Bivium as a Mixed Integer Programming Problem
DEFF Research Database (Denmark)
Borghoff, Julia; Knudsen, Lars Ramkilde; Stolpe, Mathias
2009-01-01
over $GF(2)$ into a combinatorial optimization problem. We convert the Boolean equation system into an equation system over $\\mathbb{R}$ and formulate the problem of finding a $0$-$1$-valued solution for the system as a mixed-integer programming problem. This enables us to make use of several...
A mixed integer linear program for an integrated fishery | Hasan ...
African Journals Online (AJOL)
... and labour allocation of quota based integrated fisheries. We demonstrate the workability of our model with a numerical example and sensitivity analysis based on data obtained from one of the major fisheries in New Zealand. Keywords: mixed integer linear program, fishing, trawler scheduling, processing, quotas ORiON: ...
A property of assignment type mixed integer linear programming problems
Benders, J.F.; van Nunen, J.A.E.E.
1982-01-01
In this paper we will proof that rather tight upper bounds can be given for the number of non-unique assignments that are achieved after solving the linear programming relaxation of some types of mixed integer linear assignment problems. Since in these cases the number of splitted assignments is
A fuzzy mixed integer programming for marketing planning
Directory of Open Access Journals (Sweden)
Abolfazl Danaei
2014-03-01
Full Text Available One of the primary concerns to market a product is to find appropriate channel to target customers. The recent advances on information technology have created new products with tremendous opportunities. This paper presents a mixed integer programming technique based on McCarthy's 4PS to locate suitable billboards for marketing newly introduced IPHONE product. The paper considers two types of information including age and income and tries to find the best places such that potential consumers aged 25-35 with high income visit the billboards and the cost of advertisement is minimized. The model is formulated in terms of mixed integer programming and it has been applied for potential customers who live in city of Tabriz, Iran. Using a typical software package, the model detects appropriate places in various parts of the city.
A Mixed Integer Programming for Port Anzali Development Plan
Mahdieh Allahviranloo
2009-01-01
This paper introduces a mixed integer programming model to find the optimum development plan for port Anzali. The model minimizes total system costs taking into account both port infrastructure costs and shipping costs. Due to the multipurpose function of the port, the model consists of 1020 decision variables and 2490 constraints. Results of the model determine the optimum number of berths that should be constructed in each period and for each type of cargo. In addition to, the results of se...
Relaxation and decomposition methods for mixed integer nonlinear programming
Nowak, Ivo; Bank, RE
2005-01-01
This book presents a comprehensive description of efficient methods for solving nonconvex mixed integer nonlinear programs, including several numerical and theoretical results, which are presented here for the first time. It contains many illustrations and an up-to-date bibliography. Because on the emphasis on practical methods, as well as the introduction into the basic theory, the book is accessible to a wide audience. It can be used both as a research and as a graduate text.
Applications and algorithms for mixed integer nonlinear programming
International Nuclear Information System (INIS)
Leyffer, Sven; Munson, Todd; Linderoth, Jeff; Luedtke, James; Miller, Andrew
2009-01-01
The mathematical modeling of systems often requires the use of both nonlinear and discrete components. Discrete decision variables model dichotomies, discontinuities, and general logical relationships. Nonlinear functions are required to accurately represent physical properties such as pressure, stress, temperature, and equilibrium. Problems involving both discrete variables and nonlinear constraint functions are known as mixed-integer nonlinear programs (MINLPs) and are among the most challenging computational optimization problems faced by researchers and practitioners. In this paper, we describe relevant scientific applications that are naturally modeled as MINLPs, we provide an overview of available algorithms and software, and we describe ongoing methodological advances for solving MINLPs. These algorithmic advances are making increasingly larger instances of this important family of problems tractable.
Multiobjective fuzzy stochastic linear programming problems with inexact probability distribution
Energy Technology Data Exchange (ETDEWEB)
Hamadameen, Abdulqader Othman [Optimization, Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia); Zainuddin, Zaitul Marlizawati [Department of Mathematical Sciences, Faculty of Science, UTM (Malaysia)
2014-06-19
This study deals with multiobjective fuzzy stochastic linear programming problems with uncertainty probability distribution which are defined as fuzzy assertions by ambiguous experts. The problem formulation has been presented and the two solutions strategies are; the fuzzy transformation via ranking function and the stochastic transformation when α{sup –}. cut technique and linguistic hedges are used in the uncertainty probability distribution. The development of Sen’s method is employed to find a compromise solution, supported by illustrative numerical example.
Mixed Integer Programming and Heuristic Scheduling for Space Communication
Lee, Charles H.; Cheung, Kar-Ming
2013-01-01
Optimal planning and scheduling for a communication network was created where the nodes within the network are communicating at the highest possible rates while meeting the mission requirements and operational constraints. The planning and scheduling problem was formulated in the framework of Mixed Integer Programming (MIP) to introduce a special penalty function to convert the MIP problem into a continuous optimization problem, and to solve the constrained optimization problem using heuristic optimization. The communication network consists of space and ground assets with the link dynamics between any two assets varying with respect to time, distance, and telecom configurations. One asset could be communicating with another at very high data rates at one time, and at other times, communication is impossible, as the asset could be inaccessible from the network due to planetary occultation. Based on the network's geometric dynamics and link capabilities, the start time, end time, and link configuration of each view period are selected to maximize the communication efficiency within the network. Mathematical formulations for the constrained mixed integer optimization problem were derived, and efficient analytical and numerical techniques were developed to find the optimal solution. By setting up the problem using MIP, the search space for the optimization problem is reduced significantly, thereby speeding up the solution process. The ratio of the dimension of the traditional method over the proposed formulation is approximately an order N (single) to 2*N (arraying), where N is the number of receiving antennas of a node. By introducing a special penalty function, the MIP problem with non-differentiable cost function and nonlinear constraints can be converted into a continuous variable problem, whose solution is possible.
Domí nguez, Luis F.; Pistikopoulos, Efstratios N.
2010-01-01
continuous multiparametric programming algorithm is then used to solve the reformulated convex inner problem. The second algorithm addresses the mixed-integer case of the bilevel programming problem where integer and continuous variables of the outer problem
Mixed integer (0-1) fractional programming for decision support in paper production industry
Claassen, G.D.H.
