood recreational walking. We analyzed longitudinal data collected over 8 yr (four surveys) from the RESIDential Environments (RESIDE) Study (Perth, Australia, 2003-2012). At each time point, participants reported the frequency and total minutes of recreational walking/week within their neighborhood and neighborhood environment perceptions. Objective measures of the neighborhood environment were generated using a Geographic Information System (GIS). Local recreational walking was influenced by objectively measured access to a medium-/large-size park, beach access, and higher street connectivity, which was reduced when adjusted for neighborhood perceptions. In adjusted models, positive perceptions of access to a park and beach, higher street connectivity, neighborhood esthetics, and safety from crime were independent determinants of increased neighborhood recreational walking. Local recreational walking increased by 9 min/wk (12% increase in frequency) for each additional perceived neighborhood attribute present. Our findings provide urban planners and policy makers with stronger causal evidence of the positive impact of well-connected neighborhoods and access to local parks of varying sizes on local residents' recreational walking and health. https://doi.org/10.1289/EHP823.

Judgment under Uncertainty: Heuristics and Biases.

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Tversky, A; Kahneman, D

1974-09-27

This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.

The Search for Regularity: Four Aspects of Scientific Discovery.

Science.gov (United States)

1984-09-01

reactions, and ultimately led to the determination of relative atomic weights. To some extent. Dalton’s and Guy- Lussacs laws were motivated by an atomic...heuristic search empirical laws theory of acids and bases structural models theory of phlogiston qualitative laws atomic theory 20. ABSTRACT (Continue...systems that address different facets of this process. BACON.6 focuses on discovering empirical laws that summarize numerical data. This program searches a

Shrimp Feed Formulation via Evolutionary Algorithm with Power Heuristics for Handling Constraints

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Rosshairy Abd. Rahman

2017-01-01

Full Text Available Formulating feed for shrimps represents a challenge to farmers and industry partners. Most previous studies selected from only a small number of ingredients due to cost pressures, even though hundreds of potential ingredients could be used in the shrimp feed mix. Even with a limited number of ingredients, the best combination of the most appropriate ingredients is still difficult to obtain due to various constraint requirements, such as nutrition value and cost. This paper proposes a new operator which we call Power Heuristics, as part of an Evolutionary Algorithm (EA, which acts as a constraint handling technique for the shrimp feed or diet formulation. The operator is able to choose and discard certain ingredients by utilising a specialized search mechanism. The aim is to achieve the most appropriate combination of ingredients. Power Heuristics are embedded in the EA at the early stage of a semirandom initialization procedure. The resulting combination of ingredients, after fulfilling all the necessary constraints, shows that this operator is useful in discarding inappropriate ingredients when a crucial constraint is violated.

Urbanism, Neighborhood Context, and Social Networks.

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Cornwell, Erin York; Behler, Rachel L

2015-09-01

Theories of urbanism suggest that the urban context erodes individuals' strong social ties with friends and family. Recent research has narrowed focus to the neighborhood context, emphasizing how localized structural disadvantage affects community-level cohesion and social capital. In this paper, we argue that neighborhood context also shapes social ties with friends and family- particularly for community-dwelling seniors. We hypothesize that neighborhood disadvantage, residential instability, and disorder restrict residents' abilities to cultivate close relationships with neighbors and non-neighbor friends and family. Using data from the National Social Life, Health, and Aging Project (NSHAP), we find that older adults who live in disadvantaged neighborhoods have smaller social networks. Neighborhood disadvantage is also associated with less close network ties and less frequent interaction - but only among men. Furthermore, residents of disordered neighborhoods have smaller networks and weaker ties. We urge scholars to pay greater attention to how neighborhood context contributes to disparities in network-based access to resources.

Heuristics as Bayesian inference under extreme priors.

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Parpart, Paula; Jones, Matt; Love, Bradley C

2018-05-01

Simple heuristics are often regarded as tractable decision strategies because they ignore a great deal of information in the input data. One puzzle is why heuristics can outperform full-information models, such as linear regression, which make full use of the available information. These "less-is-more" effects, in which a relatively simpler model outperforms a more complex model, are prevalent throughout cognitive science, and are frequently argued to demonstrate an inherent advantage of simplifying computation or ignoring information. In contrast, we show at the computational level (where algorithmic restrictions are set aside) that it is never optimal to discard information. Through a formal Bayesian analysis, we prove that popular heuristics, such as tallying and take-the-best, are formally equivalent to Bayesian inference under the limit of infinitely strong priors. Varying the strength of the prior yields a continuum of Bayesian models with the heuristics at one end and ordinary regression at the other. Critically, intermediate models perform better across all our simulations, suggesting that down-weighting information with the appropriate prior is preferable to entirely ignoring it. Rather than because of their simplicity, our analyses suggest heuristics perform well because they implement strong priors that approximate the actual structure of the environment. We end by considering how new heuristics could be derived by infinitely strengthening the priors of other Bayesian models. These formal results have implications for work in psychology, machine learning and economics. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Paging Doctor Google! Heuristics vs. technology [v2; ref status: indexed, http://f1000r.es/113

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Kenar D Jhaveri

2013-04-01

Full Text Available The most dramatic development in medical decision-making technology has been the advent of the Internet. This has had an impact not only on clinicians, but has also become an important resource for patients who often approach their doctors with medical information they have obtained from the Internet.  Increasingly, medical students, residents and attending physicians have been using the Internet as a tool for diagnosing and treating disease. Internet-based resources that are available take various forms, including informational websites, online journals and textbooks, and social media.  Search engines such as Google have been increasingly used to help in making diagnoses of disease entities. Do these search methods fare better than experienced heuristic methods? In a small study, we examined the comparative role of heuristics versus the 'Google' mode of thinking. Internal medicine residents were asked to “google” key words to come up with a diagnosis. Their results were compared to experienced nephrology faculty and fellows in training using heuristics and no additional help of internet. Overall, with the aid of Google, the novices (internal medicine residents correctly diagnosed renal diseases less often than the experts (the attendings but with the same frequency as the intermediates (nephrology fellows.  However, in a subgroup analysis of both common diseases and rare diseases, the novices correctly diagnosed renal diseases less often than the experts but more often than the intermediates in each analysis.  The novices correctly diagnosed renal diseases with the same frequency as nephrology fellows in training.

The recognition heuristic: a review of theory and tests.

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Pachur, Thorsten; Todd, Peter M; Gigerenzer, Gerd; Schooler, Lael J; Goldstein, Daniel G

2011-01-01

The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect - the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference).

The Recognition Heuristic: A Review of Theory and Tests

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Thorsten ePachur

2011-07-01

Full Text Available The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a that recognition is often an ecologically valid cue; (b that people often follow recognition when making inferences; (c that recognition supersedes further cue knowledge; (d that its use can produce the less-is-more effect—the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference.

The Recognition Heuristic: A Review of Theory and Tests

Science.gov (United States)

Pachur, Thorsten; Todd, Peter M.; Gigerenzer, Gerd; Schooler, Lael J.; Goldstein, Daniel G.

2011-01-01

The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect – the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266

Heuristics to Evaluate Interactive Systems for Children with Autism Spectrum Disorder (ASD).

Science.gov (United States)

Khowaja, Kamran; Salim, Siti Salwah; Asemi, Adeleh

2015-01-01

In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD). We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nielsen set, the next 5 heuristics are improved versions of Nielsen's, whereas the last 5 heuristics are new. We present two evaluation studies of our new heuristics. In the first, two groups compared Nielsen's set with the modified set of heuristics, with each group evaluating two interactive systems. The Nielsen's heuristics were assigned to the control group while the experimental group was given the modified set of heuristics, and a statistical analysis was conducted to determine the effectiveness of the modified set, the contribution of 5 new heuristics and the impact of 5 improved heuristics. The results show that the modified set is significantly more effective than the original, and we found a significant difference between the five improved heuristics and their corresponding heuristics in the original set. The five new heuristics are effective in problem identification using the modified set. The second study was conducted using a system which was developed to ascertain if the modified set was effective at identifying usability problems that could be fixed before the release of software. The post-study analysis revealed that the majority of the usability problems identified by the experts were fixed in the updated version of the system.

Heuristics to Evaluate Interactive Systems for Children with Autism Spectrum Disorder (ASD.

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Kamran Khowaja

Full Text Available In this paper, we adapted and expanded a set of guidelines, also known as heuristics, to evaluate the usability of software to now be appropriate for software aimed at children with autism spectrum disorder (ASD. We started from the heuristics developed by Nielsen in 1990 and developed a modified set of 15 heuristics. The first 5 heuristics of this set are the same as those of the original Nielsen set, the next 5 heuristics are improved versions of Nielsen's, whereas the last 5 heuristics are new. We present two evaluation studies of our new heuristics. In the first, two groups compared Nielsen's set with the modified set of heuristics, with each group evaluating two interactive systems. The Nielsen's heuristics were assigned to the control group while the experimental group was given the modified set of heuristics, and a statistical analysis was conducted to determine the effectiveness of the modified set, the contribution of 5 new heuristics and the impact of 5 improved heuristics. The results show that the modified set is significantly more effective than the original, and we found a significant difference between the five improved heuristics and their corresponding heuristics in the original set. The five new heuristics are effective in problem identification using the modified set. The second study was conducted using a system which was developed to ascertain if the modified set was effective at identifying usability problems that could be fixed before the release of software. The post-study analysis revealed that the majority of the usability problems identified by the experts were fixed in the updated version of the system.

The neighborhoods they live in: the effects of neighborhood residence on child and adolescent outcomes.

Science.gov (United States)

Leventhal, T; Brooks-Gunn, J

2000-03-01

This article provides a comprehensive review of research on the effects of neighborhood residence on child and adolescent well-being. The first section reviews key methodological issues. The following section considers links between neighborhood characteristics and child outcomes and suggests the importance of high socioeconomic status (SES) for achievement and low SES and residential instability for behavioral/emotional outcomes. The third section identifies 3 pathways (institutional resources, relationships, and norms/collective efficacy) through which neighborhoods might influence development, and which represent an extension of models identified by C. Jencks and S. Mayer (1990) and R. J. Sampson (1992). The models provide a theoretical base for studying neighborhood mechanisms and specify different levels (individual, family, school, peer, community) at which processes may operate. Implications for an emerging developmental framework for research on neighborhoods are discussed.

A perturbative clustering hyper-heuristic framework for the Danish railway system

DEFF Research Database (Denmark)

M. Pour, Shahrzad; Rasmussen, Kourosh Marjani; Burke, Edmund K.

, we propose a perturbative clustering hyper-heuristic framework. The framework improves an initial solution by reassigning outliers (those tasks that are far away) to a better cluster choice at each iteration while taking balanced crews workloads into account. The framework introduces five lowlevel...... heuristics and employs an adaptive choice function as a robust learning mechanism. The results of adaptive clustering hyper-heuristic are compared with two exact and heuristic assignment algorithms from the literature and with the random hyper-heuristic framework on 12 datasets. In comparison with the exact...... formulation, the proposed framework could obtain promising results and solved the data instances up to 5000 number of tasks. In comparison with heuristic assignment and the random hyper-heuristic, the framework yielded approximately 11%, 27% and 10%,13% mprovement on total distance and the maximum distance...

Who Gentrifies Low-Income Neighborhoods?*

Science.gov (United States)

McKinnish, Terra; Walsh, Randall; White, T. Kirk

2009-01-01

This paper uses confidential Census data, specifically the 1990 and 2000 Census Long Form data, to study demographic processes in neighborhoods that gentrified during the 1990’s. In contrast to previous studies, the analysis is conducted at the more refined census-tract level, with a narrower definition of gentrification and more closely matched comparison neighborhoods. Furthermore, our access to individual-level data with census tract identifiers allows us to separately identify recent in-migrants and long-term residents. Our results indicate that, on average, the demographic flows associated with the gentrification of urban neighborhoods during the 1990’s are not consistent with displacement and harm to minority households. In fact, taken as a whole, our results suggest that gentrification of predominantly black neighborhoods creates neighborhoods that are attractive to middle-class black households. PMID:20161532

The max–min ant system and tabu search for pressurized water reactor loading pattern design

International Nuclear Information System (INIS)

Lin, Chaung; Chen, Ying-Hsiu

2014-01-01

Highlights: • An automatic loading pattern design tool for a pressurized water reactor is developed. • The design method consists of max–min ant system and tabu search. • The heuristic rules are developed to generate the candidates for tabu search. • The initial solution of tabu search is provided by max–min ant system. • The new algorithm shows very satisfactory results compared to the old one. - Abstract: An automatic loading pattern (LP) design tool for a pressurized water reactor is developed. The design procedure consists of two steps: first, a LP is generated using max–min ant system (MMAS) and then tabu search (TS) is adopted to search the satisfactory LP. The MMAS is previously developed and the TS process is newly-developed. The heuristic rules are implemented to generate the candidate LP in TS process. The heuristic rules are comprised of two kinds of action, i.e., a single swap in the location of two fuel assemblies and rotation of fuel assembly. Since developed TS process is a local search algorithm, it is efficient for the minor change of LP. It means that a proper initial LP should be provided by the first step, i.e., by MMAS. The design requirements such as hot channel factor, the hot zero power moderator temperature coefficient, and cycle length are formulated in the objective function. The results show that the developed tool can obtain the satisfactory LP and dramatically reduce the computation time compared with previous tool using ant system alone

The neighborhood energy balance equation: does neighborhood food retail environment + physical activity environment = obesity? The CARDIA study.

Directory of Open Access Journals (Sweden)

Janne Boone-Heinonen

Full Text Available Recent obesity prevention initiatives focus on healthy neighborhood design, but most research examines neighborhood food retail and physical activity (PA environments in isolation. We estimated joint, interactive, and cumulative impacts of neighborhood food retail and PA environment characteristics on body mass index (BMI throughout early adulthood.We used cohort data from the Coronary Artery Risk Development in Young Adults (CARDIA Study [n=4,092; Year 7 (24-42 years, 1992-1993 followed over 5 exams through Year 25 (2010-2011; 12,921 person-exam observations], with linked time-varying geographic information system-derived neighborhood environment measures. Using regression with fixed effects for individuals, we modeled time-lagged BMI as a function of food and PA resource density (counts per population and neighborhood development intensity (a composite density score. We controlled for neighborhood poverty, individual-level sociodemographics, and BMI in the prior exam; and included significant interactions between neighborhood measures and by sex. Using model coefficients, we simulated BMI reductions in response to single and combined neighborhood improvements. Simulated increase in supermarket density (from 25(th to 75(th percentile predicted inter-exam reduction in BMI of 0.09 kg/m(2 [estimate (95% CI: -0.09 (-0.16, -0.02]. Increasing commercial PA facility density predicted BMI reductions up to 0.22 kg/m(2 in men, with variation across other neighborhood features [estimate (95% CI range: -0.14 (-0.29, 0.01 to -0.22 (-0.37, -0.08]. Simultaneous increases in supermarket and commercial PA facility density predicted inter-exam BMI reductions up to 0.31 kg/m(2 in men [estimate (95% CI range: -0.23 (-0.39, -0.06 to -0.31 (-0.47, -0.15] but not women. Reduced fast food restaurant and convenience store density and increased public PA facility density and neighborhood development intensity did not predict reductions in BMI.Findings suggest that

Knowledge discovery in hyper-heuristic using case-based reasoning on course timetabling

OpenAIRE

Burke, Edmund; MacCarthy, Bart L.; Petrovic, Sanja; Qu, Rong

2002-01-01

This paper presents a new hyper-heuristic method using Case-Based Reasoning (CBR) for solving course timetabling problems. The term Hyper-heuristics has recently been employed to refer to 'heuristics that choose heuristics' rather than heuristics that operate directly on given problems. One of the overriding motivations of hyper-heuristic methods is the attempt to develop techniques that can operate with greater generality than is currently possible. The basic idea behind this is that we main...

The Probability Heuristics Model of Syllogistic Reasoning.

Science.gov (United States)

Chater, Nick; Oaksford, Mike

1999-01-01

Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…

Rural Neighborhood Walkability: Implications for Assessment.