2014-01-01
This paper presents an effective and efficient method for solving a special class of mixed integer fractional programming (FP) problems. We take a classical reformulation approach for continuous FP as a starting point and extend it for solving a more general class of mixed integer (0–1) fractional
Learning oncogenetic networks by reducing to mixed integer linear programming.
Shahrabi Farahani, Hossein; Lagergren, Jens
2013-01-01
Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.
Directory of Open Access Journals (Sweden)
Tessa Vanina Soetanto
2004-01-01
Full Text Available This paper presents a study about new heuristic algorithm performance compared to Mixed Integer Programming (MIP method in solving flowshop scheduling problem to reach minimum makespan. Performance appraisal is based on Efficiency Index (EI, Relative Error (RE and Elapsed Runtime. Abstract in Bahasa Indonesia : Makalah ini menyajikan penelitian tentang performance algoritma heuristik Pour terhadap metode Mixed Integer Programming (MIP dalam menyelesaikan masalah penjadwalan flowshop dengan tujuan meminimalkan makespan. Penilaian performance dilakukan berdasarkan nilai Efficiency Index (EI, Relative Error (RE dan Elapsed Runtime. Kata kunci: flowshop, makespan, algoritma heuristik Pour, Mixed Integer Programming.
FATCOP: A Fault Tolerant Condor-PVM Mixed Integer Program Solver
National Research Council Canada - National Science Library
Chen, Qun
1999-01-01
We describe FATCOP, a new parallel mixed integer program solver written in PVM. The implementation uses the Condor resource management system to provide a virtual machine composed of otherwise idle computers...
An Improvement for Fuzzy Stochastic Goal Programming Problems
Directory of Open Access Journals (Sweden)
Shu-Cheng Lin
2017-01-01
Full Text Available We examined the solution process for linear programming problems under a fuzzy and random environment to transform fuzzy stochastic goal programming problems into standard linear programming problems. A previous paper that revised the solution process with the lower-side attainment index motivated our work. In this paper, we worked on a revision for both-side attainment index to amend its definition and theorems. Two previous examples were used to examine and demonstrate our improvement over previous results. Our findings not only improve the previous paper with both-side attainment index, but also provide a theoretical extension from lower-side attainment index to the both-side attainment index.
A mixed integer program to model spatial wildfire behavior and suppression placement decisions
Erin J. Belval; Yu Wei; Michael. Bevers
2015-01-01
Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...
Domínguez, Luis F.
2010-12-01
This work introduces two algorithms for the solution of pure integer and mixed-integer bilevel programming problems by multiparametric programming techniques. The first algorithm addresses the integer case of the bilevel programming problem where integer variables of the outer optimization problem appear in linear or polynomial form in the inner problem. The algorithm employs global optimization techniques to convexify nonlinear terms generated by a reformulation linearization technique (RLT). A continuous multiparametric programming algorithm is then used to solve the reformulated convex inner problem. The second algorithm addresses the mixed-integer case of the bilevel programming problem where integer and continuous variables of the outer problem appear in linear or polynomial forms in the inner problem. The algorithm relies on the use of global multiparametric mixed-integer programming techniques at the inner optimization level. In both algorithms, the multiparametric solutions obtained are embedded in the outer problem to form a set of single-level (M)(I)(N)LP problems - which are then solved to global optimality using standard fixed-point (global) optimization methods. Numerical examples drawn from the open literature are presented to illustrate the proposed algorithms. © 2010 Elsevier Ltd.
DEFF Research Database (Denmark)
Liu, Zhaoxi; Wu, Qiuwei; Oren, Shmuel S.
2017-01-01
This paper presents a distribution locational marginal pricing (DLMP) method through chance constrained mixed-integer programming designed to alleviate the possible congestion in the future distribution network with high penetration of electric vehicles (EVs). In order to represent the stochastic...
DEFF Research Database (Denmark)
Hernández, Adriana Carolina Luna; Aldana, Nelson Leonardo Diaz; Graells, Moises
2017-01-01
-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data...
An overview of solution methods for multi-objective mixed integer linear programming programs
DEFF Research Database (Denmark)
Andersen, Kim Allan; Stidsen, Thomas Riis
Multiple objective mixed integer linear programming (MOMIP) problems are notoriously hard to solve to optimality, i.e. finding the complete set of non-dominated solutions. We will give an overview of existing methods. Among those are interactive methods, the two phases method and enumeration...... methods. In particular we will discuss the existing branch and bound approaches for solving multiple objective integer programming problems. Despite the fact that branch and bound methods has been applied successfully to integer programming problems with one criterion only a few attempts has been made...
Mixed integer linear programming for maximum-parsimony phylogeny inference.
Sridhar, Srinath; Lam, Fumei; Blelloch, Guy E; Ravi, R; Schwartz, Russell
2008-01-01
Reconstruction of phylogenetic trees is a fundamental problem in computational biology. While excellent heuristic methods are available for many variants of this problem, new advances in phylogeny inference will be required if we are to be able to continue to make effective use of the rapidly growing stores of variation data now being gathered. In this paper, we present two integer linear programming (ILP) formulations to find the most parsimonious phylogenetic tree from a set of binary variation data. One method uses a flow-based formulation that can produce exponential numbers of variables and constraints in the worst case. The method has, however, proven extremely efficient in practice on datasets that are well beyond the reach of the available provably efficient methods, solving several large mtDNA and Y-chromosome instances within a few seconds and giving provably optimal results in times competitive with fast heuristics than cannot guarantee optimality. An alternative formulation establishes that the problem can be solved with a polynomial-sized ILP. We further present a web server developed based on the exponential-sized ILP that performs fast maximum parsimony inferences and serves as a front end to a database of precomputed phylogenies spanning the human genome.
DEFF Research Database (Denmark)
Jensen, Toke Koldborg; Kjærsgaard, Niels Christian
Slaughterhouses are major players in the pork supply chain, and supply and demand must be matched in order to generate the highest proﬁt. In particular, carcasses must be sorted in order to produce the “right” ﬁnal products from the “right” carcasses. We develop a mixed-integer programming (MIP) ...... at slaughterhouses. Finally, we comment on the expected effect of variations in the raw material supply and the demand as well as future research concerning joint modelling of supply chain aspects.......Slaughterhouses are major players in the pork supply chain, and supply and demand must be matched in order to generate the highest proﬁt. In particular, carcasses must be sorted in order to produce the “right” ﬁnal products from the “right” carcasses. We develop a mixed-integer programming (MIP...