Science.gov (United States)

Kegler, Michelle C; Alcantara, Iris; Haardörfer, Regine; Gemma, Alexandra; Ballard, Denise; Gazmararian, Julie

2015-06-16

Physical activity levels, including walking, are lower in the southern U.S., particularly in rural areas. This study investigated the concept of rural neighborhood walkability to aid in developing tools for assessing walkability and to identify intervention targets in rural communities. Semi-structured interviews were conducted with physically active adults (n = 29) in rural Georgia. Mean age of participants was 55.9 years; 66% were male, 76% were white, and 24% were African American. Participants drew maps of their neighborhoods and discussed the relevance of typical domains of walkability to their decisions to exercise. Comparative analyses were conducted to identify major themes. The majority felt the concept of neighborhood was applicable and viewed their neighborhood as small geographically (less than 0.5 square miles). Sidewalks were not viewed as essential for neighborhood-based physical activity and typical destinations for walking were largely absent. Destinations within walking distance included neighbors' homes and bodies of water. Views were mixed on whether shade, safety, dogs, and aesthetics affected decisions to exercise in their neighborhoods. Measures of neighborhood walkability in rural areas should acknowledge the small size of self-defined neighborhoods, that walking in rural areas is likely for leisure time exercise, and that some domains may not be relevant.

Comparative study of heuristic evaluation and usability testing methods.

Science.gov (United States)

Thyvalikakath, Thankam Paul; Monaco, Valerie; Thambuganipalle, Himabindu; Schleyer, Titus

2009-01-01

Usability methods, such as heuristic evaluation, cognitive walk-throughs and user testing, are increasingly used to evaluate and improve the design of clinical software applications. There is still some uncertainty, however, as to how those methods can be used to support the development process and evaluation in the most meaningful manner. In this study, we compared the results of a heuristic evaluation with those of formal user tests in order to determine which usability problems were detected by both methods. We conducted heuristic evaluation and usability testing on four major commercial dental computer-based patient records (CPRs), which together cover 80% of the market for chairside computer systems among general dentists. Both methods yielded strong evidence that the dental CPRs have significant usability problems. An average of 50% of empirically-determined usability problems were identified by the preceding heuristic evaluation. Some statements of heuristic violations were specific enough to precisely identify the actual usability problem that study participants encountered. Other violations were less specific, but still manifested themselves in usability problems and poor task outcomes. In this study, heuristic evaluation identified a significant portion of problems found during usability testing. While we make no assumptions about the generalizability of the results to other domains and software systems, heuristic evaluation may, under certain circumstances, be a useful tool to determine design problems early in the development cycle.

Nearest neighbors by neighborhood counting.

Science.gov (United States)

Wang, Hui

2006-06-01

Finding nearest neighbors is a general idea that underlies many artificial intelligence tasks, including machine learning, data mining, natural language understanding, and information retrieval. This idea is explicitly used in the k-nearest neighbors algorithm (kNN), a popular classification method. In this paper, this idea is adopted in the development of a general methodology, neighborhood counting, for devising similarity functions. We turn our focus from neighbors to neighborhoods, a region in the data space covering the data point in question. To measure the similarity between two data points, we consider all neighborhoods that cover both data points. We propose to use the number of such neighborhoods as a measure of similarity. Neighborhood can be defined for different types of data in different ways. Here, we consider one definition of neighborhood for multivariate data and derive a formula for such similarity, called neighborhood counting measure or NCM. NCM was tested experimentally in the framework of kNN. Experiments show that NCM is generally comparable to VDM and its variants, the state-of-the-art distance functions for multivariate data, and, at the same time, is consistently better for relatively large k values. Additionally, NCM consistently outperforms HEOM (a mixture of Euclidean and Hamming distances), the "standard" and most widely used distance function for multivariate data. NCM has a computational complexity in the same order as the standard Euclidean distance function and NCM is task independent and works for numerical and categorical data in a conceptually uniform way. The neighborhood counting methodology is proven sound for multivariate data experimentally. We hope it will work for other types of data.

Neighborhood Context and Immigrant Young Children's Development

Science.gov (United States)

Leventhal, Tama; Shuey, Elizabeth A.

2014-01-01

This study explored how neighborhood social processes and resources, relevant to immigrant families and immigrant neighborhoods, contribute to young children's behavioral functioning and achievement across diverse racial/ethnic groups. Data were drawn from the Project on Human Development in Chicago Neighborhoods, a neighborhood-based,…

Internal Medicine residents use heuristics to estimate disease probability

Directory of Open Access Journals (Sweden)

Sen Phang

2015-12-01

Conclusions: Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing.

NeighborHood

OpenAIRE

Corominola Ocaña, Víctor

2015-01-01

NeighborHood és una aplicació basada en el núvol, adaptable a qualsevol dispositiu (mòbil, tablet, desktop). L'objectiu d'aquesta aplicació és poder permetre als usuaris introduir a les persones del seu entorn més immediat i que aquestes persones siguin visibles per a la resta d'usuaris. NeighborHood es una aplicación basada en la nube, adaptable a cualquier dispositivo (móvil, tablet, desktop). El objetivo de esta aplicación es poder permitir a los usuarios introducir a las personas de su...

Expanding the Possibilities of AIS Data with Heuristics

Directory of Open Access Journals (Sweden)

Bjørnar Brende Smestad

2017-06-01

Full Text Available Automatic Identification System (AIS is primarily used as a tracking system for ships, but with the launch of satellites to collect these data, new and previously untested possibilities are emerging. This paper presents the development of heuristics for establishing the specific ship type using information retrieved from AIS data alone. These heuristics expand the possibilities of AIS data, as the specific ship type is vital for several transportation research cases, such as emission analyses of ship traffic and studies on slow steaming. The presented method for developing heuristics can be used for a wider range of vessels. These heuristics may form the basis of large-scale studies on ship traffic using AIS data when it is not feasible or desirable to use commercial ship data registers.

Impact of heuristics in clustering large biological networks.

Science.gov (United States)

Shafin, Md Kishwar; Kabir, Kazi Lutful; Ridwan, Iffatur; Anannya, Tasmiah Tamzid; Karim, Rashid Saadman; Hoque, Mohammad Mozammel; Rahman, M Sohel

2015-12-01

Traditional clustering algorithms often exhibit poor performance for large networks. On the contrary, greedy algorithms are found to be relatively efficient while uncovering functional modules from large biological networks. The quality of the clusters produced by these greedy techniques largely depends on the underlying heuristics employed. Different heuristics based on different attributes and properties perform differently in terms of the quality of the clusters produced. This motivates us to design new heuristics for clustering large networks. In this paper, we have proposed two new heuristics and analyzed the performance thereof after incorporating those with three different combinations in a recently celebrated greedy clustering algorithm named SPICi. We have extensively analyzed the effectiveness of these new variants. The results are found to be promising. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Priority Heuristic: Making Choices Without Trade-Offs

Science.gov (United States)

Brandstätter, Eduard; Gigerenzer, Gerd; Hertwig, Ralph

2010-01-01

Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, we generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (i) Allais' paradox, (ii) risk aversion for gains if probabilities are high, (iii) risk seeking for gains if probabilities are low (lottery tickets), (iv) risk aversion for losses if probabilities are low (buying insurance), (v) risk seeking for losses if probabilities are high, (vi) certainty effect, (vii) possibility effect, and (viii) intransitivities. We test how accurately the heuristic predicts people's choices, compared to previously proposed heuristics and three modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory. PMID:16637767

Cognitive load during route selection increases reliance on spatial heuristics.

Science.gov (United States)

Brunyé, Tad T; Martis, Shaina B; Taylor, Holly A

2018-05-01

Planning routes from maps involves perceiving the symbolic environment, identifying alternate routes and applying explicit strategies and implicit heuristics to select an option. Two implicit heuristics have received considerable attention, the southern route preference and initial segment strategy. This study tested a prediction from decision-making theory that increasing cognitive load during route planning will increase reliance on these heuristics. In two experiments, participants planned routes while under conditions of minimal (0-back) or high (2-back) working memory load. In Experiment 1, we examined how memory load impacts the southern route heuristic. In Experiment 2, we examined how memory load impacts the initial segment heuristic. Results replicated earlier results demonstrating a southern route preference (Experiment 1) and initial segment strategy (Experiment 2) and further demonstrated that evidence for heuristic reliance is more likely under conditions of concurrent working memory load. Furthermore, the extent to which participants maintained efficient route selection latencies in the 2-back condition predicted the magnitude of this effect. Together, results demonstrate that working memory load increases the application of heuristics during spatial decision making, particularly when participants attempt to maintain quick decisions while managing concurrent task demands.

Work and Home Neighborhood Design and Physical Activity.

Science.gov (United States)

Carlson, Jordan A; Frank, Lawrence D; Ulmer, Jared; Conway, Terry L; Saelens, Brian E; Cain, Kelli L; Sallis, James F

2018-01-01

To investigate relations of perceived worksite neighborhood environments to total physical activity and active transportation, over and above home neighborhood built environments. Observational epidemiologic study. Baltimore, Maryland-Washington, DC, and Seattle-King County, Washington metropolitan areas. One thousand eighty-five adults (mean age = 45.0 [10.2]; 46% women) recruited from 32 neighborhoods stratified by high/low neighborhood income and walkability. The Neighborhood Environment Walkability Survey assessed perceptions of worksite and home neighborhood environments. Accelerometers assessed total moderate-to-vigorous physical activity (MVPA). The International Physical Activity Questionnaire assessed total active transportation and active transportation to and around work. Mixed-effects regression tested relations of home and worksite neighborhood environments to each physical activity outcome, adjusted for demographics. Home and worksite mixed land use and street connectivity had the most consistent positive associations with physical activity outcomes. Worksite traffic and pedestrian safety were also associated with multiple physical activity outcomes. The worksite neighborhood explained additional variance in physical activity outcomes than explained by the home neighborhood. Worksite and home neighborhood environments interacted in explaining active transportation to work, with the greatest impacts occurring when both neighborhoods were activity supportive. Both worksite and home neighborhood environments were independently related to total MVPA and active transportation. Community design policies should target improving the physical activity supportiveness of worksite neighborhood environments and integrating commercial and residential development.

Applying usability heuristics to radiotherapy systems

International Nuclear Information System (INIS)

Chan, Alvita J.; Islam, Mohammad K.; Rosewall, Tara; Jaffray, David A.; Easty, Anthony C.; Cafazzo, Joseph A.

2012-01-01

Background and purpose: Heuristic evaluations have been used to evaluate safety of medical devices by identifying and assessing usability issues. Since radiotherapy treatment delivery systems often consist of multiple complex user-interfaces, a heuristic evaluation was conducted to assess the potential safety issues of such a system. Material and methods: A heuristic evaluation was conducted to evaluate the treatment delivery system at Princess Margaret Hospital (Toronto, Canada). Two independent evaluators identified usability issues with the user-interfaces and rated the severity of each issue. Results: The evaluators identified 75 usability issues in total. Eighteen of them were rated as high severity, indicating the potential to have a major impact on patient safety. A majority of issues were found on the record and verify system, and many were associated with the patient setup process. While the hospital has processes in place to ensure patient safety, recommendations were developed to further mitigate the risks of potential consequences. Conclusions: Heuristic evaluation is an efficient and inexpensive method that can be successfully applied to radiotherapy delivery systems to identify usability issues and improve patient safety. Although this study was conducted only at one site, the findings may have broad implications for the design of these systems.

Neighborhood Concentrated Disadvantage and Dating Violence among Urban Adolescents: The Mediating Role of Neighborhood Social Processes.

Science.gov (United States)

Garthe, Rachel C; Gorman-Smith, Deborah; Gregory, Joshua; E Schoeny, Michael

2018-03-14

The link between relationship violence and aspects of neighborhood concentrated disadvantage (e.g., percent of unemployed adults, percent of families below poverty level), has been established. However, the literature examining neighborhood social processes, including informal social control and social cohesion, in relation to adolescent dating violence has shown mixed results with a limited theoretical foundation and methodology. Using a social disorganization theoretical framework, this study examined the mediating role of these neighborhood social processes in the relation between concentrated disadvantage and adolescent dating violence within an urban context. Participants included 605 adult residents in 30 census tracts and 203 adolescents from neighborhoods on the West and South sides of Chicago. Neighborhood-level concentrated disadvantage was measured via Census data, adult residents reported on neighborhood social processes, and youth reported on dating violence. Informal social control was negatively associated with dating violence, and social cohesion was positively associated with dating violence. A multilevel mediation model showed that concentrated disadvantage was related to higher levels of dating violence via lower levels of informal social control. These results extend social disorganization theory to dating violence within an urban context, while also highlighting the important role of neighborhood processes on relationship violence. Implications for research and intervention programming are discussed. © Society for Community Research and Action 2018.

Comprehensive Neighborhood Portraits and Child Asthma Disparities.

Science.gov (United States)

Kranjac, Ashley W; Kimbro, Rachel T; Denney, Justin T; Osiecki, Kristin M; Moffett, Brady S; Lopez, Keila N

2017-07-01

Objectives Previous research has established links between child, family, and neighborhood disadvantages and child asthma. We add to this literature by first characterizing neighborhoods in Houston, TX by demographic, economic, and air quality characteristics to establish differences in pediatric asthma diagnoses across neighborhoods. Second, we identify the relative risk of social, economic, and environmental risk factors for child asthma diagnoses. Methods We geocoded and linked electronic pediatric medical records to neighborhood-level social and economic indicators. Using latent profile modeling techniques, we identified Advantaged, Middle-class, and Disadvantaged neighborhoods. We then used a modified version of the Blinder-Oaxaca regression decomposition method to examine differences in asthma diagnoses across children in these different neighborhoods. Results Both compositional (the characteristics of the children and the ambient air quality in the neighborhood) and associational (the relationship between child and air quality characteristics and asthma) differences within the distinctive neighborhood contexts influence asthma outcomes. For example, unequal exposure to PM 2.5 and O 3 among children in Disadvantaged and Middle-class neighborhoods contribute to asthma diagnosis disparities within these contexts. For children in Disadvantaged and Advantaged neighborhoods, associational differences between racial/ethnic and socioeconomic characteristics and asthma diagnoses explain a significant proportion of the gap. Conclusions for Practice Our results provide evidence that differential exposure to pollution and protective factors associated with non-Hispanic White children and children from affluent families contribute to asthma disparities between neighborhoods. Future researchers should consider social and racial inequalities as more proximate drivers, not merely as associated, with asthma disparities in children.

Neighborhood Influences on Perceived Social Support Among Parents: Findings from the Project on Human Development in Chicago Neighborhoods

Science.gov (United States)

Tendulkar, Shalini A.; Koenen, Karestan C.; Dunn, Erin C.; Buka, Stephen; Subramanian, S. V.

2012-01-01

Background Social support is frequently linked to positive parenting behavior. Similarly, studies increasingly show a link between neighborhood residential environment and positive parenting behavior. However, less is known about how the residential environment influences parental social support. To address this gap, we examine the relationship between neighborhood concentrated disadvantage and collective efficacy and the level and change in parental caregiver perceptions of non-familial social support. Methodology/Principal Findings The data for this study came from three data sources, the Project on Human Development in Chicago Neighborhoods (PHDCN) Study's Longitudinal Cohort Survey of caregivers and their offspring, a Community Survey of adult residents in these same neighborhoods and the 1990 Census. Social support is measured at Wave 1 and Wave 3 and neighborhood characteristics are measured at Wave 1. Multilevel linear regression models are fit. The results show that neighborhood collective efficacy is a significant (ß = .04; SE = .02; p = .03), predictor of the positive change in perceived social support over a 7 year period, however, not of the level of social support, adjusting for key compositional variables and neighborhood concentrated disadvantage. In contrast concentrated neighborhood disadvantage is not a significant predictor of either the level or change in social support. Conclusion Our finding suggests that neighborhood collective efficacy may be important for inducing the perception of support from friends in parental caregivers over time. PMID:22493683

Neighborhood influences on perceived social support among parents: findings from the project on human development in Chicago neighborhoods.

Science.gov (United States)

Tendulkar, Shalini A; Koenen, Karestan C; Dunn, Erin C; Buka, Stephen; Subramanian, S V

2012-01-01

Social support is frequently linked to positive parenting behavior. Similarly, studies increasingly show a link between neighborhood residential environment and positive parenting behavior. However, less is known about how the residential environment influences parental social support. To address this gap, we examine the relationship between neighborhood concentrated disadvantage and collective efficacy and the level and change in parental caregiver perceptions of non-familial social support. The data for this study came from three data sources, the Project on Human Development in Chicago Neighborhoods (PHDCN) Study's Longitudinal Cohort Survey of caregivers and their offspring, a Community Survey of adult residents in these same neighborhoods and the 1990 Census. Social support is measured at Wave 1 and Wave 3 and neighborhood characteristics are measured at Wave 1. Multilevel linear regression models are fit. The results show that neighborhood collective efficacy is a significant (ß = .04; SE = .02; p = .03), predictor of the positive change in perceived social support over a 7 year period, however, not of the level of social support, adjusting for key compositional variables and neighborhood concentrated disadvantage. In contrast concentrated neighborhood disadvantage is not a significant predictor of either the level or change in social support. Our finding suggests that neighborhood collective efficacy may be important for inducing the perception of support from friends in parental caregivers over time.

Schools, Neighborhood Risk Factors, and Crime

Science.gov (United States)

Willits, Dale; Broidy, Lisa; Denman, Kristine

2013-01-01

Prior research has identified a link between schools (particularly high schools) and neighborhood crime rates. However, it remains unclear whether the relationship between schools and crime is a reflection of other criminogenic dynamics at the neighborhood level or whether schools influence neighborhood crime patterns independently of other…

Heuristics: foundations for a novel approach to medical decision making.

Science.gov (United States)

Bodemer, Nicolai; Hanoch, Yaniv; Katsikopoulos, Konstantinos V

2015-03-01

Medical decision-making is a complex process that often takes place during uncertainty, that is, when knowledge, time, and resources are limited. How can we ensure good decisions? We present research on heuristics-simple rules of thumb-and discuss how medical decision-making can benefit from these tools. We challenge the common view that heuristics are only second-best solutions by showing that they can be more accurate, faster, and easier to apply in comparison to more complex strategies. Using the example of fast-and-frugal decision trees, we illustrate how heuristics can be studied and implemented in the medical context. Finally, we suggest how a heuristic-friendly culture supports the study and application of heuristics as complementary strategies to existing decision rules.

Robust Circle Detection Using Harmony Search

Directory of Open Access Journals (Sweden)

Jaco Fourie

2017-01-01

Full Text Available Automatic circle detection is an important element of many image processing algorithms. Traditionally the Hough transform has been used to find circular objects in images but more modern approaches that make use of heuristic optimisation techniques have been developed. These are often used in large complex images where the presence of noise or limited computational resources make the Hough transform impractical. Previous research on the use of the Harmony Search (HS in circle detection showed that HS is an attractive alternative to many of the modern circle detectors based on heuristic optimisers like genetic algorithms and simulated annealing. We propose improvements to this work that enables our algorithm to robustly find multiple circles in larger data sets and still work on realistic images that are heavily corrupted by noisy edges.

Neural basis of scientific innovation induced by heuristic prototype.

Directory of Open Access Journals (Sweden)

Junlong Luo

Full Text Available A number of major inventions in history have been based on bionic imitation. Heuristics, by applying biological systems to the creation of artificial devices and machines, might be one of the most critical processes in scientific innovation. In particular, prototype heuristics propositions that innovation may engage automatic activation of a prototype such as a biological system to form novel associations between a prototype's function and problem-solving. We speculated that the cortical dissociation between the automatic activation and forming novel associations in innovation is critical point to heuristic creativity. In the present study, novel and old scientific innovations (NSI and OSI were selected as experimental materials in using learning-testing paradigm to explore the neural basis of scientific innovation induced by heuristic prototype. College students were required to resolve NSI problems (to which they did not know the answers and OSI problems (to which they knew the answers. From two fMRI experiments, our results showed that the subjects could resolve NSI when provided with heuristic prototypes. In Experiment 1, it was found that the lingual gyrus (LG; BA18 might be related to prototype heuristics in college students resolving NSI after learning a relative prototype. In Experiment 2, the LG (BA18 and precuneus (BA31 were significantly activated for NSI compared to OSI when college students learned all prototypes one day before the test. In addition, the mean beta-values of these brain regions of NSI were all correlated with the behavior accuracy of NSI. As our hypothesis indicated, the findings suggested that the LG might be involved in forming novel associations using heuristic information, while the precuneus might be involved in the automatic activation of heuristic prototype during scientific innovation.

Neural basis of scientific innovation induced by heuristic prototype.

Science.gov (United States)

Luo, Junlong; Li, Wenfu; Qiu, Jiang; Wei, Dongtao; Liu, Yijun; Zhang, Qinlin

2013-01-01

A number of major inventions in history have been based on bionic imitation. Heuristics, by applying biological systems to the creation of artificial devices and machines, might be one of the most critical processes in scientific innovation. In particular, prototype heuristics propositions that innovation may engage automatic activation of a prototype such as a biological system to form novel associations between a prototype's function and problem-solving. We speculated that the cortical dissociation between the automatic activation and forming novel associations in innovation is critical point to heuristic creativity. In the present study, novel and old scientific innovations (NSI and OSI) were selected as experimental materials in using learning-testing paradigm to explore the neural basis of scientific innovation induced by heuristic prototype. College students were required to resolve NSI problems (to which they did not know the answers) and OSI problems (to which they knew the answers). From two fMRI experiments, our results showed that the subjects could resolve NSI when provided with heuristic prototypes. In Experiment 1, it was found that the lingual gyrus (LG; BA18) might be related to prototype heuristics in college students resolving NSI after learning a relative prototype. In Experiment 2, the LG (BA18) and precuneus (BA31) were significantly activated for NSI compared to OSI when college students learned all prototypes one day before the test. In addition, the mean beta-values of these brain regions of NSI were all correlated with the behavior accuracy of NSI. As our hypothesis indicated, the findings suggested that the LG might be involved in forming novel associations using heuristic information, while the precuneus might be involved in the automatic activation of heuristic prototype during scientific innovation.

"A Heuristic for Visual Thinking in History"

Science.gov (United States)

Staley, David J.

2007-01-01

This article details a heuristic history teachers can use in assigning and evaluating multimedia projects in history. To use this heuristic successfully, requires more than simply following the steps in the list or stages in a recipe: in many ways, it requires a reorientation in what it means to think like an historian. This article, as much as…

Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry.

Science.gov (United States)

Rappoport, Dmitrij; Galvin, Cooper J; Zubarev, Dmitry Yu; Aspuru-Guzik, Alán

2014-03-11

While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles.

An improved sheep flock heredity algorithm for job shop scheduling and flow shop scheduling problems

Directory of Open Access Journals (Sweden)

Chandramouli Anandaraman

2011-10-01

Full Text Available Job Shop Scheduling Problem (JSSP and Flow Shop Scheduling Problem (FSSP are strong NP-complete combinatorial optimization problems among class of typical production scheduling problems. An improved Sheep Flock Heredity Algorithm (ISFHA is proposed in this paper to find a schedule of operations that can minimize makespan. In ISFHA, the pairwise mutation operation is replaced by a single point mutation process with a probabilistic property which guarantees the feasibility of the solutions in the local search domain. A Robust-Replace (R-R heuristic is introduced in place of chromosomal crossover to enhance the global search and to improve the convergence. The R-R heuristic is found to enhance the exploring potential of the algorithm and enrich the diversity of neighborhoods. Experimental results reveal the effectiveness of the proposed algorithm, whose optimization performance is markedly superior to that of genetic algorithms and is comparable to the best results reported in the literature.

Internet Bad Neighborhoods Aggregation

NARCIS (Netherlands)

Moreira Moura, Giovane; Sadre, R.; Sperotto, Anna; Pras, Aiko; Paschoal Gaspary, L.; De Turk, Filip

Internet Bad Neighborhoods have proven to be an innovative approach for fighting spam. They have also helped to understand how spammers are distributed on the Internet. In our previous works, the size of each bad neighborhood was fixed to a /24 subnetwork. In this paper, however, we investigate if

Negative life events vary by neighborhood and mediate the relation between neighborhood context and psychological well-being.

Directory of Open Access Journals (Sweden)

Katherine King

Full Text Available Researchers have speculated that negative life events are more common in troubled neighborhoods, amplifying adverse effects on health. Using a clustered representative sample of Chicago residents (2001-03; n = 3,105 from the Chicago Community Adult Health Survey, we provide the first documentation that negative life events are highly geographically clustered compared to health outcomes. Associations between neighborhood context and negative life events were also found to vary by event type. We then demonstrate the power of a contextualized approach by testing path models in which life events mediate the relation between neighborhood characteristics and health outcomes, including self-rated health, anxiety, and depression. The indirect paths between neighborhood conditions and health through negative life event exposure are highly significant and large compared to the direct paths from neighborhood conditions to health. Our results indicate that neighborhood conditions can have acute as well as chronic effects on health, and that negative life events are a powerful mechanism by which context may influence health.

Negative life events vary by neighborhood and mediate the relation between neighborhood context and psychological well-being.

Science.gov (United States)

King, Katherine; Ogle, Christin

2014-01-01

Researchers have speculated that negative life events are more common in troubled neighborhoods, amplifying adverse effects on health. Using a clustered representative sample of Chicago residents (2001-03; n = 3,105) from the Chicago Community Adult Health Survey, we provide the first documentation that negative life events are highly geographically clustered compared to health outcomes. Associations between neighborhood context and negative life events were also found to vary by event type. We then demonstrate the power of a contextualized approach by testing path models in which life events mediate the relation between neighborhood characteristics and health outcomes, including self-rated health, anxiety, and depression. The indirect paths between neighborhood conditions and health through negative life event exposure are highly significant and large compared to the direct paths from neighborhood conditions to health. Our results indicate that neighborhood conditions can have acute as well as chronic effects on health, and that negative life events are a powerful mechanism by which context may influence health.

Interliminal Design: Understanding cognitive heuristics to mitigate design distortion

Directory of Open Access Journals (Sweden)

Andrew McCollough

2014-12-01

Full Text Available Cognitive heuristics are mental shortcuts adapted over time to enable rapid interpretation of our complex environment. They are intrinsic to human cognition and resist modification. Heuristics applied outside the context to which they are best suited are termed cognitive bias, and are the cause of systematic errors in judgment and reasoning. As both a cognitive and intuitive discipline, design by individuals is vulnerable to context-inappropriate heuristic usage. Designing in groups can act positively to counterbalance these tendencies, but is subject to heuristic misuse and biases particular to social environments. Mismatch between desired and actual outcomes– termed here, design distortion – occurs when such usage goes unnoticed and unaddressed, and can affect multiple dimensions of a system. We propose a methodology, interliminal design, emerging from the Program in Collaborative Design at Pacific Northwest College of Art, to specifically address the influence of cognitive heuristics in design. This adaptive approach involves reflective, dialogic, inquiry-driven practices intended to increase awareness of heuristic usage, and identify aspects of the design process vulnerable to misuse on both individual and group levels. By facilitating the detection and mitigation of potentially costly errors in judgment and decision-making that create distortion, such metacognitive techniques can meaningfully improve design.

A Local Search Algorithm for the Flow Shop Scheduling Problem with Release Dates

Directory of Open Access Journals (Sweden)

Tao Ren

2015-01-01

Full Text Available This paper discusses the flow shop scheduling problem to minimize the makespan with release dates. By resequencing the jobs, a modified heuristic algorithm is obtained for handling large-sized problems. Moreover, based on some properties, a local search scheme is provided to improve the heuristic to gain high-quality solution for moderate-sized problems. A sequence-independent lower bound is presented to evaluate the performance of the algorithms. A series of simulation results demonstrate the effectiveness of the proposed algorithms.

Heuristic Diagrams as a Tool to Teach History of Science

Science.gov (United States)

Chamizo, Jose A.

2012-01-01

The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The…

Neighborhood perceptions and allostatic load

DEFF Research Database (Denmark)

van Deurzen, Ioana; Rod, Naja Hulvej; Christensen, Ulla

2016-01-01

An influential argument explaining why living in certain neighborhoods can become harmful to one's health maintains that individuals can perceive certain characteristics of the neighborhood as threatening and the prolonged exposure to a threatening environment could induce chronic stress. Following...... this line of argumentation, in the present study we test whether subjective perceptions of neighborhood characteristics relate to an objective measure of stress-related physiological functioning, namely allostatic load (AL). We use a large dataset of 5280 respondents living in different regions of Denmark...... and we account for two alternative mechanisms, i.e., the objective characteristics of the living environment and the socio-economic status of individuals. Our results support the chronic stress mechanisms linking neighborhood quality to health. Heightened perceptions of disorder and pollution were found...

Heuristic Diagrams as a Tool to Teach History of Science

Science.gov (United States)

Chamizo, José A.

2012-05-01

The graphic organizer called here heuristic diagram as an improvement of Gowin's Vee heuristic is proposed as a tool to teach history of science. Heuristic diagrams have the purpose of helping students (or teachers, or researchers) to understand their own research considering that asks and problem-solving are central to scientific activity. The left side originally related in Gowin's Vee with philosophies, theories, models, laws or regularities now agrees with Toulmin's concepts (language, models as representation techniques and application procedures). Mexican science teachers without experience in science education research used the heuristic diagram to learn about the history of chemistry considering also in the left side two different historical times: past and present. Through a semantic differential scale teachers' attitude to the heuristic diagram was evaluated and its usefulness was demonstrated.

Neighborhood influences on perceived social support among parents: findings from the project on human development in Chicago neighborhoods.

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Shalini A Tendulkar

Full Text Available BACKGROUND: Social support is frequently linked to positive parenting behavior. Similarly, studies increasingly show a link between neighborhood residential environment and positive parenting behavior. However, less is known about how the residential environment influences parental social support. To address this gap, we examine the relationship between neighborhood concentrated disadvantage and collective efficacy and the level and change in parental caregiver perceptions of non-familial social support. METHODOLOGY/PRINCIPAL FINDINGS: The data for this study came from three data sources, the Project on Human Development in Chicago Neighborhoods (PHDCN Study's Longitudinal Cohort Survey of caregivers and their offspring, a Community Survey of adult residents in these same neighborhoods and the 1990 Census. Social support is measured at Wave 1 and Wave 3 and neighborhood characteristics are measured at Wave 1. Multilevel linear regression models are fit. The results show that neighborhood collective efficacy is a significant (ß = .04; SE = .02; p = .03, predictor of the positive change in perceived social support over a 7 year period, however, not of the level of social support, adjusting for key compositional variables and neighborhood concentrated disadvantage. In contrast concentrated neighborhood disadvantage is not a significant predictor of either the level or change in social support. CONCLUSION: Our finding suggests that neighborhood collective efficacy may be important for inducing the perception of support from friends in parental caregivers over time.

The priority heuristic: making choices without trade-offs.

Science.gov (United States)

Brandstätter, Eduard; Gigerenzer, Gerd; Hertwig, Ralph

2006-04-01

Bernoulli's framework of expected utility serves as a model for various psychological processes, including motivation, moral sense, attitudes, and decision making. To account for evidence at variance with expected utility, the authors generalize the framework of fast and frugal heuristics from inferences to preferences. The priority heuristic predicts (a) the Allais paradox, (b) risk aversion for gains if probabilities are high, (c) risk seeking for gains if probabilities are low (e.g., lottery tickets), (d) risk aversion for losses if probabilities are low (e.g., buying insurance), (e) risk seeking for losses if probabilities are high, (f) the certainty effect, (g) the possibility effect, and (h) intransitivities. The authors test how accurately the heuristic predicts people's choices, compared with previously proposed heuristics and 3 modifications of expected utility theory: security-potential/aspiration theory, transfer-of-attention-exchange model, and cumulative prospect theory. ((c) 2006 APA, all rights reserved).