Mixed integer linear programming model for dynamic supplier selection problem considering discounts
Directory of Open Access Journals (Sweden)
Adi Wicaksono Purnawan
2018-01-01
Full Text Available Supplier selection is one of the most important elements in supply chain management. This function involves evaluation of many factors such as, material costs, transportation costs, quality, delays, supplier capacity, storage capacity and others. Each of these factors varies with time, therefore, supplier identified for one period is not necessarily be same for the next period to supply the same product. So, mixed integer linear programming (MILP was developed to overcome the dynamic supplier selection problem (DSSP. In this paper, a mixed integer linear programming model is built to solve the lot-sizing problem with multiple suppliers, multiple periods, multiple products and quantity discounts. The buyer has to make a decision for some products which will be supplied by some suppliers for some periods cosidering by discount. To validate the MILP model with randomly generated data. The model is solved by Lingo 16.
Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach
Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin
2014-09-01
Enhanced index tracking is a popular form of portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.
A Mixed Integer Linear Programming Model for the North Atlantic Aircraft Trajectory Planning
Sbihi , Mohammed; Rodionova , Olga; Delahaye , Daniel; Mongeau , Marcel
2015-01-01
International audience; This paper discusses the trajectory planning problem for ights in the North Atlantic oceanic airspace (NAT). We develop a mathematical optimization framework in view of better utilizing available capacity by re-routing aircraft. The model is constructed by discretizing the problem parameters. A Mixed integer linear program (MILP) is proposed. Based on the MILP a heuristic to solve real-size instances is also introduced
Chenlu Miao; Gang Du; Yi Xia; Danping Wang
2016-01-01
Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP) to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP), which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard pr...
FSILP: fuzzy-stochastic-interval linear programming for supporting municipal solid waste management.
Li, Pu; Chen, Bing
2011-04-01
Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk. Copyright © 2010 Elsevier Ltd. All rights reserved.
Domí nguez, Luis F.; Pistikopoulos, Efstratios N.
2012-01-01
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear
Mixed Integer Linear Programming model for Crude Palm Oil Supply Chain Planning
Sembiring, Pasukat; Mawengkang, Herman; Sadyadharma, Hendaru; Bu'ulolo, F.; Fajriana
2018-01-01
The production process of crude palm oil (CPO) can be defined as the milling process of raw materials, called fresh fruit bunch (FFB) into end products palm oil. The process usually through a series of steps producing and consuming intermediate products. The CPO milling industry considered in this paper does not have oil palm plantation, therefore the FFB are supplied by several public oil palm plantations. Due to the limited availability of FFB, then it is necessary to choose from which plantations would be appropriate. This paper proposes a mixed integer linear programming model the supply chain integrated problem, which include waste processing. The mathematical programming model is solved using neighborhood search approach.
Optimal Allocation of Static Var Compensator via Mixed Integer Conic Programming
Energy Technology Data Exchange (ETDEWEB)
Zhang, Xiaohu [ORNL; Shi, Di [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Zhiwei [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Huang, Junhui [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Xu [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)
2017-01-01
Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.
Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach
International Nuclear Information System (INIS)
Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.
2010-01-01
This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach.
Scheduling of head-dependent cascaded hydro systems: Mixed-integer quadratic programming approach
Energy Technology Data Exchange (ETDEWEB)
Catalao, J.P.S.; Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)
2010-03-15
This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent cascaded hydro systems. We propose a novel mixed-integer quadratic programming approach, considering not only head-dependency, but also discontinuous operating regions and discharge ramping constraints. Thus, an enhanced short-term hydro scheduling is provided due to the more realistic modeling presented in this paper. Numerical results from two case studies, based on Portuguese cascaded hydro systems, illustrate the proficiency of the proposed approach. (author)
Optimal placement of capacitors in a radial network using conic and mixed integer linear programming
Energy Technology Data Exchange (ETDEWEB)
Jabr, R.A. [Electrical, Computer and Communication Engineering Department, Notre Dame University, P.O. Box: 72, Zouk Mikhael, Zouk Mosbeh (Lebanon)
2008-06-15
This paper considers the problem of optimally placing fixed and switched type capacitors in a radial distribution network. The aim of this problem is to minimize the costs associated with capacitor banks, peak power, and energy losses whilst satisfying a pre-specified set of physical and technical constraints. The proposed solution is obtained using a two-phase approach. In phase-I, the problem is formulated as a conic program in which all nodes are candidates for placement of capacitor banks whose sizes are considered as continuous variables. A global solution of the phase-I problem is obtained using an interior-point based conic programming solver. Phase-II seeks a practical optimal solution by considering capacitor sizes as discrete variables. The problem in this phase is formulated as a mixed integer linear program based on minimizing the L1-norm of deviations from the phase-I state variable values. The solution to the phase-II problem is obtained using a mixed integer linear programming solver. The proposed method is validated via extensive comparisons with previously published results. (author)
DEFF Research Database (Denmark)
Pour, Shahrzad M.; Drake, John H.; Ejlertsen, Lena Secher
2017-01-01
A railway signaling system is a complex and interdependent system which should ensure the safe operation of trains. We introduce and address a mixed integer optimisation model for the preventive signal maintenance crew scheduling problem in the Danish railway system. The problem contains many...... to feed as ‘warm start’ solutions to a Mixed Integer Programming (MIP) solver for further optimisation. We apply the CP/MIP framework to a section of the Danish rail network and benchmark our results against both direct application of a MIP solver and modelling the problem as a Constraint Optimisation...
A Mixed Integer Programming Poultry Feed Ration Optimisation Problem Using the Bat Algorithm
Directory of Open Access Journals (Sweden)
Godfrey Chagwiza
2016-01-01
Full Text Available In this paper, a feed ration problem is presented as a mixed integer programming problem. An attempt to find the optimal quantities of Moringa oleifera inclusion into the poultry feed ration was done and the problem was solved using the Bat algorithm and the Cplex solver. The study used findings of previous research to investigate the effects of Moringa oleifera inclusion in poultry feed ration. The results show that the farmer is likely to gain US$0.89 more if Moringa oleifera is included in the feed ration. Results also show superiority of the Bat algorithm in terms of execution time and number of iterations required to find the optimum solution as compared with the results obtained by the Cplex solver. Results revealed that there is a significant economic benefit of Moringa oleifera inclusion into the poultry feed ration.
Planning of fuel coal imports using a mixed integer programming method
International Nuclear Information System (INIS)
Shih, L.H.