Identifying Onboarding Heuristics for Free-to-Play Mobile Games

DEFF Research Database (Denmark)

Thomsen, Line Ebdrup; Weigert Petersen, Falko; Drachen, Anders

2016-01-01

a set of heuristics for the design of onboarding phases in mobile games is presented. The heuristics are identified by a lab-based mixed-methods experiment, utilizing lightweight psycho-physiological measures together with self-reported player responses, across three titles that cross the genres...... of puzzle games, base builders and arcade games, and utilize different onboarding phase design approaches. Results showcase how heuristics can be used to design engaging onboarding phases in mobile games....

A heuristic evaluation of the Facebook's advertising tool beacon

OpenAIRE

Jamal, A; Cole, M

2009-01-01

Interface usability is critical to the successful adoption of information systems. The aim of this study is to evaluate interface of Facebook's advertising tool Beacon by using privacy heuristics [4]. Beacon represents an interesting case study because of the negative media and user backlash it received. The findings of heuristic evaluation suggest violation of privacy heuristics [4]. Here, analysis identified concerns about user choice and consent, integrity and security of data, and awarene...

Interliminal Design: Understanding cognitive heuristics to mitigate design distortion

OpenAIRE

Andrew McCollough; DeAunne Denmark; Donald Harker

2014-01-01

Cognitive heuristics are mental shortcuts adapted over time to enable rapid interpretation of our complex environment. They are intrinsic to human cognition and resist modification. Heuristics applied outside the context to which they are best suited are termed cognitive bias, and are the cause of systematic errors in judgment and reasoning. As both a cognitive and intuitive discipline, design by individuals is vulnerable to context-inappropriate heuristic usage. Designing in groups can act p...

Internal Medicine residents use heuristics to estimate disease probability.

Science.gov (United States)

Phang, Sen Han; Ravani, Pietro; Schaefer, Jeffrey; Wright, Bruce; McLaughlin, Kevin

2015-01-01

Training in Bayesian reasoning may have limited impact on accuracy of probability estimates. In this study, our goal was to explore whether residents previously exposed to Bayesian reasoning use heuristics rather than Bayesian reasoning to estimate disease probabilities. We predicted that if residents use heuristics then post-test probability estimates would be increased by non-discriminating clinical features or a high anchor for a target condition. We randomized 55 Internal Medicine residents to different versions of four clinical vignettes and asked them to estimate probabilities of target conditions. We manipulated the clinical data for each vignette to be consistent with either 1) using a representative heuristic, by adding non-discriminating prototypical clinical features of the target condition, or 2) using anchoring with adjustment heuristic, by providing a high or low anchor for the target condition. When presented with additional non-discriminating data the odds of diagnosing the target condition were increased (odds ratio (OR) 2.83, 95% confidence interval [1.30, 6.15], p = 0.009). Similarly, the odds of diagnosing the target condition were increased when a high anchor preceded the vignette (OR 2.04, [1.09, 3.81], p = 0.025). Our findings suggest that despite previous exposure to the use of Bayesian reasoning, residents use heuristics, such as the representative heuristic and anchoring with adjustment, to estimate probabilities. Potential reasons for attribute substitution include the relative cognitive ease of heuristics vs. Bayesian reasoning or perhaps residents in their clinical practice use gist traces rather than precise probability estimates when diagnosing.

Maximum relevance, minimum redundancy band selection based on neighborhood rough set for hyperspectral data classification

International Nuclear Information System (INIS)

Liu, Yao; Chen, Yuehua; Tan, Kezhu; Xie, Hong; Wang, Liguo; Xie, Wu; Yan, Xiaozhen; Xu, Zhen

2016-01-01

Band selection is considered to be an important processing step in handling hyperspectral data. In this work, we selected informative bands according to the maximal relevance minimal redundancy (MRMR) criterion based on neighborhood mutual information. Two measures MRMR difference and MRMR quotient were defined and a forward greedy search for band selection was constructed. The performance of the proposed algorithm, along with a comparison with other methods (neighborhood dependency measure based algorithm, genetic algorithm and uninformative variable elimination algorithm), was studied using the classification accuracy of extreme learning machine (ELM) and random forests (RF) classifiers on soybeans’ hyperspectral datasets. The results show that the proposed MRMR algorithm leads to promising improvement in band selection and classification accuracy. (paper)

Neighborhoods, US, 2017, Zillow, SEGS

Data.gov (United States)

U.S. Environmental Protection Agency — This web service depicts nearly 17,000 neighborhood boundaries in over 650 U.S. cities. Zillow created the neighborhood boundaries and is sharing them with the...

The consultation timetabling problem at Danish high schools

DEFF Research Database (Denmark)

Kristiansen, Simon; Sørensen, Matias; Herold, Michald B.

2013-01-01

Gurobi and Adaptive Large Neighborhood Search (ALNS), and computational results are established using 300 real-life datasets. These tests show that the developed ALNS algorithm is significantly outperforming both Gurobi and a currently applied heuristic for the PCTP. For both the PCTP and the SCTP......, it is shown that the ALNS algorithm in average provides results within 5 % of optimum. The developed algorithm has been implemented in the commercial product Lectio, and is therefore available for approximately 95 % of the Danish high schools....

The recognition heuristic : A review of theory and tests

OpenAIRE

Pachur, T.; Todd, P.; Gigerenzer, G.; Schooler, L.; Goldstein, D.

2011-01-01

The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) th...

Neighborhood Disadvantage and Physical Function: The Contributions of Neighborhood-Level Perceptions of Safety From Crime and Walking for Recreation.

Science.gov (United States)

Loh, Venurs H Y; Rachele, Jerome N; Brown, Wendy J; Ghani, Fatima; Turrell, Gavin

2018-04-20

Residents of more socioeconomically disadvantaged neighborhoods are more likely to report poorer physical function, although the reasons for this remain unknown. It is possible that neighborhood-level perceptions of safety from crime contribute to this relationship through its association with walking for recreation. Data were obtained from the fourth wave (collected in 2013) of the HABITAT (How Areas in Brisbane Influence HealTh and AcTivity) multilevel longitudinal study of middle- to older-aged adults (46-74 y) residing in 200 neighborhoods in Brisbane, Australia. The data were analyzed separately for men (n = 2190) and women (n = 2977) using multilevel models. Residents of the most disadvantaged neighborhoods had poorer physical function, perceived their neighborhoods to be less safe from crime, and do less walking for recreation. These factors accounted for differences in physical function between disadvantaged and advantaged neighborhoods (24% for men and 25% for women). This study highlights the importance of contextual characteristics, through their associations with behaviors, that can have in explaining the relationship between neighborhood disadvantage and physical function. Interventions aimed at improving neighborhood safety integrated with supportive environments for physical activity may have positive impact on physical function among all socioeconomic groups.

Multiple Charging Station Location-Routing Problem with Time Window of Electric Vehicle

Directory of Open Access Journals (Sweden)

Wang Li-ying

2015-11-01

Full Text Available This paper presents the electric vehicle (EV multiple charging station location-routing problem with time window to optimize the routing plan of capacitated EVs and the strategy of charging stations. In particular, the strategy of charging stations includes both infrastructure-type selection and station location decisions. The problem accounts for two critical constraints in logistic practice: the vehicle loading capacity and the customer time windows. A hybrid heuristic that incorporates an adaptive variable neighborhood search (AVNS with the tabu search algorithm for intensification was developed to address the problem. The specialized neighborhood structures and the selection methods of charging station used in the shaking step of AVNS were proposed. In contrast to the commercial solver CPLEX, experimental results on small-scale test instances demonstrate that the algorithm can find nearly optimal solutions on small-scale instances. The results on large-scale instances also show the effectiveness of the algorithm.

Guided Iterative Substructure Search (GI-SSS) - A New Trick for an Old Dog.

Science.gov (United States)

Weskamp, Nils

2016-07-01

Substructure search (SSS) is a fundamental technique supported by various chemical information systems. Many users apply it in an iterative manner: they modify their queries to shape the composition of the retrieved hit sets according to their needs. We propose and evaluate two heuristic extensions of SSS aimed at simplifying these iterative query modifications by collecting additional information during query processing and visualizing this information in an intuitive way. This gives the user a convenient feedback on how certain changes to the query would affect the retrieved hit set and reduces the number of trial-and-error cycles needed to generate an optimal search result. The proposed heuristics are simple, yet surprisingly effective and can be easily added to existing SSS implementations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Can we trust module-respect heuristics?

International Nuclear Information System (INIS)

Mo, Yuchang

2013-01-01

BDD (Binary Decision Diagrams) have proven to be a very efficient tool to assess Fault Trees. However, the size of BDD, and therefore the efficiency of the whole methodology, depends dramatically on the choice of variable ordering. The determination of the best variable ordering is intractable. Therefore, heuristics have been designed to select reasonably good variable orderings. One very important common feature for good static heuristics is to respect modules. In this paper, the notion of module-respect is studied in a systematic way. It is proved that under certain condition there always exists an optimal ordering that respects modules. This condition is that for each module there is always a smallest module BDD and each included module variable appears only once. On the other hand, it is shown that for the trees not satisfying the above sufficient condition the optimal orderings may not be able to be directly generated using module-respect heuristics, even when the shuffling strategy is used.

Heuristics for minimizing the maximum within-clusters distance

Directory of Open Access Journals (Sweden)

José Augusto Fioruci

2012-12-01

Full Text Available The clustering problem consists in finding patterns in a data set in order to divide it into clusters with high within-cluster similarity. This paper presents the study of a problem, here called MMD problem, which aims at finding a clustering with a predefined number of clusters that minimizes the largest within-cluster distance (diameter among all clusters. There are two main objectives in this paper: to propose heuristics for the MMD and to evaluate the suitability of the best proposed heuristic results according to the real classification of some data sets. Regarding the first objective, the results obtained in the experiments indicate a good performance of the best proposed heuristic that outperformed the Complete Linkage algorithm (the most used method from the literature for this problem. Nevertheless, regarding the suitability of the results according to the real classification of the data sets, the proposed heuristic achieved better quality results than C-Means algorithm, but worse than Complete Linkage.

Neighborhood Ethnic Density as an Explanation for the Academic Achievement of Ethnic Minority Youth Placed in Neighborhood Disadvantage

Science.gov (United States)

Madyun, Na'im; Lee, Moosung

2010-01-01

The underachievement of ethnic minority youth from disadvantaged neighborhoods is a pervasive educational issue this nation is facing. Based on an ecological perspective, we examined the contextual effects of neighborhood ethnic density and neighborhood disadvantage on the academic achievement of Hmong immigrant youths. Utilizing hierarchical…

Heuristics structure and pervade formal risk assessment.

Science.gov (United States)

MacGillivray, Brian H

2014-04-01

Lay perceptions of risk appear rooted more in heuristics than in reason. A major concern of the risk regulation literature is that such "error-strewn" perceptions may be replicated in policy, as governments respond to the (mis)fears of the citizenry. This has led many to advocate a relatively technocratic approach to regulating risk, characterized by high reliance on formal risk and cost-benefit analysis. However, through two studies of chemicals regulation, we show that the formal assessment of risk is pervaded by its own set of heuristics. These include rules to categorize potential threats, define what constitutes valid data, guide causal inference, and to select and apply formal models. Some of these heuristics lay claim to theoretical or empirical justifications, others are more back-of-the-envelope calculations, while still more purport not to reflect some truth but simply to constrain discretion or perform a desk-clearing function. These heuristics can be understood as a way of authenticating or formalizing risk assessment as a scientific practice, representing a series of rules for bounding problems, collecting data, and interpreting evidence (a methodology). Heuristics are indispensable elements of induction. And so they are not problematic per se, but they can become so when treated as laws rather than as contingent and provisional rules. Pitfalls include the potential for systematic error, masking uncertainties, strategic manipulation, and entrenchment. Our central claim is that by studying the rules of risk assessment qua rules, we develop a novel representation of the methods, conventions, and biases of the prior art. © 2013 Society for Risk Analysis.

Mathematical programming solver based on local search

CERN Document Server

Gardi, Frédéric; Darlay, Julien; Estellon, Bertrand; Megel, Romain

2014-01-01

This book covers local search for combinatorial optimization and its extension to mixed-variable optimization. Although not yet understood from the theoretical point of view, local search is the paradigm of choice for tackling large-scale real-life optimization problems. Today's end-users demand interactivity with decision support systems. For optimization software, this means obtaining good-quality solutions quickly. Fast iterative improvement methods, like local search, are suited to satisfying such needs. Here the authors show local search in a new light, in particular presenting a new kind of mathematical programming solver, namely LocalSolver, based on neighborhood search. First, an iconoclast methodology is presented to design and engineer local search algorithms. The authors' concern about industrializing local search approaches is of particular interest for practitioners. This methodology is applied to solve two industrial problems with high economic stakes. Software based on local search induces ex...

Geometrical tile design for complex neighborhoods.

Science.gov (United States)

Czeizler, Eugen; Kari, Lila

2009-01-01

Recent research has showed that tile systems are one of the most suitable theoretical frameworks for the spatial study and modeling of self-assembly processes, such as the formation of DNA and protein oligomeric structures. A Wang tile is a unit square, with glues on its edges, attaching to other tiles and forming larger and larger structures. Although quite intuitive, the idea of glues placed on the edges of a tile is not always natural for simulating the interactions occurring in some real systems. For example, when considering protein self-assembly, the shape of a protein is the main determinant of its functions and its interactions with other proteins. Our goal is to use geometric tiles, i.e., square tiles with geometrical protrusions on their edges, for simulating tiled paths (zippers) with complex neighborhoods, by ribbons of geometric tiles with simple, local neighborhoods. This paper is a step toward solving the general case of an arbitrary neighborhood, by proposing geometric tile designs that solve the case of a "tall" von Neumann neighborhood, the case of the f-shaped neighborhood, and the case of a 3 x 5 "filled" rectangular neighborhood. The techniques can be combined and generalized to solve the problem in the case of any neighborhood, centered at the tile of reference, and included in a 3 x (2k + 1) rectangle.

A Novel Quad Harmony Search Algorithm for Grid-Based Path Finding

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Saso Koceski

2014-09-01

Full Text Available A novel approach to the problem of grid-based path finding has been introduced. The method is a block-based search algorithm, founded on the bases of two algorithms, namely the quad-tree algorithm, which offered a great opportunity for decreasing the time needed to compute the solution, and the harmony search (HS algorithm, a meta-heuristic algorithm used to obtain the optimal solution. This quad HS algorithm uses the quad-tree decomposition of free space in the grid to mark the free areas and treat them as a single node, which greatly improves the execution. The results of the quad HS algorithm have been compared to other meta-heuristic algorithms, i.e., ant colony, genetic algorithm, particle swarm optimization and simulated annealing, and it was proved to obtain the best results in terms of time and giving the optimal path.

Interim Report on Heuristics about Inspection Parameters: Updates to Heuristics Resulting from Refinement on Projects

Science.gov (United States)

Shull, Forrest; Seaman, Carolyn; Feldman, Raimund; Haingaertner, Ralf; Regardie, Myrna

2008-01-01

In 2008, we have continued analyzing the inspection data in an effort to better understand the applicability and effect of the inspection heuristics on inspection outcomes. Our research goals during this period are: 1. Investigate the effect of anomalies in the dataset (e.g. the very large meeting length values for some inspections) on our results 2. Investigate the effect of the heuristics on other inspection outcome variables (e.g. effort) 3. Investigate whether the recommended ranges can be modified to give inspection planners more flexibility without sacrificing effectiveness 4. Investigate possible refinements or modifications to the heuristics for specific subdomains (partitioned, e.g., by size, domain, or Center) This memo reports our results to date towards addressing these goals. In the next section, the first goal is addressed by describing the types of anomalies we have found in our dataset, how we have addressed them, and the effect of these changes on our previously reported results. In the following section, on "methodology", we describe the analyses we have conducted to address the other three goals and the results of these analyses are described in the "results" section. Finally, we conclude with future plans for continuing our investigation.