1997-01-01
In the public utility and commercial fuel industries, commodities from multiple supply sources are sometimes blended before use to reduce costs and assure quality. A typical example of these commodities is the fuel coal used in coal fired power plants. The diversity of the supply sources for these plants makes the planning and scheduling of fuel coal logistics difficult, especially for a power company that has more than one power plant. This study proposes a mixed integer programming model that provides planning and scheduling of coal imports from multiple suppliers for the Taiwan Power Company. The objective is to minimize total inventory cost by minimizing procurement cost, transportation cost and holding cost. Constraints on the system include company procurement policy, power plant demand, harbor unloading capacity, inventory balance equations, blending requirements, and safety stock. An example problem is presented using the central coal logistics system of the Taiwan Power Company to demonstrate the validity of the proposed model
Planning of fuel coal imports using a mixed integer programming method
Energy Technology Data Exchange (ETDEWEB)
Shih, L.H. [National Cheng Kung University, Tainan (Taiwan). Dept. of Mineral and Petroleum Engineering
1997-12-31
In the public utility and commercial fuel industries, commodities from multiple supply sources are sometimes blended before use to reduce costs and assure quality. A typical example of these commodities is the fuel coal used in coal fired power plants. The diversity of the supply sources for these plants makes the planning and scheduling of fuel coal logistics difficult, especially for a power company that has more than one power plant. This study proposes a mixed integer programming model that provides planning and scheduling of coal imports from multiple suppliers for the Taiwan Power Company. The objective is to minimize total inventory cost by minimizing procurement cost, transportation cost and holding cost. Constraints on the system include company procurement policy, power plant demand, harbor unloading capacity, inventory balance equations, blending requirements, and safety stock. An example problem is presented using the central coal logistics system of the Taiwan Power Company to demonstrate the validity of the proposed model.
Integrative improvement method and mixed-integer programming in system planning
International Nuclear Information System (INIS)
Sadegheih, A.
2002-01-01
In this paper, system planning network is formulated for mixed-integer programming and a Ga. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The Dc load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions. and also provides information regarding the optimal generation at each generation point. This method of solutions is demonstrated on the expansion of a 5 bus -bar system to 6 bus-bars
A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.
Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa
2018-02-01
Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.
Advances in mixed-integer programming methods for chemical production scheduling.
Velez, Sara; Maravelias, Christos T
2014-01-01
The goal of this paper is to critically review advances in the area of chemical production scheduling over the past three decades and then present two recently proposed solution methods that have led to dramatic computational enhancements. First, we present a general framework and problem classification and discuss modeling and solution methods with an emphasis on mixed-integer programming (MIP) techniques. Second, we present two solution methods: (a) a constraint propagation algorithm that allows us to compute parameters that are then used to tighten MIP scheduling models and (b) a reformulation that introduces new variables, thus leading to effective branching. We also present computational results and an example illustrating how these methods are implemented, as well as the resulting enhancements. We close with a discussion of open research challenges and future research directions.
A Branch and Bound Algorithm for a Class of Biobjective Mixed Integer Programs
DEFF Research Database (Denmark)
Stidsen, Thomas Riis; Andersen, Kim Allan; Dammann, Bernd
2014-01-01
there is the complicating factor that some of the variables are required to be integral. The resulting class of problems is named multiobjective mixed integer programming (MOMIP) problems. Solving these kinds of optimization problems exactly requires a method that can generate the whole set of nondominated points (the...... Pareto-optimal front). In this paper, we first give a survey of the newly developed branch and bound methods for solving MOMIP problems. After that, we propose a new branch and bound method for solving a subclass of MOMIP problems, where only two objectives are allowed, the integer variables are binary......, and one of the two objectives has only integer variables. The proposed method is able to find the full set of nondominated points. It is tested on a large number of problem instances, from six different classes of MOMIP problems. The results reveal that the developed biobjective branch and bound method...
A Two-Stage Stochastic Mixed-Integer Programming Approach to the Smart House Scheduling Problem
Ozoe, Shunsuke; Tanaka, Yoichi; Fukushima, Masao
A “Smart House” is a highly energy-optimized house equipped with photovoltaic systems (PV systems), electric battery systems, fuel cell cogeneration systems (FC systems), electric vehicles (EVs) and so on. Smart houses are attracting much attention recently thanks to their enhanced ability to save energy by making full use of renewable energy and by achieving power grid stability despite an increased power draw for installed PV systems. Yet running a smart house's power system, with its multiple power sources and power storages, is no simple task. In this paper, we consider the problem of power scheduling for a smart house with a PV system, an FC system and an EV. We formulate the problem as a mixed integer programming problem, and then extend it to a stochastic programming problem involving recourse costs to cope with uncertain electricity demand, heat demand and PV power generation. Using our method, we seek to achieve the optimal power schedule running at the minimum expected operation cost. We present some results of numerical experiments with data on real-life demands and PV power generation to show the effectiveness of our method.
Application of mixed-integer linear programming in a car seats assembling process
Directory of Open Access Journals (Sweden)
Jorge Iván Perez Rave
2011-12-01
Full Text Available In this paper, a decision problem involving a car parts manufacturing company is modeled in order to prepare the company for an increase in demand. Mixed-integer linear programming was used with the following decision variables: creating a second shift, purchasing additional equipment, determining the required work force, and other alternatives involving new manners of work distribution that make it possible to separate certain operations from some workplaces and integrate them into others to minimize production costs. The model was solved using GAMS. The solution consisted of programming 19 workers under a configuration that merges two workplaces and separates some operations from some workplaces. The solution did not involve purchasing additional machinery or creating a second shift. As a result, the manufacturing paradigms that had been valid in the company for over 14 years were broken. This study allowed the company to increase its productivity and obtain significant savings. It also shows the benefits of joint work between academia and companies, and provides useful information for professors, students and engineers regarding production and continuous improvement.
Optimal Airport Surface Traffic Planning Using Mixed-Integer Linear Programming
Directory of Open Access Journals (Sweden)
P. C. Roling
2008-01-01
Full Text Available We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool that aims to optimize the routing and scheduling of airport surface traffic in such a way as to deconflict the taxi plans while optimizing delay, total taxi-time, or some other airport efficiency metric. Certain input parameters related to resource demand, such as the expected landing times and the expected pushback times, are rather difficult to predict accurately. Due to uncertainty in the input data driving the taxi-planning process, the taxi-planning tool is designed such that it produces solutions that are robust to uncertainty. The taxi-planning concept presented herein, which is based on mixed-integer linear programming, is designed such that it is able to adapt to perturbations in these input conditions, as well as to account for failure in the actual execution of surface trajectories. The capabilities of the tool are illustrated in a simple hypothetical airport.
International Nuclear Information System (INIS)
Santos Coelho, Leandro dos
2009-01-01
The reliability-redundancy optimization problems can involve the selection of components with multiple choices and redundancy levels that produce maximum benefits, and are subject to the cost, weight, and volume constraints. Many classical mathematical methods have failed in handling nonconvexities and nonsmoothness in reliability-redundancy optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solutions. One of these meta-heuristics is the particle swarm optimization (PSO). PSO is a population-based heuristic optimization technique inspired by social behavior of bird flocking and fish schooling. This paper presents an efficient PSO algorithm based on Gaussian distribution and chaotic sequence (PSO-GC) to solve the reliability-redundancy optimization problems. In this context, two examples in reliability-redundancy design problems are evaluated. Simulation results demonstrate that the proposed PSO-GC is a promising optimization technique. PSO-GC performs well for the two examples of mixed-integer programming in reliability-redundancy applications considered in this paper. The solutions obtained by the PSO-GC are better than the previously best-known solutions available in the recent literature
Optimising the selection of food items for FFQs using Mixed Integer Linear Programming.
Gerdessen, Johanna C; Souverein, Olga W; van 't Veer, Pieter; de Vries, Jeanne Hm
2015-01-01
To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium. The food lists generated by the MILP model have good performance in terms of length, coverage and R 2 (explained variance) of all nutrients. MILP-generated food lists were 32-40 % shorter than a benchmark food list, whereas their quality in terms of R 2 was similar to that of the benchmark. The results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.
A mixed integer linear programming model applied in barge planning for Omya
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David Bredström
2015-12-01
Full Text Available This article presents a mathematical model for barge transport planning on the river Rhine, which is part of a decision support system (DSS recently taken into use by the Swiss company Omya. The system is operated by Omya’s regional office in Cologne, Germany, responsible for distribution planning at the regional distribution center (RDC in Moerdijk, the Netherlands. The distribution planning is a vital part of supply chain management of Omya’s production of Norwegian high quality calcium carbonate slurry, supplied to European paper manufacturers. The DSS operates within a vendor managed inventory (VMI setting, where the customer inventories are monitored by Omya, who decides upon the refilling days and quantities delivered by barges. The barge planning problem falls into the category of inventory routing problems (IRP and is further characterized with multiple products, heterogeneous fleet with availability restrictions (the fleet is owned by third party, vehicle compartments, dependency of barge capacity on water-level, multiple customer visits, bounded customer inventories and rolling planning horizon. There are additional modelling details which had to be considered to make it possible to employ the model in practice at a sufficient level of detail. To the best of our knowledge, we have not been able to find similar models covering all these aspects in barge planning. This article presents the developed mixed-integer programming model and discusses practical experience with its solution. Briefly, it also puts the model into the context of the entire business case of value chain optimization in Omya.
A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.
Röhl, Annika; Bockmayr, Alexander
2017-01-03
Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.
Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer
2016-06-02
Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Baran, Richard; Northen, Trent R
2013-10-15
Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.
Energy Technology Data Exchange (ETDEWEB)
Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br
2009-04-15
The reliability-redundancy optimization problems can involve the selection of components with multiple choices and redundancy levels that produce maximum benefits, and are subject to the cost, weight, and volume constraints. Many classical mathematical methods have failed in handling nonconvexities and nonsmoothness in reliability-redundancy optimization problems. As an alternative to the classical optimization approaches, the meta-heuristics have been given much attention by many researchers due to their ability to find an almost global optimal solutions. One of these meta-heuristics is the particle swarm optimization (PSO). PSO is a population-based heuristic optimization technique inspired by social behavior of bird flocking and fish schooling. This paper presents an efficient PSO algorithm based on Gaussian distribution and chaotic sequence (PSO-GC) to solve the reliability-redundancy optimization problems. In this context, two examples in reliability-redundancy design problems are evaluated. Simulation results demonstrate that the proposed PSO-GC is a promising optimization technique. PSO-GC performs well for the two examples of mixed-integer programming in reliability-redundancy applications considered in this paper. The solutions obtained by the PSO-GC are better than the previously best-known solutions available in the recent literature.
Automatic Design of Synthetic Gene Circuits through Mixed Integer Non-linear Programming
Huynh, Linh; Kececioglu, John; Köppe, Matthias; Tagkopoulos, Ilias
2012-01-01
Automatic design of synthetic gene circuits poses a significant challenge to synthetic biology, primarily due to the complexity of biological systems, and the lack of rigorous optimization methods that can cope with the combinatorial explosion as the number of biological parts increases. Current optimization methods for synthetic gene design rely on heuristic algorithms that are usually not deterministic, deliver sub-optimal solutions, and provide no guaranties on convergence or error bounds. Here, we introduce an optimization framework for the problem of part selection in synthetic gene circuits that is based on mixed integer non-linear programming (MINLP), which is a deterministic method that finds the globally optimal solution and guarantees convergence in finite time. Given a synthetic gene circuit, a library of characterized parts, and user-defined constraints, our method can find the optimal selection of parts that satisfy the constraints and best approximates the objective function given by the user. We evaluated the proposed method in the design of three synthetic circuits (a toggle switch, a transcriptional cascade, and a band detector), with both experimentally constructed and synthetic promoter libraries. Scalability and robustness analysis shows that the proposed framework scales well with the library size and the solution space. The work described here is a step towards a unifying, realistic framework for the automated design of biological circuits. PMID:22536398
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Maoyuan Feng
2014-01-01
Full Text Available This study proposes a mixed integer linear programming (MILP model to optimize the spillways scheduling for reservoir flood control. Unlike the conventional reservoir operation model, the proposed MILP model specifies the spillways status (including the number of spillways to be open and the degree of the spillway opened instead of reservoir release, since the release is actually controlled by using the spillway. The piecewise linear approximation is used to formulate the relationship between the reservoir storage and water release for a spillway, which should be open/closed with a status depicted by a binary variable. The control order and symmetry rules of spillways are described and incorporated into the constraints for meeting the practical demand. Thus, a MILP model is set up to minimize the maximum reservoir storage. The General Algebraic Modeling System (GAMS and IBM ILOG CPLEX Optimization Studio (CPLEX software are used to find the optimal solution for the proposed MILP model. The China’s Three Gorges Reservoir, whose spillways are of five types with the total number of 80, is selected as the case study. It is shown that the proposed model decreases the flood risk compared with the conventional operation and makes the operation more practical by specifying the spillways status directly.