Neighborhood and Network Disadvantage among Urban Renters

Directory of Open Access Journals (Sweden)

Matthew Desmond

2015-06-01

Full Text Available Drawing on novel survey data, this study maps the distribution of neighborhood and network disadvantage in a population of Milwaukee renters and evaluates the relationship between each disadvantage and multiple social and health outcomes. We find that many families live in neighborhoods with above average disadvantage but are embedded in networks with below average disadvantage, and vice versa. Neighborhood (but not network disadvantage is associated with lower levels of neighborly trust but also with higher levels of community support (e.g., providing neighbors with food. Network (but not neighborhood disadvantage is associated with lower levels of civic engagement. Asthma and diabetes are associated exclusively with neighborhood disadvantage, but depression is associated exclusively with network disadvantage. These findings imply that some social problems may be better addressed by neighborhood interventions and others by network interventions.

Functional Interpretation of Neighborhood Public Spaces in Terms of Identity

Directory of Open Access Journals (Sweden)

Hamid Majedi

2015-03-01

Full Text Available The aim of this article is to evaluate the effect of neighborhood public space transformation due to rapid urbanization in Tehran since 1960s, on the formation of neighborhood identity. In order to find the role of public spaces in enhancing neighborhood identities, two middle class neighborhoods with different spatial organizations are compared with each other: Nazi Abad a planned neighborhood and Mehran a typical unplanned neighborhood which developed through rapid urbanization.   Next, the effect of neighborhood public spaces on neighborhood inhabitants is evaluated from two perspectives: Perceptual dimension and social dimension. The findings indicate that planned spatial organization and various neighborhood public spaces result in stronger neighborhood identity. It enhances both perceptual dimension of neighborhood identity(place attachment and its social dimension (sense of community. In contrast unplanned spatial organization which is the typical feature of Tehran neighborhoods leads to weak neighborhood identity.

The impact of neighborhood walkability on walking: does it differ across adult life stage and does neighborhood buffer size matter?

Science.gov (United States)

Villanueva, Karen; Knuiman, Matthew; Nathan, Andrea; Giles-Corti, Billie; Christian, Hayley; Foster, Sarah; Bull, Fiona

2014-01-01

We explored the impact of neighborhood walkability on young adults, early-middle adults, middle-aged adults, and older adults' walking across different neighborhood buffers. Participants completed the Western Australian Health and Wellbeing Surveillance System Survey (2003-2009) and were allocated a neighborhood walkability score at 200m, 400m, 800m, and 1600m around their home. We found little difference in strength of associations across neighborhood size buffers for all life stages. We conclude that neighborhood walkability supports more walking regardless of adult life stage and is relevant for small (e.g., 200m) and larger (e.g., 1600m) neighborhood buffers. © 2013 The Authors. Published by Elsevier Ltd All rights reserved.

A Two-Phase Heuristic Algorithm for the Common Frequency Routing Problem with Vehicle Type Choice in the Milk Run

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Yu Lin

2015-01-01

Full Text Available High frequency and small lot size are characteristics of milk runs and are often used to implement the just-in-time (JIT strategy in logistical systems. The common frequency problem, which simultaneously involves planning of the route and frequency, has been extensively researched in milk run systems. In addition, vehicle type choice in the milk run system also has a significant influence on the operating cost. Therefore, in this paper, we simultaneously consider vehicle routing planning, frequency planning, and vehicle type choice in order to optimize the sum of the cost of transportation, inventory, and dispatch. To this end, we develop a mathematical model to describe the common frequency problem with vehicle type choice. Since the problem is NP hard, we develop a two-phase heuristic algorithm to solve the model. More specifically, an initial satisfactory solution is first generated through a greedy heuristic algorithm to maximize the ratio of the superior arc frequency to the inferior arc frequency. Following this, a tabu search (TS with limited search scope is used to improve the initial satisfactory solution. Numerical examples with different sizes establish the efficacy of our model and our proposed algorithm.

Heuristic Portfolio Trading Rules with Capital Gain Taxes

DEFF Research Database (Denmark)

Fischer, Marcel; Gallmeyer, Michael

2016-01-01

We study the out-of-sample performance of portfolio trading strategies used when an investor faces capital gain taxation and proportional transaction costs. Overlaying simple tax trading heuristics on trading strategies improves out-of-sample performance. For medium to large transaction costs......, no trading strategy can outperform a 1/N trading strategy augmented with a tax heuristic, not even the most tax and transaction cost-efficient buy-and-hold strategy. Overall, the best strategy is 1/N augmented with a heuristic that allows for a fixed deviation in absolute portfolio weights. Our results thus...... show that the best trading strategies balance diversification considerations and tax considerations....

TOUR CONSTRUCTION HEURISTICS FOR AN ORDER SEQUENCING PROBLEM

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De Villiers, A. P.

2012-11-01

Full Text Available An order picking system that requires pickers to move in a clockwise direction around a picking line with fixed locations is considered. The problem is divided into three tiers. The tier in which orders must be sequenced is addressed. Eight tour construction heuristics are developed and implemented for an order picking system operating in unidirectional picking lines. Two classes of tour construction heuristics the tour construction starting position ( and the tour construction ending position ( are developed to sequence orders in a picking line. All algorithms are tested and compared using real life data sets. The best solution quality was obtained by a heuristic with adaptations.

RELAXATION HEURISTICS FOR THE SET COVERING PROBLEM

OpenAIRE

Umetani, Shunji; Yagiura, Mutsunori; 柳浦, 睦憲

2007-01-01

The set covering problem (SCP) is one of representative combinatorial optimization problems, which has many practical applications. The continuous development of mathematical programming has derived a number of impressive heuristic algorithms as well as exact branch-and-bound algorithms, which can solve huge SCP instances of bus, railway and airline crew scheduling problems. We survey heuristic algorithms for SCP focusing mainly on contributions of mathematical programming techniques to heuri...

A heuristic forecasting model for stock decision

OpenAIRE

Zhang, D.; Jiang, Q.; Li, X.

2005-01-01

This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. ...

Relative level of occurrence of the principal heuristics in Nigeria property valuation

Directory of Open Access Journals (Sweden)

Iroham C.O.,

2013-06-01

Full Text Available The neglect of the other principal heuristics namely avaialability, representative and positivity in real estate behaviourial property research as against the exclusive focus on anchoring and adjustment heuristics invariably results to a lopsided research. This work studied the four principal heuristics in property behaviourial property valutaion in a bid to discovering its relative level of occurrence. The study adopted a cross-sectional questionnaire survey approach of 159 of the 270 Head Offices of Estate Surveying and Valuation firms in Lagos Metropolis, while 29 and 30 questionnaire were distributed to the Head Offices of the entire Estate Surveying and Valuation Firms in Abuja and Port-Harcourt respectively. The data gotten was analyzed with the aid of Statistical Package for the Social Sciences first using frequency distributions/means and the data so analyzed was further analyzed using maximum and minimum values, means/standard deviations and ultimately ranking of such means. The result revealed that respondents use the various principal heuristics in this decreasing order of magnitude: availability heuristics (26.77%, anchoring and adjustment heuristics (18.62%; representative heuristics (15.63% and least of all positivity heuristics (10.41%. The authors thereby opined that emphasis be placed more on availability heuristics research particularly as usage of heuristcis (anchoring and adjustment has been seen to influence valuation inconsistency/accuracy

Heuristics for container loading of furniture

DEFF Research Database (Denmark)

Egeblad, Jens; Garavelli, Claudio; Lisi, Stefano

2010-01-01

. In the studied company, the problem arises hundreds of times daily during transport planning. Instances may contain more than one hundred different items with irregular shapes. To solve this complex problem we apply a set of heuristics successively that each solve one part of the problem. Large items...... are combined in specific structures to ensure proper protection of the items during transportation and to simplify the problem. The solutions generated by the heuristic has an average loading utilization of 91.3% for the most general instances with average running times around 100 seconds....

Use of Statistical Heuristics in Everyday Inductive Reasoning.

Science.gov (United States)

Nisbett, Richard E.; And Others

1983-01-01

In everyday reasoning, people use statistical heuristics (judgmental tools that are rough intuitive equivalents of statistical principles). Use of statistical heuristics is more likely when (1) sampling is clear, (2) the role of chance is clear, (3) statistical reasoning is normative for the event, or (4) the subject has had training in…

Beyond rational expectations: the effects of heuristic switching in an overlapping generations model

OpenAIRE

Boone, Brecht; Quaghebeur, Ewoud

2018-01-01

We explore the transitional dynamics in an Overlapping Generations framework with and without heuristic switching. Agents use simple heuristics to forecast the interest rate and the real wage. The fraction of agents using a specific heuristic depends on its relative forecasting performance. In the absence of heuristic switching, the results indicate that there is a lot of variation in the transitional dynamics over different parameter values and heuristics. They might even oscillate or diverg...

Neighborhood Disadvantage, Neighborhood Safety and Cardiometabolic Risk Factors in African Americans: Biosocial Associations in the Jackson Heart Study

Science.gov (United States)

Clark, Cheryl R.; Ommerborn, Mark J.; Hickson, DeMarc A.; Grooms, Kya N.; Sims, Mario; Taylor, Herman A.; Albert, Michelle A.

2013-01-01

Objective We examined associations between neighborhood socioeconomic disadvantage, perceived neighborhood safety and cardiometabolic risk factors, adjusting for health behaviors and socioeconomic status (SES) among African Americans. Methods Study participants were non-diabetic African Americans (n = 3,909) in the baseline examination (2000–2004) of the Jackson Heart Study. We measured eight risk factors: the metabolic syndrome, its five components, insulin resistance and cardiovascular inflammation. We assessed neighborhood socioeconomic disadvantage with US Census 2000 data. We assessed perceived neighborhood safety, health behaviors and SES via survey. We used generalized estimating equations to estimate associations with a random intercept model for neighborhood effects. Results After adjustment for health behaviors and SES, neighborhood socioeconomic disadvantage was associated with the metabolic syndrome in women (PR 1.13, 95% CI 1.01, 1.27). Lack of perceived safety was associated with elevated glucose (OR 1.36, 95% CI 1.03, 1.80) and waist circumference (PR 1.06, 95% CI 1.02, 1.11) among women, and with elevated glucose (PR 1.30, 95% CI 1.02, 1.66) and insulin resistance (PR 1.25, 95% CI 1.08, 1.46) among men. Conclusions Neighborhood socioeconomic disadvantage and perceived safety should be considered as targets for intervention to reduce cardiometabolic risks among African Americans. PMID:23691005

Modified strip packing heuristics for the rectangular variable-sized bin packing problem

Directory of Open Access Journals (Sweden)

FG Ortmann

2010-06-01

Full Text Available Two packing problems are considered in this paper, namely the well-known strip packing problem (SPP and the variable-sized bin packing problem (VSBPP. A total of 252 strip packing heuristics (and variations thereof from the literature, as well as novel heuristics proposed by the authors, are compared statistically by means of 1170 SPP benchmark instances in order to identify the best heuristics in various classes. A combination of new heuristics with a new sorting method yields the best results. These heuristics are combined with a previous heuristic for the VSBPP by the authors to find good feasible solutions to 1357 VSBPP benchmark instances. This is the largest statistical comparison of algorithms for the SPP and the VSBPP to the best knowledge of the authors.

Developing heuristics for Web communication: an introduction to this special issue

NARCIS (Netherlands)

van der Geest, Thea; Spyridakis, Jan H.

2000-01-01

This article describes the role of heuristics in the Web design process. The five sets of heuristics that appear in this issue are also described, as well as the research methods used in their development. The heuristics were designed to help designers and developers of Web pages or sites to

WWER core pattern enhancement using adaptive improved harmony search

International Nuclear Information System (INIS)

Nazari, T.; Aghaie, M.; Zolfaghari, A.; Minuchehr, A.; Norouzi, A.

2013-01-01

Highlights: ► The classical and improved harmony search algorithms are introduced. ► The advantage of IHS is demonstrated in Shekel's Foxholes. ► The CHS and IHS are compared with other Heuristic algorithms. ► The adaptive improved harmony search is applied for two cases. ► Two cases of WWER core are optimized in BOC FA pattern. - Abstract: The efficient operation and fuel management of PWRs are of utmost importance. Core performance analysis constitutes an essential phase in core fuel management optimization. Finding an optimum core arrangement for loading of fuel assemblies, FAs, in a nuclear core is a complex problem. In this paper, application of classical harmony search (HS) and adaptive improved harmony search (IHS) in loading pattern (LP) design, for pressurized water reactors, is described. In this analysis, finding the best core pattern, which attains maximum multiplication factor, k eff , by considering maximum allowable power picking factors (PPF) is the main objective. Therefore a HS based, LP optimization code is prepared and CITATION code which is a neutronic calculation code, applied to obtain effective multiplication factor, neutron fluxes and power density in desired cores. Using adaptive improved harmony search and neutronic code, generated LP optimization code, could be applicable for PWRs core with many numbers of FAs. In this work, at first step, HS and IHS efficiencies are compared with some other heuristic algorithms in Shekel's Foxholes problem and capability of the adaptive improved harmony search is demonstrated. Results show, efficient application of IHS. At second step, two WWER cases are studied and then IHS proffered improved core patterns with regard to mentioned objective functions.

Knowlegde treasure in maré neighborhood: people as information sources

Directory of Open Access Journals (Sweden)

Anderson Morais Chalaça

2007-12-01

Full Text Available This work is a presentation of research results in an exploratory level as a graduation monograph. The aim of the work was to approach people common citizens as information fonts related to determined community in the perspective of the social responsibility of the librarian professional. The research environment dealt was the Maré neighborhood and its communities. The methodology used was research-action in order to create a research staff to investigate the existence of these people and their actions as information fonts in the community. The work also aimed to make the “invisible” more visible, identifying where and how search, recall ad information use is done through people that gather knowledge in a referred community. Thus a structures interview technique was used to register the information fonts´ knowledge, their occupations and talents; making the revelation of how the knowledge was acquired as well as its transmission to other people. The interview was Transcripted and edited being designed into a virtual format in a site that contais the knowlegde Treasure in Maré Neighborhood.

On the Importance of Elimination Heuristics in Lazy Propagation

DEFF Research Database (Denmark)

Madsen, Anders Læsø; Butz, Cory J.

2012-01-01

elimination orders on-line. This paper considers the importance of elimination heuristics in LP when using Variable Elimination (VE) as the message and single marginal computation algorithm. It considers well-known cost measures for selecting the next variable to eliminate and a new cost measure....... The empirical evaluation examines dierent heuristics as well as sequences of cost measures, and was conducted on real-world and randomly generated Bayesian networks. The results show that for most cases performance is robust relative to the cost measure used and in some cases the elimination heuristic can have...

A meta-heuristic cuckoo search and eigen permutation approach for ...

Indian Academy of Sciences (India)

Akhilesh Kumar Gupta

2018-04-17

Apr 17, 2018 ... system (HOS) into a simplified lower order model of rea- sonable accuracy by ..... dom walk whose flight step length is dependent on a power law formula often ..... In: IEEE International Conference on Electric. Power and Energy ... hybrid cuckoo search and genetic algorithm for reliability– redundancy ...

A database of linear codes over F_13 with minimum distance bounds and new quasi-twisted codes from a heuristic search algorithm

Directory of Open Access Journals (Sweden)

Eric Z. Chen

2015-01-01

Full Text Available Error control codes have been widely used in data communications and storage systems. One central problem in coding theory is to optimize the parameters of a linear code and construct codes with best possible parameters. There are tables of best-known linear codes over finite fields of sizes up to 9. Recently, there has been a growing interest in codes over $\\mathbb{F}_{13}$ and other fields of size greater than 9. The main purpose of this work is to present a database of best-known linear codes over the field $\\mathbb{F}_{13}$ together with upper bounds on the minimum distances. To find good linear codes to establish lower bounds on minimum distances, an iterative heuristic computer search algorithm is employed to construct quasi-twisted (QT codes over the field $\\mathbb{F}_{13}$ with high minimum distances. A large number of new linear codes have been found, improving previously best-known results. Tables of $[pm, m]$ QT codes over $\\mathbb{F}_{13}$ with best-known minimum distances as well as a table of lower and upper bounds on the minimum distances for linear codes of length up to 150 and dimension up to 6 are presented.