A multiple objective mixed integer linear programming model for power generation expansion planning
Energy Technology Data Exchange (ETDEWEB)
Antunes, C. Henggeler; Martins, A. Gomes [INESC-Coimbra, Coimbra (Portugal); Universidade de Coimbra, Dept. de Engenharia Electrotecnica, Coimbra (Portugal); Brito, Isabel Sofia [Instituto Politecnico de Beja, Escola Superior de Tecnologia e Gestao, Beja (Portugal)
2004-03-01
Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision makers may grasp the conflicting nature and the trade-offs among the different objectives in order to select satisfactory compromise solutions. This paper presents a multiple objective mixed integer linear programming model for power generation expansion planning that allows the consideration of modular expansion capacity values of supply-side options. This characteristic of the model avoids the well-known problem associated with continuous capacity values that usually have to be discretized in a post-processing phase without feedback on the nature and importance of the changes in the attributes of the obtained solutions. Demand-side management (DSM) is also considered an option in the planning process, assuming there is a sufficiently large portion of the market under franchise conditions. As DSM full costs are accounted in the model, including lost revenues, it is possible to perform an evaluation of the rate impact in order to further inform the decision process (Author)
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Chenlu Miao
2016-01-01
Full Text Available Many leader-follower relationships exist in product family design engineering problems. We use bilevel programming (BLP to reflect the leader-follower relationship and describe such problems. Product family design problems have unique characteristics; thus, mixed integer nonlinear BLP (MINLBLP, which has both continuous and discrete variables and multiple independent lower-level problems, is widely used in product family optimization. However, BLP is difficult in theory and is an NP-hard problem. Consequently, using traditional methods to solve such problems is difficult. Genetic algorithms (GAs have great value in solving BLP problems, and many studies have designed GAs to solve BLP problems; however, such GAs are typically designed for special cases that do not involve MINLBLP with one or multiple followers. Therefore, we propose a bilevel GA to solve these particular MINLBLP problems, which are widely used in product family problems. We give numerical examples to demonstrate the effectiveness of the proposed algorithm. In addition, a reducer family case study is examined to demonstrate practical applications of the proposed BLGA.
Lemmen-Gerdessen, van J.C.; Souverein, O.W.; Veer, van 't P.; Vries, de J.H.M.
2015-01-01
Objective To support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible. Design Selection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear
Canepa, Edward S.; Claudel, Christian G.
2012-01-01
This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.
Canepa, Edward S.
2012-09-01
This article presents a new mixed integer programming formulation of the traffic density estimation problem in highways modeled by the Lighthill Whitham Richards equation. We first present an equivalent formulation of the problem using an Hamilton-Jacobi equation. Then, using a semi-analytic formula, we show that the model constraints resulting from the Hamilton-Jacobi equation result in linear constraints, albeit with unknown integers. We then pose the problem of estimating the density at the initial time given incomplete and inaccurate traffic data as a Mixed Integer Program. We then present a numerical implementation of the method using experimental flow and probe data obtained during Mobile Century experiment. © 2012 IEEE.
Domínguez, Luis F.
2012-06-25
An algorithm for the solution of convex multiparametric mixed-integer nonlinear programming problems arising in process engineering problems under uncertainty is introduced. The proposed algorithm iterates between a multiparametric nonlinear programming subproblem and a mixed-integer nonlinear programming subproblem to provide a series of parametric upper and lower bounds. The primal subproblem is formulated by fixing the integer variables and solved through a series of multiparametric quadratic programming (mp-QP) problems based on quadratic approximations of the objective function, while the deterministic master subproblem is formulated so as to provide feasible integer solutions for the next primal subproblem. To reduce the computational effort when infeasibilities are encountered at the vertices of the critical regions (CRs) generated by the primal subproblem, a simplicial approximation approach is used to obtain CRs that are feasible at each of their vertices. The algorithm terminates when there does not exist an integer solution that is better than the one previously used by the primal problem. Through a series of examples, the proposed algorithm is compared with a multiparametric mixed-integer outer approximation (mp-MIOA) algorithm to demonstrate its computational advantages. © 2012 American Institute of Chemical Engineers (AIChE).
Tang, Jiafu; Liu, Yang; Fung, Richard; Luo, Xinggang
2008-12-01
Manufacturers have a legal accountability to deal with industrial waste generated from their production processes in order to avoid pollution. Along with advances in waste recovery techniques, manufacturers may adopt various recycling strategies in dealing with industrial waste. With reuse strategies and technologies, byproducts or wastes will be returned to production processes in the iron and steel industry, and some waste can be recycled back to base material for reuse in other industries. This article focuses on a recovery strategies optimization problem for a typical class of industrial waste recycling process in order to maximize profit. There are multiple strategies for waste recycling available to generate multiple byproducts; these byproducts are then further transformed into several types of chemical products via different production patterns. A mixed integer programming model is developed to determine which recycling strategy and which production pattern should be selected with what quantity of chemical products corresponding to this strategy and pattern in order to yield maximum marginal profits. The sales profits of chemical products and the set-up costs of these strategies, patterns and operation costs of production are considered. A simulated annealing (SA) based heuristic algorithm is developed to solve the problem. Finally, an experiment is designed to verify the effectiveness and feasibility of the proposed method. By comparing a single strategy to multiple strategies in an example, it is shown that the total sales profit of chemical products can be increased by around 25% through the simultaneous use of multiple strategies. This illustrates the superiority of combinatorial multiple strategies. Furthermore, the effects of the model parameters on profit are discussed to help manufacturers organize their waste recycling network.
Mixed-integer programming methods for transportation and power generation problems
Damci Kurt, Pelin
This dissertation conducts theoretical and computational research to solve challenging problems in application areas such as supply chain and power systems. The first part of the dissertation studies a transportation problem with market choice (TPMC) which is a variant of the classical transportation problem in which suppliers with limited capacities have a choice of which demands (markets) to satisfy. We show that TPMC is strongly NP-complete. We consider a version of the problem with a service level constraint on the maximum number of markets that can be rejected and show that if the original problem is polynomial, its cardinality-constrained version is also polynomial. We propose valid inequalities for mixed-integer cover and knapsack sets with variable upper bound constraints, which appear as substructures of TPMC and use them in a branch-and-cut algorithm to solve this problem. The second part of this dissertation studies a unit commitment (UC) problem in which the goal is to minimize the operational cost of power generators over a time period subject to physical constraints while satisfying demand. We provide several exponential classes of multi-period ramping and multi-period variable upper bound inequalities. We prove the strength of these inequalities and describe polynomial-time separation algorithms. Computational results show the effectiveness of the proposed inequalities when used as cuts in a branch-and-cut algorithm to solve the UC problem. The last part of this dissertation investigates the effects of uncertain wind power on the UC problem. A two-stage robust model and a three-stage stochastic program are compared.
Mixed integer programming model for optimizing the layout of an ICU vehicle
Directory of Open Access Journals (Sweden)
García-Sánchez Álvaro
2009-12-01
Full Text Available Abstract Background This paper presents a Mixed Integer Programming (MIP model for designing the layout of the Intensive Care Units' (ICUs patient care space. In particular, this MIP model was developed for optimizing the layout for materials to be used in interventions. This work was developed within the framework of a joint project between the Madrid Technical Unverstity and the Medical Emergency Services of the Madrid Regional Government (SUMMA 112. Methods The first task was to identify the relevant information to define the characteristics of the new vehicles and, in particular, to obtain a satisfactory interior layout to locate all the necessary materials. This information was gathered from health workers related to ICUs. With that information an optimization model was developed in order to obtain a solution. From the MIP model, a first solution was obtained, consisting of a grid to locate the different materials needed for the ICUs. The outcome from the MIP model was discussed with health workers to tune the solution, and after slightly altering that solution to meet some requirements that had not been included in the mathematical model, the eventual solution was approved by the persons responsible for specifying the characteristics of the new vehicles. According to the opinion stated by the SUMMA 112's medical group responsible for improving the ambulances (the so-called "coaching group", the outcome was highly satisfactory. Indeed, the final design served as a basis to draw up the requirements of a public tender. Results As a result from solving the Optimization model, a grid was obtained to locate the different necessary materials for the ICUs. This grid had to be slightly altered to meet some requirements that had not been included in the mathematical model. The results were discussed with the persons responsible for specifying the characteristics of the new vehicles. Conclusion The outcome was highly satisfactory. Indeed, the final
A Mixed-Integer Linear Programming approach to wind farm layout and inter-array cable routing
DEFF Research Database (Denmark)
Fischetti, Martina; Leth, John-Josef; Borchersen, Anders Bech
2015-01-01
A Mixed-Integer Linear Programming (MILP) approach is proposed to optimize the turbine allocation and inter-array offshore cable routing. The two problems are considered with a two steps strategy, solving the layout problem first and then the cable problem. We give an introduction to both problems...... and present the MILP models we developed to solve them. To deal with interference in the onshore cases, we propose an adaptation of the standard Jensen’s model, suitable for 3D cases. A simple Stochastic Programming variant of our model allows us to consider different wind scenarios in the optimization...
Canepa, Edward S.
2013-01-01
Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for some decision variable. We use this fact to pose the problem of detecting spoofing cyber-attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offline. A numerical implementation is performed on a cyber-attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © 2013 IEEE.
Canepa, Edward S.
2013-09-01
Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill- Whitham-Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set of traffic flow data generated by multiple sensors of different types, we show that the constraints resulting from this partial differential equation are mixed integer linear inequalities for a specific decision variable. We use this fact to pose the problem of detecting spoofing cyber attacks in probe-based traffic flow information systems as mixed integer linear feasibility problem. The resulting framework can be used to detect spoofing attacks in real time, or to evaluate the worst-case effects of an attack offliine. A numerical implementation is performed on a cyber attack scenario involving experimental data from the Mobile Century experiment and the Mobile Millennium system currently operational in Northern California. © American Institute of Mathematical Sciences.
Directory of Open Access Journals (Sweden)
I Gede Agus Widyadana
2001-01-01
Full Text Available The decisions to choose appropriate tools for solving industrial problems are not just tools that achieve optimal solution only but it should consider computation time too. One of industrial problems that still difficult to achieve both criteria is scheduling problem. This paper discuss comparison between mixed integer programming which result optimal solution and heuristic method to solve job shop scheduling problem with separable sequence-dependent setup. The problems are generated and the result shows that the heuristic methods still cannot satisfy optimal solution.
Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Chen, Xiujuan; Chen, Jiapei
2017-03-01
Due to the existence of complexities of heterogeneities, hierarchy, discreteness, and interactions in municipal solid waste management (MSWM) systems such as Beijing, China, a series of socio-economic and eco-environmental problems may emerge or worsen and result in irredeemable damages in the following decades. Meanwhile, existing studies, especially ones focusing on MSWM in Beijing, could hardly reflect these complexities in system simulations and provide reliable decision support for management practices. Thus, a framework of distributed mixed-integer fuzzy hierarchical programming (DMIFHP) is developed in this study for MSWM under these complexities. Beijing is selected as a representative case. The Beijing MSWM system is comprehensively analyzed in many aspects such as socio-economic conditions, natural conditions, spatial heterogeneities, treatment facilities, and system complexities, building a solid foundation for system simulation and optimization. Correspondingly, the MSWM system in Beijing is discretized as 235 grids to reflect spatial heterogeneity. A DMIFHP model which is a nonlinear programming problem is constructed to parameterize the Beijing MSWM system. To enable scientific solving of it, a solution algorithm is proposed based on coupling of fuzzy programming and mixed-integer linear programming. Innovations and advantages of the DMIFHP framework are discussed. The optimal MSWM schemes and mechanism revelations will be discussed in another companion paper due to length limitation.
The use of mixed-integer programming for inverse treatment planning with pre-defined field segments
International Nuclear Information System (INIS)
Bednarz, Greg; Michalski, Darek; Houser, Chris; Huq, M. Saiful; Xiao Ying; Rani, Pramila Anne; Galvin, James M.