Heuristics guide cooperative behaviors in public goods game

Science.gov (United States)

Wang, Yongjie; Chen, Tong

2015-12-01

In public goods game (PGG), player's cooperative behavior is not pure economical rationality, but social preference and prosocial intuition play extremely important roles as well. Social preference and prosocial intuition can be guided by heuristics from one's neighbors in daily life. To better investigate the impacts of heuristics on the evolution of cooperation, four types of agents are introduced into our spatial PGG. Through numerical simulations, results show that the larger percentages of cooperators with independent thought, the easier emergence and maintenance of collective cooperative behaviors. Additionally, we find that differentia heuristic capability has great effect on the equilibrium of PGG. Cooperation can be obviously promoted, when heuristic capability of cooperators with independent thought is stronger than that of defectors with independent thought. Finally, we observe that cooperators with independent thought and defectors with independent thought are favorable for the formation of some high quality clusters, which can resist the invasion between each other. Our work may help us understand more clearly the mechanism of cooperation in real world.

Investigating the Impacts of Design Heuristics on Idea Initiation and Development

Science.gov (United States)

Kramer, Julia; Daly, Shanna R.; Yilmaz, Seda; Seifert, Colleen M.; Gonzalez, Richard

2015-01-01

This paper presents an analysis of engineering students' use of Design Heuristics as part of a team project in an undergraduate engineering design course. Design Heuristics are an empirically derived set of cognitive "rules of thumb" for use in concept generation. We investigated heuristic use in the initial concept generation phase,…

Fast or Frugal, but Not Both: Decision Heuristics under Time Pressure

Science.gov (United States)

Bobadilla-Suarez, Sebastian; Love, Bradley C.

2018-01-01

Heuristics are simple, yet effective, strategies that people use to make decisions. Because heuristics do not require all available information, they are thought to be easy to implement and to not tax limited cognitive resources, which has led heuristics to be characterized as fast-and-frugal. We question this monolithic conception of heuristics…

Heuristic versus statistical physics approach to optimization problems

International Nuclear Information System (INIS)

Jedrzejek, C.; Cieplinski, L.

1995-01-01

Optimization is a crucial ingredient of many calculation schemes in science and engineering. In this paper we assess several classes of methods: heuristic algorithms, methods directly relying on statistical physics such as the mean-field method and simulated annealing; and Hopfield-type neural networks and genetic algorithms partly related to statistical physics. We perform the analysis for three types of problems: (1) the Travelling Salesman Problem, (2) vector quantization, and (3) traffic control problem in multistage interconnection network. In general, heuristic algorithms perform better (except for genetic algorithms) and much faster but have to be specific for every problem. The key to improving the performance could be to include heuristic features into general purpose statistical physics methods. (author)

Arational heuristic model of economic decision making

OpenAIRE

Grandori, Anna

2010-01-01

The article discuss the limits of both the rational actor and the behavioral paradigms in explaining and guiding innovative decision making and outlines a model of economic decision making that in the course of being 'heuristic' (research and discovery oriented) is also 'rational' (in the broad sense of following correct reasoning and scientific methods, non 'biasing'). The model specifies a set of 'rational heuristics' for innovative decision making, for the various sub-processes of problem ...

The affect heuristic in occupational safety.

Science.gov (United States)

Savadori, Lucia; Caovilla, Jessica; Zaniboni, Sara; Fraccaroli, Franco

2015-07-08

The affect heuristic is a rule of thumb according to which, in the process of making a judgment or decision, people use affect as a cue. If a stimulus elicits positive affect then risks associated to that stimulus are viewed as low and benefits as high; conversely, if the stimulus elicits negative affect, then risks are perceived as high and benefits as low. The basic tenet of this study is that affect heuristic guides worker's judgment and decision making in a risk situation. The more the worker likes her/his organization the less she/he will perceive the risks as high. A sample of 115 employers and 65 employees working in small family agricultural businesses completed a questionnaire measuring perceived safety costs, psychological safety climate, affective commitment and safety compliance. A multi-sample structural analysis supported the thesis that safety compliance can be explained through an affect-based heuristic reasoning, but only for employers. Positive affective commitment towards their family business reduced employers' compliance with safety procedures by increasing the perceived cost of implementing them.

When decision heuristics and science collide.

Science.gov (United States)

Yu, Erica C; Sprenger, Amber M; Thomas, Rick P; Dougherty, Michael R

2014-04-01

The ongoing discussion among scientists about null-hypothesis significance testing and Bayesian data analysis has led to speculation about the practices and consequences of "researcher degrees of freedom." This article advances this debate by asking the broader questions that we, as scientists, should be asking: How do scientists make decisions in the course of doing research, and what is the impact of these decisions on scientific conclusions? We asked practicing scientists to collect data in a simulated research environment, and our findings show that some scientists use data collection heuristics that deviate from prescribed methodology. Monte Carlo simulations show that data collection heuristics based on p values lead to biases in estimated effect sizes and Bayes factors and to increases in both false-positive and false-negative rates, depending on the specific heuristic. We also show that using Bayesian data collection methods does not eliminate these biases. Thus, our study highlights the little appreciated fact that the process of doing science is a behavioral endeavor that can bias statistical description and inference in a manner that transcends adherence to any particular statistical framework.

Swift and Smart Decision Making: Heuristics that Work

Science.gov (United States)

Hoy, Wayne K.; Tarter, C. J.

2010-01-01

Purpose: The aim of this paper is to examine the research literature on decision making and identify and develop a set of heuristics that work for school decision makers. Design/methodology/approach: This analysis is a synthesis of the research on decision-making heuristics that work. Findings: A set of nine rules for swift and smart decision…

Evaluation Framework for Search Instruments

International Nuclear Information System (INIS)

Warren, Glen A.; Smith, Leon E.; Cooper, Matt W.; Kaye, William R.

2005-01-01

A framework for quantitatively evaluating current and proposed gamma-ray search instrument designs has been developed. The framework is designed to generate a large library of ''virtual neighborhoods'' that can be used to test and evaluate nearly any gamma-ray sensor type. Calculating nuisance-source emissions and combining various sources to create a large number of random virtual scenes places a significant computational burden on the development of the framework. To reduce this burden, a number of radiation transport simplifications have been made which maintain the essential physics ingredients for the quantitative assessment of search instruments while significantly reducing computational times. The various components of the framework, from the simulation and benchmarking of nuisance source emissions to the computational engine for generating the gigabytes of simulated search scenes, are discussed

Inhibitory mechanism of the matching heuristic in syllogistic reasoning.

Science.gov (United States)

Tse, Ping Ping; Moreno Ríos, Sergio; García-Madruga, Juan Antonio; Bajo Molina, María Teresa

2014-11-01

A number of heuristic-based hypotheses have been proposed to explain how people solve syllogisms with automatic processes. In particular, the matching heuristic employs the congruency of the quantifiers in a syllogism—by matching the quantifier of the conclusion with those of the two premises. When the heuristic leads to an invalid conclusion, successful solving of these conflict problems requires the inhibition of automatic heuristic processing. Accordingly, if the automatic processing were based on processing the set of quantifiers, no semantic contents would be inhibited. The mental model theory, however, suggests that people reason using mental models, which always involves semantic processing. Therefore, whatever inhibition occurs in the processing implies the inhibition of the semantic contents. We manipulated the validity of the syllogism and the congruency of the quantifier of its conclusion with those of the two premises according to the matching heuristic. A subsequent lexical decision task (LDT) with related words in the conclusion was used to test any inhibition of the semantic contents after each syllogistic evaluation trial. In the LDT, the facilitation effect of semantic priming diminished after correctly solved conflict syllogisms (match-invalid or mismatch-valid), but was intact after no-conflict syllogisms. The results suggest the involvement of an inhibitory mechanism of semantic contents in syllogistic reasoning when there is a conflict between the output of the syntactic heuristic and actual validity. Our results do not support a uniquely syntactic process of syllogistic reasoning but fit with the predictions based on mental model theory. Copyright © 2014 Elsevier B.V. All rights reserved.

Psychology into economics: fast and frugal heuristics

OpenAIRE

Schilirò, Daniele

2015-01-01

The present essay focuses on the fast and frugal heuristics program set forth by Gerd Gigerenzer and his fellows. In particular it examines the contribution of Gigerenzer and Goldstein (1996) ‘Reasoning the Fast and Frugal Way: Models of Bounded Rationality’. This essay, following the theoretical propositions and the empirical evidence of Gigerenzer and Goldstein, points out that simple cognitive mechanisms such as fast and frugal heuristics can be capable of successful performance in real wo...

Efficient Heuristics for Simulating Population Overflow in Parallel Networks

NARCIS (Netherlands)

Zaburnenko, T.S.; Nicola, V.F.

2006-01-01

In this paper we propose a state-dependent importance sampling heuristic to estimate the probability of population overflow in networks of parallel queues. This heuristic approximates the “optimal��? state-dependent change of measure without the need for costly optimization involved in other

Neighborhood Poverty and Adolescent Development

Science.gov (United States)

McBride Murry, Velma; Berkel, Cady; Gaylord-Harden, Noni K.; Copeland-Linder, Nikeea; Nation, Maury

2011-01-01

This article provides a comprehensive review of studies conducted over the past decade on the effects of neighborhood and poverty on adolescent normative and nonnormative development. Our review includes a summary of studies examining the associations between neighborhood poverty and adolescent identity development followed by a review of studies…

Hyperspectral band selection based on consistency-measure of neighborhood rough set theory

International Nuclear Information System (INIS)

Liu, Yao; Xie, Hong; Wang, Liguo; Tan, Kezhu; Chen, Yuehua; Xu, Zhen

2016-01-01

Band selection is a well-known approach for reducing dimensionality in hyperspectral imaging. In this paper, a band selection method based on consistency-measure of neighborhood rough set theory (CMNRS) was proposed to select informative bands from hyperspectral images. A decision-making information system was established by the reflection spectrum of soybeans’ hyperspectral data between 400 nm and 1000 nm wavelengths. The neighborhood consistency-measure, which reflects not only the size of the decision positive region, but also the sample distribution in the boundary region, was used as the evaluation function of band significance. The optimal band subset was selected by a forward greedy search algorithm. A post-pruning strategy was employed to overcome the over-fitting problem and find the minimum subset. To assess the effectiveness of the proposed band selection technique, two classification models (extreme learning machine (ELM) and random forests (RF)) were built. The experimental results showed that the proposed algorithm can effectively select key bands and obtain satisfactory classification accuracy. (paper)

Strategies of Building a Stronger Sense of Community for Sustainable Neighborhoods: Comparing Neighborhood Accessibility with Community Empowerment Programs

Directory of Open Access Journals (Sweden)

Te-I Albert Tsai

2014-05-01

Full Text Available New Urbanist development in the U.S. aims at enhancing a sense of community and seeks to return to the design of early transitional neighborhoods which have pedestrian-oriented environments with retail shops and services within walking distances of housing. Meanwhile, 6000 of Taiwan’s community associations have been running community empowerment programs supported by the Council for Cultural Affairs that have helped many neighborhoods to rebuild so-called community cohesion. This research attempts to evaluate whether neighborhoods with facilities near housing and shorter travel distances within a neighborhood would promote stronger social interactions and form a better community attachment than neighborhoods that have various opportunities for residents to participate in either formal or informal social gatherings. After interviewing and surveying residents from 19 neighborhoods in Taipei’s Beitou District, and correlating the psychological sense of community with inner neighborhood’s daily travel distances and numbers of participatory activities held by community organizations under empowerment programs together with frequencies of regular individual visits and casual meetings, statistical evidence yielded that placing public facilities near residential locations is more effective than providing various programs for elevating a sense of community.

Algorithms for Academic Search and Recommendation Systems

DEFF Research Database (Denmark)

Amolochitis, Emmanouil

2014-01-01

are part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. In the third part of the work we present the design of a quantitative association rule mining algorithm. The introduced mining algorithm processes......In this work we present novel algorithms for academic search, recommendation and association rules mining. In the first part of the work we introduce a novel hierarchical heuristic scheme for re-ranking academic publications. The scheme is based on the hierarchical combination of a custom...... implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. On the second part we describe the design of hybrid recommender ensemble (user, item and content based). The newly introduced algorithms...

On Dual Processing and Heuristic Approaches to Moral Cognition

Science.gov (United States)

Lapsley, Daniel K.; Hill, Patrick L.

2008-01-01

We examine the implications of dual-processing theories of cognition for the moral domain, with particular emphasis upon "System 1" theories: the Social Intuitionist Model (Haidt), moral heuristics (Sunstein), fast-and-frugal moral heuristics (Gigerenzer), schema accessibility (Lapsley & Narvaez) and moral expertise (Narvaez). We argue that these…

Neighborhood crime and transit station access mode choice - phase III of neighborhood crime and travel behavior.

Science.gov (United States)

2015-08-01

This report provides the findings from the third phase of a three-part study about the influences of neighborhood crimes on travel : mode choice. While previous phases found evidence that high levels of neighborhood crime discourage people from choos...

Heuristic introduction to gravitational waves

International Nuclear Information System (INIS)

Sandberg, V.D.

1982-01-01

The purpose of this article is to provide a rough and somewhat heuristic theoretical background and introduction to gravitational radiation, its generation, and its detection based on Einstein's general theory of relativity

In search of a consumer-focused food classification system. An experimental heuristic approach to differentiate degrees of quality.

Science.gov (United States)

Torres-Ruiz, Francisco J; Marano-Marcolini, Carla; Lopez-Zafra, Esther

2018-06-01

The present paper focuses on the problems that arise in food classification systems (FCSs), especially when the food product type has different levels or grades of quality. Despite the principal function of these systems being to assist the consumer (to inform, clarify and facilitate choice and purchase), they frequently have the opposite effect. Thus, the main aim of the present research involves providing orientations for the design of effective food classification systems. To address this objective, considering the context of food product consumption (related to heuristic processing), we conducted an experimental study with 720 participants. We analysed the usefulness of heuristic elements by a factorial 2 (category length: short and long) × 3 (visual signs: colours, numbers and images) design in relation to recall and recognition activities. The results showed that the elements used to make the classification more effective for consumers vary depending on whether the user seeks to prioritize the recall or the recognition of product categories. Thus, long categories with images significantly improve recognition, and short categories with colours improve recall. A series of recommendations are provided that can help to enhance FCSs and to make them more intuitive and easier to understand for consumers. Implications with regard to theory and practice are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evaluating Heuristics for Planning Effective and Efficient Inspections

Science.gov (United States)

Shull, Forrest J.; Seaman, Carolyn B.; Diep, Madeline M.; Feldmann, Raimund L.; Godfrey, Sara H.; Regardie, Myrna

2010-01-01

A significant body of knowledge concerning software inspection practice indicates that the value of inspections varies widely both within and across organizations. Inspection effectiveness and efficiency can be measured in numerous ways, and may be affected by a variety of factors such as Inspection planning, the type of software, the developing organization, and many others. In the early 1990's, NASA formulated heuristics for inspection planning based on best practices and early NASA inspection data. Over the intervening years, the body of data from NASA inspections has grown. This paper describes a multi-faceted exploratory analysis performed on this · data to elicit lessons learned in general about conducting inspections and to recommend improvements to the existing heuristics. The contributions of our results include support for modifying some of the original inspection heuristics (e.g. Increasing the recommended page rate), evidence that Inspection planners must choose between efficiency and effectiveness, as a good tradeoff between them may not exist, and Identification of small subsets of inspections for which new inspection heuristics are needed. Most Importantly, this work illustrates the value of collecting rich data on software Inspections, and using it to gain insight into, and Improve, inspection practice.

Analytic and heuristic processes in the detection and resolution of conflict.

Science.gov (United States)

Ferreira, Mário B; Mata, André; Donkin, Christopher; Sherman, Steven J; Ihmels, Max

2016-10-01

Previous research with the ratio-bias task found larger response latencies for conflict trials where the heuristic- and analytic-based responses are assumed to be in opposition (e.g., choosing between 1/10 and 9/100 ratios of success) when compared to no-conflict trials where both processes converge on the same response (e.g., choosing between 1/10 and 11/100). This pattern is consistent with parallel dual-process models, which assume that there is effective, rather than lax, monitoring of the output of heuristic processing. It is, however, unclear why conflict resolution sometimes fails. Ratio-biased choices may increase because of a decline in analytical reasoning (leaving heuristic-based responses unopposed) or to a rise in heuristic processing (making it more difficult for analytic processes to override the heuristic preferences). Using the process-dissociation procedure, we found that instructions to respond logically and response speed affected analytic (controlled) processing (C), leaving heuristic processing (H) unchanged, whereas the intuitive preference for large nominators (as assessed by responses to equal ratio trials) affected H but not C. These findings create new challenges to the debate between dual-process and single-process accounts, which are discussed.

Heuristic thinking and human intelligence: a commentary on Marewski, Gaissmaier and Gigerenzer.

Science.gov (United States)

Evans, Jonathan St B T; Over, David E

2010-05-01

Marewski, Gaissmaier and Gigerenzer (2009) present a review of research on fast and frugal heuristics, arguing that complex problems are best solved by simple heuristics, rather than the application of knowledge and logical reasoning. We argue that the case for such heuristics is overrated. First, we point out that heuristics can often lead to biases as well as effective responding. Second, we show that the application of logical reasoning can be both necessary and relatively simple. Finally, we argue that the evidence for a logical reasoning system that co-exists with simpler heuristic forms of thinking is overwhelming. Not only is it implausible a priori that we would have evolved such a system that is of no use to us, but extensive evidence from the literature on dual processing in reasoning and judgement shows that many problems can only be solved when this form of reasoning is used to inhibit and override heuristic thinking.

Defensible Spaces in Philadelphia: Exploring Neighborhood Boundaries Through Spatial Analysis

Directory of Open Access Journals (Sweden)

Rory Kramer

2017-02-01

Full Text Available Few spatial scales are as important to individual outcomes as the neighborhood. However, it is nearly impossible to define neighborhoods in a generalizable way. This article proposes that by shifting the focus to measuring neighborhood boundaries rather than neighborhoods, scholars can avoid the problem of the indefinable neighborhood and better approach questions of what predicts racial segregation across areas. By quantifying an externality space theory of neighborhood boundaries, this article introduces a novel form of spatial analysis to test where potential physical markers of neighborhood boundaries (major roads, rivers, railroads, and the like are associated with persistent racial boundaries between 1990 and 2010. Using Philadelphia as a case study, the paper identifies neighborhoods with persistent racial boundaries. It theorizes that local histories of white reactions to black in-migration explain which boundaries persistently resisted racial turnover, unlike the majority of Philadelphia’s neighborhoods, and that those racial boundaries shape the location, progress, and reaction to new residential development in those neighborhoods.

Heuristic and algorithmic processing in English, mathematics, and science education.

Science.gov (United States)

Sharps, Matthew J; Hess, Adam B; Price-Sharps, Jana L; Teh, Jane

2008-01-01

Many college students experience difficulties in basic academic skills. Recent research suggests that much of this difficulty may lie in heuristic competency--the ability to use and successfully manage general cognitive strategies. In the present study, the authors evaluated this possibility. They compared participants' performance on a practice California Basic Educational Skills Test and on a series of questions in the natural sciences with heuristic and algorithmic performance on a series of mathematics and reading comprehension exercises. Heuristic competency in mathematics was associated with better scores in science and mathematics. Verbal and algorithmic skills were associated with better reading comprehension. These results indicate the importance of including heuristic training in educational contexts and highlight the importance of a relatively domain-specific approach to questions of cognition in higher education.

The rationality of intuition: Studying adaptive heuristics in project decision-making

DEFF Research Database (Denmark)

Stingl, Verena; Geraldi, Joana

This paper presents a research agenda for studying adaptive heuristics in project decision making. Project decisions are a potentially fruitful research field for adaptive heuristics. These decisions typically take place under time and information constraints, with high complexity and ambiguity...... - environments in which adaptive heuristics typically strive as effective decision tools. Yet, project decisions as a research topic introduce challenges that are currently not considered in the main body of adaptive heuristics research: the issue of group decision making, and the element of an unpredictable...... the limitations of these methods for project decision-making, and suggests alternative methodologies, suitable to cope with group decision-making and irreducible uncertainty....

Fairness and other leadership heuristics: A four-nation study

NARCIS (Netherlands)

Janson, A.; Levy, L.; Sitkin, S.B.; Lind, E.A.

2008-01-01

Leaders' fairness may be just one of several heuristics - cognitive shortcuts - that followers use to decide quickly whether they can rely on a given leader to lead them to ends that are good for the collective, rather than just good for the leader. Other leadership heuristics might include leader

Neighborhood Economic Enterprises: An Analysis, Survey, and Guide to Resources in Starting Up Neighborhood Enterprises.

Science.gov (United States)

Kotler, Neil G.

This pamphlet provides information on the history of and current trends toward neighborhood economic enterprises and provides guidance for setting up such enterprises. A bibliography of books, articles, and newsletters that have information on how to start and sustain neighborhood businesses and cooperatives is provided. Also included is a list of…

Neighborhood Disparities in the Restaurant Food Environment.

Science.gov (United States)

Martinez-Donate, Ana P; Espino, Jennifer Valdivia; Meinen, Amy; Escaron, Anne L; Roubal, Anne; Nieto, Javier; Malecki, Kristen

2016-11-01

Restaurant meals account for a significant portion of the American diet. Investigating disparities in the restaurant food environment can inform targeted interventions to increase opportunities for healthy eating among those who need them most. To examine neighborhood disparities in restaurant density and the nutrition environment within restaurants among a statewide sample of Wisconsin households. Households (N = 259) were selected from the 2009-2010 Survey of the Health of Wisconsin (SHOW), a population-based survey of Wisconsin adults. Restaurants in the household neighborhood were enumerated and audited using the Nutrition Environment Measures Survey for Restaurants (NEMS-R). Neighborhoods were defined as a 2- and 5-mile street-distance buffer around households in urban and non-urban areas, respectively. Adjusted linear regression models identified independent associations between sociodemographic household characteristics and neighborhood restaurant density and nutrition environment scores. On average, each neighborhood contained approximately 26 restaurants. On average, restaurants obtained 36.1% of the total nutrition environment points. After adjusting for household characteristics, higher restaurant density was associated with both younger and older household average age (P restaurant food environment in Wisconsin neighborhoods varies by age, race, and urbanicity, but offers ample room for improvement across socioeconomic groups and urbanicity levels. Future research must identify policy and environmental interventions to promote healthy eating in all restaurants, especially in young and/or rural neighborhoods in Wisconsin.

Visualization for Hyper-Heuristics: Back-End Processing

Energy Technology Data Exchange (ETDEWEB)

Simon, Luke [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-03-01

Modern society is faced with increasingly complex problems, many of which can be formulated as generate-and-test optimization problems. Yet, general-purpose optimization algorithms may sometimes require too much computational time. In these instances, hyperheuristics may be used. Hyper-heuristics automate the design of algorithms to create a custom algorithm for a particular scenario, finding the solution significantly faster than its predecessor. However, it may be difficult to understand exactly how a design was derived and why it should be trusted. This project aims to address these issues by creating an easy-to-use graphical user interface (GUI) for hyper-heuristics and an easy-to-understand scientific visualization for the produced solutions. To support the development of this GUI, my portion of the research involved developing algorithms that would allow for parsing of the data produced by the hyper-heuristics. This data would then be sent to the front-end, where it would be displayed to the end user.

WWER core pattern enhancement using adaptive improved harmony search

Energy Technology Data Exchange (ETDEWEB)

Nazari, T. [Nuclear Engineering Department, Shahid Beheshti University, G.C., P.O. Box 1983963113, Tehran (Iran, Islamic Republic of); Aghaie, M., E-mail: M_Aghaie@sbu.ac.ir [Nuclear Engineering Department, Shahid Beheshti University, G.C., P.O. Box 1983963113, Tehran (Iran, Islamic Republic of); Zolfaghari, A.; Minuchehr, A.; Norouzi, A. [Nuclear Engineering Department, Shahid Beheshti University, G.C., P.O. Box 1983963113, Tehran (Iran, Islamic Republic of)

2013-01-15

Highlights: Black-Right-Pointing-Pointer The classical and improved harmony search algorithms are introduced. Black-Right-Pointing-Pointer The advantage of IHS is demonstrated in Shekel's Foxholes. Black-Right-Pointing-Pointer The CHS and IHS are compared with other Heuristic algorithms. Black-Right-Pointing-Pointer The adaptive improved harmony search is applied for two cases. Black-Right-Pointing-Pointer Two cases of WWER core are optimized in BOC FA pattern. - Abstract: The efficient operation and fuel management of PWRs are of utmost importance. Core performance analysis constitutes an essential phase in core fuel management optimization. Finding an optimum core arrangement for loading of fuel assemblies, FAs, in a nuclear core is a complex problem. In this paper, application of classical harmony search (HS) and adaptive improved harmony search (IHS) in loading pattern (LP) design, for pressurized water reactors, is described. In this analysis, finding the best core pattern, which attains maximum multiplication factor, k{sub eff}, by considering maximum allowable power picking factors (PPF) is the main objective. Therefore a HS based, LP optimization code is prepared and CITATION code which is a neutronic calculation code, applied to obtain effective multiplication factor, neutron fluxes and power density in desired cores. Using adaptive improved harmony search and neutronic code, generated LP optimization code, could be applicable for PWRs core with many numbers of FAs. In this work, at first step, HS and IHS efficiencies are compared with some other heuristic algorithms in Shekel's Foxholes problem and capability of the adaptive improved harmony search is demonstrated. Results show, efficient application of IHS. At second step, two WWER cases are studied and then IHS proffered improved core patterns with regard to mentioned objective functions.

Mining chemical reactions using neighborhood behavior and condensed graphs of reactions approaches.

Science.gov (United States)

de Luca, Aurélie; Horvath, Dragos; Marcou, Gilles; Solov'ev, Vitaly; Varnek, Alexandre

2012-09-24

This work addresses the problem of similarity search and classification of chemical reactions using Neighborhood Behavior (NB) and Condensed Graphs of Reaction (CGR) approaches. The CGR formalism represents chemical reactions as a classical molecular graph with dynamic bonds, enabling descriptor calculations on this graph. Different types of the ISIDA fragment descriptors generated for CGRs in combination with two metrics--Tanimoto and Euclidean--were considered as chemical spaces, to serve for reaction dissimilarity scoring. The NB method has been used to select an optimal combination of descriptors which distinguish different types of chemical reactions in a database containing 8544 reactions of 9 classes. Relevance of NB analysis has been validated in generic (multiclass) similarity search and in clustering with Self-Organizing Maps (SOM). NB-compliant sets of descriptors were shown to display enhanced mapping propensities, allowing the construction of better Self-Organizing Maps and similarity searches (NB and classical similarity search criteria--AUC ROC--correlate at a level of 0.7). The analysis of the SOM clusters proved chemically meaningful CGR substructures representing specific reaction signatures.

Space, race, and poverty: Spatial inequalities in walkable neighborhood amenities?

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John Whalen

2012-05-01

Full Text Available BACKGROUND Multiple and varied benefits have been suggested for increased neighborhood walkability. However, spatial inequalities in neighborhood walkability likely exist and may be attributable, in part, to residential segregation. OBJECTIVE Utilizing a spatial demographic perspective, we evaluated potential spatial inequalities in walkable neighborhood amenities across census tracts in Boston, MA (US. METHODS The independent variables included minority racial/ethnic population percentages and percent of families in poverty. Walkable neighborhood amenities were assessed with a composite measure. Spatial autocorrelation in key study variables were first calculated with the Global Moran's I statistic. Then, Spearman correlations between neighborhood socio-demographic characteristics and walkable neighborhood amenities were calculated as well as Spearman correlations accounting for spatial autocorrelation. We fit ordinary least squares (OLS regression and spatial autoregressive models when appropriate as a final step. RESULTS Significant positive spatial autocorrelation was found in neighborhood socio-demographic characteristics (e.g. census tract percent Black, but not walkable neighborhood amenities or in the OLS regression residuals. Spearman correlations between neighborhood socio-demographic characteristics and walkable neighborhood amenities were not statistically significant, nor were neighborhood socio-demographic characteristics significantly associated with walkable neighborhood amenities in OLS regression models. CONCLUSIONS Our results suggest that there is residential segregation in Boston and that spatial inequalities do not necessarily show up using a composite measure. COMMENTS Future research in other geographic areas (including international contexts and using different definitions of neighborhoods (including small-area definitions should evaluate if spatial inequalities are found using composite measures, but also should

A Priori Knowledge and Heuristic Reasoning in Architectural Design.

Science.gov (United States)

Rowe, Peter G.

1982-01-01

It is proposed that the various classes of a priori knowledge incorporated in heuristic reasoning processes exert a strong influence over architectural design activity. Some design problems require exercise of some provisional set of rules, inference, or plausible strategy which requires heuristic reasoning. A case study illustrates this concept.…

A review of neighborhood effects and early child development: How, where, and for whom, do neighborhoods matter?

Science.gov (United States)

Minh, Anita; Muhajarine, Nazeem; Janus, Magdalena; Brownell, Marni; Guhn, Martin

2017-07-01

This paper describes a scoping review of 42 studies of neighborhood effects on developmental health for children ages 0-6, published between 2009 and 2014. It focuses on three themes: (1) theoretical mechanisms that drive early childhood development, i.e. how neighborhoods matter for early childhood development; (2) dependence of such mechanisms on place-based characteristics i.e. where neighborhood effects occur; (3) dependence of such mechanisms on child characteristics, i.e. for whom is development most affected. Given that ecological systems theories postulate diverse mechanisms via which neighborhood characteristics affect early child development, we specifically examine evidence on mediation and/or moderation effects. We conclude by discussing future challenges, and proposing recommendations for analyses that utilize ecological longitudinal population-based databases. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Heuristic extension of the Schwarzschild metric

International Nuclear Information System (INIS)

Espinosa, J.M.

1982-01-01

The Schwarzschild solution of Einstein's equations of gravitation has several singularities. It is known that the singularity at r = 2Gm/c 2 is only apparent, a result of the coordinates in which the solution was found. Paradoxical results occuring near the singularity show the system of coordinates is incomplete. We introduce a simple, two-dimensional metric with an apparent singularity that makes it incomplete. By a straightforward, heuristic procedure we extend and complete this simple metric. We then use the same procedure to give a heuristic derivation of the Kruskal system of coordinates, which is known to extend the Schwarzschild manifold past its apparent singularity and produce a complete manifold

A Comparison between Different Meta-Heuristic Techniques in Power Allocation for Physical Layer Security

Directory of Open Access Journals (Sweden)

N. Okati

2017-12-01

Full Text Available Node cooperation can protect wireless networks from eavesdropping by using the physical characteristics of wireless channels rather than cryptographic methods. Allocating the proper amount of power to cooperative nodes is a challenging task. In this paper, we use three cooperative nodes, one as relay to increase throughput at the destination and two friendly jammers to degrade eavesdropper’s link. For this scenario, the secrecy rate function is a non-linear non-convex problem. So, in this case, exact optimization methods can only achieve suboptimal solution. In this paper, we applied different meta-heuristic optimization techniques, like Genetic Algorithm (GA, Partial Swarm Optimization (PSO, Bee Algorithm (BA, Tabu Search (TS, Simulated Annealing (SA and Teaching-Learning-Based Optimization (TLBO. They are compared with each other to obtain solution for power allocation in a wiretap wireless network. Although all these techniques find suboptimal solutions, but they appear superlative to exact optimization methods. Finally, we define a Figure of Merit (FOM as a rule of thumb to determine the best meta-heuristic algorithm. This FOM considers quality of solution, number of required iterations to converge, and CPU time.

Ethnicity at the individual and neighborhood level as an explanation for moving out of the neighborhood

NARCIS (Netherlands)

Schaake, K.; Burgers, J.; Mulder, C.H.

2010-01-01

We address the influence of both the ethnic composition of the neighborhood and the ethnicity of individual residents on moving out of neighborhoods in the Netherlands. Using the Housing Research Netherlands survey and multinomial logistic regression analyses of moving out versus not moving or

Rapid Development, Build-Out Ratio and Subsequent Neighborhood Turnover

Directory of Open Access Journals (Sweden)

George O. Rogers

2018-04-01

Full Text Available Neighborhood development is primarily comprised of structural elements that include design elements, nearby amenities and ecological attributes. This paper assumes that the process of development itself also influences the character of the neighborhood—specifically, that the rate of development and build-out ratio influences neighborhood turnover. While the structural components clearly set a framework for development, the process of development expresses the character of the neighborhood in subtle messages conveyed through the market. Neighborhoods in the rapidly growing university town of College Station, Texas are analyzed in terms of neighborhood design, nearby amenities and landscape ecology components. Residential property records are used to characterize each neighborhood in terms of the rate of development and current build-out ratio. The multivariate analysis indicates that the development rate increases subsequent neighborhood turnover rates while the build-out ratio decreases it.

An Enhanced Differential Evolution with Elite Chaotic Local Search

Directory of Open Access Journals (Sweden)

Zhaolu Guo

2015-01-01

Full Text Available Differential evolution (DE is a simple yet efficient evolutionary algorithm for real-world engineering problems. However, its search ability should be further enhanced to obtain better solutions when DE is applied to solve complex optimization problems. This paper presents an enhanced differential evolution with elite chaotic local search (DEECL. In DEECL, it utilizes a chaotic search strategy based on the heuristic information from the elite individuals to promote the exploitation power. Moreover, DEECL employs a simple and effective parameter adaptation mechanism to enhance the robustness. Experiments are conducted on a set of classical test functions. The experimental results show that DEECL is very competitive on the majority of the test functions.

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

Science.gov (United States)

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

Neighborhood decline and the economic crisis : an introduction

NARCIS (Netherlands)

van Kempen, Ronald; Bolt, Gideon; van Ham, Maarten

2016-01-01

Urban neighborhoods are still important in the lives of its residents. Therefore, it is important to find out how the recent global financial and economic crisis affects these neighborhoods. Which types of neighborhoods and which residents suffer more than others? This introduction provides an

An efficient heuristic versus a robust hybrid meta-heuristic for general framework of serial-parallel redundancy problem

International Nuclear Information System (INIS)

Sadjadi, Seyed Jafar; Soltani, R.

2009-01-01

We present a heuristic approach to solve a general framework of serial-parallel redundancy problem where the reliability of the system is maximized subject to some general linear constraints. The complexity of the redundancy problem is generally considered to be NP-Hard and the optimal solution is not normally available. Therefore, to evaluate the performance of the proposed method, a hybrid genetic algorithm is also implemented whose parameters are calibrated via Taguchi's robust design method. Then, various test problems are solved and the computational results indicate that the proposed heuristic approach could provide us some promising reliabilities, which are fairly close to optimal solutions in a reasonable amount of time.

The beauty of simple models: Themes in recognition heuristic research

Directory of Open Access Journals (Sweden)

Daniel G. Goldstein

2011-07-01

Full Text Available The advantage of models that do not use flexible parameters is that one can precisely show to what degree they predict behavior, and in what situations. In three issues of this journal, the recognition heuristic has been examined carefully from many points of view. We comment here on four themes, the use of optimization models to understand the rationality of heuristics, the generalization of the recognition input beyond a binary judgment, new conditions for less-is-more effects, and the importance of specifying boundary conditions for cognitive heuristics.

HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN

Science.gov (United States)

While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...

Neighborhood Energy/Economic Development project

Energy Technology Data Exchange (ETDEWEB)

1991-12-31

Energy costs impact low income communities more than anyone else. Low income residents pay a larger percentage of their incomes for energy costs. In addition, they generally have far less discretionary energy use to eliminate in response to increasing energy prices. Furthermore, with less discretionary income, home energy efficiency improvements are often too expensive. Small neighborhood businesses are in the same situation. Improved efficiency in the use of energy can improve this situation by reducing energy costs for residents and local businesses. More importantly, energy management programs can increase the demand for local goods and services and lead to the creation of new job training and employment opportunities. In this way, neighborhood based energy efficiency programs can support community economic development. The present project, undertaken with the support of the Urban Consortium Energy Task Force, was intended to serve as a demonstration of energy/economic programming at the neighborhood level. The San Francisco Neighborhood Energy/Economic Development (NEED) project was designed to be a visible demonstration of bringing the economic development benefits of energy management home to low-income community members who need it most. To begin, a Community Advisory Committee was established to guide the design of the programs to best meet needs of the community. Subsequently three neighborhood energy/economic development programs were developed: The small business energy assistance program; The youth training and weatherization program; and, The energy review of proposed housing development projects.

Neighborhood Effects on Health: Concentrated Advantage and Disadvantage

Science.gov (United States)

Finch, Brian K.; Do, D. Phuong; Heron, Melonie; Bird, Chloe; Seeman, Teresa; Lurie, Nicole

2010-01-01

We investigate an alternative conceptualization of neighborhood context and its association with health. Using an index that measures a continuum of concentrated advantage and disadvantage, we examine whether the relationship between neighborhood conditions and health varies by socio-economic status. Using NHANES III data geo-coded to census tracts, we find that while largely uneducated neighborhoods are universally deleterious, individuals with more education benefit from living in highly educated neighborhoods to a greater degree than individuals with lower levels of education. PMID:20627796

Neighborhood Integration and Connectivity Predict Cognitive Performance and Decline

Directory of Open Access Journals (Sweden)

Amber Watts PhD

2015-08-01

Full Text Available Objective: Neighborhood characteristics may be important for promoting walking, but little research has focused on older adults, especially those with cognitive impairment. We evaluated the role of neighborhood characteristics on cognitive function and decline over a 2-year period adjusting for measures of walking. Method: In a study of 64 older adults with and without mild Alzheimer’s disease (AD, we evaluated neighborhood integration and connectivity using geographical information systems data and space syntax analysis. In multiple regression analyses, we used these characteristics to predict 2-year declines in factor analytically derived cognitive scores (attention, verbal memory, mental status adjusting for age, sex, education, and self-reported walking. Results : Neighborhood integration and connectivity predicted cognitive performance at baseline, and changes in cognitive performance over 2 years. The relationships between neighborhood characteristics and cognitive performance were not fully explained by self-reported walking. Discussion : Clearer definitions of specific neighborhood characteristics associated with walkability are needed to better understand the mechanisms by which neighborhoods may impact cognitive outcomes. These results have implications for measuring neighborhood characteristics, design and maintenance of living spaces, and interventions to increase walking among older adults. We offer suggestions for future research measuring neighborhood characteristics and cognitive function.

Girls' self-efficacy in the context of neighborhood gender stratification.

Science.gov (United States)

Soller, Brian; Jackson, Aubrey L

2018-05-01

Scholars have linked neighborhood characteristics to self-efficacy, but few have considered how gender factors into this association. We integrate literature on neighborhoods, gender stratification, and self-efficacy to examine the association between women's relative resources among neighborhood residents and adolescents' self-efficacy. We hypothesize that girls report more self-efficacy when they reside in neighborhoods where women have more socioeconomic resources relative to men. We test this hypothesis using data from the Project on Human Development in Chicago Neighborhoods and the 1990 Census. Results from multilevel regression models with gender-interacted effects indicate the neighborhood level of women's relative resources was not associated with boys' self-efficacy. However, girls reported higher self-efficacy when women's relative resources in their neighborhoods were greater. This association persisted after including potential individual- and neighborhood-level confounding variables. Our study underscores the importance of attending to gendered processes when understanding how neighborhoods impact youth. Copyright © 2018. Published by Elsevier Inc.

Local beam angle optimization with linear programming and gradient search

International Nuclear Information System (INIS)

Craft, David

2007-01-01

The optimization of beam angles in IMRT planning is still an open problem, with literature focusing on heuristic strategies and exhaustive searches on discrete angle grids. We show how a beam angle set can be locally refined in a continuous manner using gradient-based optimization in the beam angle space. The gradient is derived using linear programming duality theory. Applying this local search to 100 random initial angle sets of a phantom pancreatic case demonstrates the method, and highlights the many-local-minima aspect of the BAO problem. Due to this function structure, we recommend a search strategy of a thorough global search followed by local refinement at promising beam angle sets. Extensions to nonlinear IMRT formulations are discussed. (note)

Examining public open spaces by neighborhood-level walkability and deprivation.

Science.gov (United States)

Badland, Hannah M; Keam, Rosanna; Witten, Karen; Kearns, Robin

2010-11-01

Public open spaces (POS) are recognized as important to promote physical activity engagement. However, it is unclear how POS attributes, such as activities available, environmental quality, amenities present, and safety, are associated with neighborhood-level walkability and deprivation. Twelve neighborhoods were selected within 1 constituent city of Auckland, New Zealand based on higher (n = 6) or lower (n = 6) walkability characteristics. Neighborhoods were dichotomized as more (n = 7) or less (n = 5) socioeconomically deprived. POS (n = 69) were identified within these neighborhoods and audited using the New Zealand-Public Open Space Tool. Unpaired 1-way analysis of variance tests were applied to compare differences in attributes and overall score of POS by neighborhood walkability and deprivation. POS located in more walkable neighborhoods have significantly higher overall scores when compared with less walkable neighborhoods. Deprivation comparisons identified POS located in less deprived communities have better quality environments, but fewer activities and safety features present when compared with more deprived neighborhoods. A positive relationship existed between presence of POS attributes and neighborhood walkability, but the relationship between POS and neighborhood-level deprivation was less clear. Variation in neighborhood POS quality alone is unlikely to explain poorer health outcomes for residents in more deprived areas.

A Longitudinal Analysis of the Influence of the Neighborhood Environment on Recreational Walking within the Neighborhood: Results from RESIDE

OpenAIRE

Christian, Hayley; Knuiman, Matthew; Divitini, Mark; Foster, Sarah; Hooper, Paula; Boruff, Bryan; Bull, Fiona; Giles-Corti, Billie

2017-01-01

Background: There is limited longitudinal evidence confirming the role of neighborhood environment attributes in encouraging people to walk more or if active people simply choose to live in activity-friendly neighborhoods. Natural experiments of policy changes to create more walkable communities provide stronger evidence for a causal effect of neighborhood environments on residents’ walking. Objectives: We aimed to investigate longitudinal associations between objective and perceived neighbor...

Ship Routing with Pickup and Delivery for a Maritime Oil Transportation System: MIP Model and Heuristics

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Vinícius P. Rodrigues

2016-09-01

Full Text Available This paper examines a ship routing problem with pickup and delivery and time windows for maritime oil transportation, motivated by the production and logistics activities of an oil company operating in the Brazilian coast. The transportation costs from offshore platforms to coastal terminals are an important issue in the search for operational excellence in the oil industry, involving operations that demand agile and effective decision support systems. This paper presents an optimization approach to address this problem, based on a mixed integer programming (MIP model and a novel and exploratory application of two tailor-made MIP heuristics, based on relax-and-fix and time decomposition procedures. The model minimizes fuel costs of a heterogeneous fleet of oil tankers and costs related to freighting contracts. The model also considers company-specific constraints for offshore oil transportation. Computational experiments based on the mathematical models and the related MIP heuristics are presented for a set of real data provided by the company, which confirm the potential of optimization-based methods to find good solutions for problems of moderate sizes.

Heuristic Evaluation on Mobile Interfaces: A New Checklist

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Rosa Yáñez Gómez

2014-01-01

Full Text Available The rapid evolution and adoption of mobile devices raise new usability challenges, given their limitations (in screen size, battery life, etc. as well as the specific requirements of this new interaction. Traditional evaluation techniques need to be adapted in order for these requirements to be met. Heuristic evaluation (HE, an Inspection Method based on evaluation conducted by experts over a real system or prototype, is based on checklists which are desktop-centred and do not adequately detect mobile-specific usability issues. In this paper, we propose a compilation of heuristic evaluation checklists taken from the existing bibliography but readapted to new mobile interfaces. Selecting and rearranging these heuristic guidelines offer a tool which works well not just for evaluation but also as a best-practices checklist. The result is a comprehensive checklist which is experimentally evaluated as a design tool. This experimental evaluation involved two software engineers without any specific knowledge about usability, a group of ten users who compared the usability of a first prototype designed without our heuristics, and a second one after applying the proposed checklist. The results of this experiment show the usefulness of the proposed checklist for avoiding usability gaps even with nontrained developers.

Heuristic Evaluation on Mobile Interfaces: A New Checklist

Science.gov (United States)

Yáñez Gómez, Rosa; Cascado Caballero, Daniel; Sevillano, José-Luis

2014-01-01

The rapid evolution and adoption of mobile devices raise new usability challenges, given their limitations (in screen size, battery life, etc.) as well as the specific requirements of this new interaction. Traditional evaluation techniques need to be adapted in order for these requirements to be met. Heuristic evaluation (HE), an Inspection Method based on evaluation conducted by experts over a real system or prototype, is based on checklists which are desktop-centred and do not adequately detect mobile-specific usability issues. In this paper, we propose a compilation of heuristic evaluation checklists taken from the existing bibliography but readapted to new mobile interfaces. Selecting and rearranging these heuristic guidelines offer a tool which works well not just for evaluation but also as a best-practices checklist. The result is a comprehensive checklist which is experimentally evaluated as a design tool. This experimental evaluation involved two software engineers without any specific knowledge about usability, a group of ten users who compared the usability of a first prototype designed without our heuristics, and a second one after applying the proposed checklist. The results of this experiment show the usefulness of the proposed checklist for avoiding usability gaps even with nontrained developers. PMID:25295300

Application of a sensitive collection heuristic for very large protein families: Evolutionary relationship between adipose triglyceride lipase (ATGL and classic mammalian lipases

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Berezovsky Igor

2006-03-01

Full Text Available Abstract Background Manually finding subtle yet statistically significant links to distantly related homologues becomes practically impossible for very populated protein families due to the sheer number of similarity searches to be invoked and analyzed. The unclear evolutionary relationship between classical mammalian lipases and the recently discovered human adipose triglyceride lipase (ATGL; a patatin family member is an exemplary case for such a problem. Results We describe an unsupervised, sensitive sequence segment collection heuristic suitable for assembling very large protein families. It is based on fan-like expanding, iterative database searches. To prevent inclusion of unrelated hits, additional criteria are introduced: minimal alignment length and overlap with starting sequence segments, finding starting sequences in reciprocal searches, automated filtering for compositional bias and repetitive patterns. This heuristic was implemented as FAMILYSEARCHER in the ANNIE sequence analysis environment and applied to search for protein links between the classical lipase family and the patatin-like group. Conclusion The FAMILYSEARCHER is an efficient tool for tracing distant evolutionary relationships involving large protein families. Although classical lipases and ATGL have no obvious sequence similarity and differ with regard to fold and catalytic mechanism, homology links detected with FAMILYSEARCHER show that they are evolutionarily related. The conserved sequence parts can be narrowed down to an ancestral core module consisting of three β-strands, one α-helix and a turn containing the typical nucleophilic serine. Moreover, this ancestral module also appears in numerous enzymes with various substrate specificities, but that critically rely on nucleophilic attack mechanisms.

Generalized perturbation theory (GPT) methods. A heuristic approach

International Nuclear Information System (INIS)

Gandini, A.

1987-01-01

Wigner first proposed a perturbation theory as early as 1945 to study fundamental quantities such as the reactivity worths of different materials. The first formulation, CPT, for conventional perturbation theory is based on universal quantum mechanics concepts. Since that early conception, significant contributions have been made to CPT, in particular, Soodak, who rendered a heuristic interpretation of the adjoint function, (referred to as the GPT method for generalized perturbation theory). The author illustrates the GPT methodology in a variety of linear and nonlinear domains encountered in nuclear reactor analysis. The author begins with the familiar linear neutron field and then generalizes the methodology to other linear and nonlinear fields, using heuristic arguments. The author believes that the inherent simplicity and elegance of the heuristic derivation, although intended here for reactor physics problems might be usefully adopted in collateral fields and includes such examples

Better Buildings Neighborhood Program Progress Stories

Energy Technology Data Exchange (ETDEWEB)

None

2012-04-19

n neighborhoods across the country, stories are emerging constantly of individuals, businesses, and organizations that are benefiting from energy efficiency. Included are the stories of real people making their homes, businesses, and communities better with the help of the Better Buildings Neighborhood Program.

Neighborhood social capital and individual health.