2002-01-01
Complex intensity patterns generated by traditional beamlet-based inverse treatment plans are often very difficult to deliver. In the approach presented in this work the intensity maps are controlled by pre-defining field segments to be used for dose optimization. A set of simple rules was used to define a pool of allowable delivery segments and the mixed-integer programming (MIP) method was used to optimize segment weights. The optimization problem was formulated by combining real variables describing segment weights with a set of binary variables, used to enumerate voxels in targets and critical structures. The MIP method was compared to the previously used Cimmino projection algorithm. The field segmentation approach was compared to an inverse planning system with a traditional beamlet-based beam intensity optimization. In four complex cases of oropharyngeal cancer the segmental inverse planning produced treatment plans, which competed with traditional beamlet-based IMRT plans. The mixed-integer programming provided mechanism for imposition of dose-volume constraints and allowed for identification of the optimal solution for feasible problems. Additional advantages of the segmental technique presented here are: simplified dosimetry, quality assurance and treatment delivery. (author)
International Nuclear Information System (INIS)
Zhang, Jianyun; Liu, Pei; Zhou, Zhe; Ma, Linwei; Li, Zheng; Ni, Weidou
2014-01-01
Highlights: • Integration of heat streams with HRSG in a polygeneration system is studied. • A mixed-integer nonlinear programming model is proposed to optimize heat network. • Operating parameters and heat network configuration are optimized simultaneously. • The optimized heat network highly depends on the HRSG type and model specification. - Abstract: A large number of heat flows at various temperature and pressure levels exist in a polygeneration plant which co-produces electricity and chemical products. Integration of these external heat flows in a heat recovery steam generator (HRSG) has great potential to further enhance energy efficiency of such a plant; however, it is a challenging problem arising from the large design space of heat exchanger network. In this paper, a mixed-integer nonlinear programming model is developed for the design optimization of a HRSG with consideration of all alternative matches between the HRSG and external heat flows. This model is applied to four polygeneration cases with different HRSG types, and results indicate that the optimized heat network mainly depends on the HRSG type and the model specification
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H Kazemipoor
2012-04-01
Full Text Available A multi-skilled project scheduling problem (MSPSP has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time.
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Mbarek Elbounjimi
2015-11-01
Full Text Available Closed-loop supply chain network design is a critical issue due to its impact on both economic and environmental performances of the supply chain. In this paper, we address the problem of designing a multi-echelon, multi-product and capacitated closed-loop supply chain network. First, a mixed-integer linear programming formulation is developed to maximize the total profit. The main contribution of the proposed model is addressing two economic viability issues of closed-loop supply chain. The first issue is the collection of sufficient quantity of end-of-life products are assured by retailers against an acquisition price. The second issue is exploiting the benefits of colocation of forward facilities and reverse facilities. The presented model is solved by LINGO for some test problems. Computational results and sensitivity analysis are conducted to show the performance of the proposed model.
Yin, Sisi; Nishi, Tatsushi
2014-11-01
Quantity discount policy is decision-making for trade-off prices between suppliers and manufacturers while production is changeable due to demand fluctuations in a real market. In this paper, quantity discount models which consider selection of contract suppliers, production quantity and inventory simultaneously are addressed. The supply chain planning problem with quantity discounts under demand uncertainty is formulated as a mixed-integer nonlinear programming problem (MINLP) with integral terms. We apply an outer-approximation method to solve MINLP problems. In order to improve the efficiency of the proposed method, the problem is reformulated as a stochastic model replacing the integral terms by using a normalisation technique. We present numerical examples to demonstrate the efficiency of the proposed method.
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Renata Melo e Silva de Oliveira
2015-03-01
Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests. With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs. The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.
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Akyene Tetteh
2017-04-01
Full Text Available Background: Although the Internet boosts business profitability, without certain activities like efficient transportation, scheduling, products ordered via the Internet may reach their destination very late. The environmental problems (vehicle part disposal, carbon monoxide [CO], nitrogen oxide [NOx] and hydrocarbons [HC] associated with transportation are mostly not accounted for by industries. Objectives: The main objective of this article is to minimising negative externalities cost in e-commerce environments. Method: The 0-1 mixed integer linear programming (0-1 MILP model was used to model the problem statement. The result was further analysed using the externality percentage impact factor (EPIF. Results: The simulation results suggest that (1 The mode of ordering refined petroleum products does not impact on the cost of distribution, (2 an increase in private cost is directly proportional to the externality cost, (3 externality cost is largely controlled by the government and number of vehicles used in the distribution and this is in no way influenced by the mode of request (i.e. Internet or otherwise and (4 externality cost may be reduce by using more ecofriendly fuel system.
Fu, Zhenghui; Wang, Han; Lu, Wentao; Guo, Huaicheng; Li, Wei
2017-12-01
Electric power system involves different fields and disciplines which addressed the economic system, energy system, and environment system. Inner uncertainty of this compound system would be an inevitable problem. Therefore, an inexact multistage fuzzy-stochastic programming (IMFSP) was developed for regional electric power system management constrained by environmental quality. A model which concluded interval-parameter programming, multistage stochastic programming, and fuzzy probability distribution was built to reflect the uncertain information and dynamic variation in the case study, and the scenarios under different credibility degrees were considered. For all scenarios under consideration, corrective actions were allowed to be taken dynamically in accordance with the pre-regulated policies and the uncertainties in reality. The results suggest that the methodology is applicable to handle the uncertainty of regional electric power management systems and help the decision makers to establish an effective development plan.
DEFF Research Database (Denmark)
Ommen, Torben Schmidt; Markussen, Wiebke Brix; Elmegaard, Brian
2014-01-01
In the paper, three frequently used operation optimisation methods are examined with respect to their impact on operation management of the combined utility technologies for electric power and DH (district heating) of eastern Denmark. The investigation focusses on individual plant operation...... differences and differences between the solution found by each optimisation method. One of the investigated approaches utilises LP (linear programming) for optimisation, one uses LP with binary operation constraints, while the third approach uses NLP (non-linear programming). The LP model is used...... as a benchmark, as this type is frequently used, and has the lowest amount of constraints of the three. A comparison of the optimised operation of a number of units shows significant differences between the three methods. Compared to the reference, the use of binary integer variables, increases operation...
An Improved Search Approach for Solving Non-Convex Mixed-Integer Non Linear Programming Problems
Sitopu, Joni Wilson; Mawengkang, Herman; Syafitri Lubis, Riri
2018-01-01
The nonlinear mathematical programming problem addressed in this paper has a structure characterized by a subset of variables restricted to assume discrete values, which are linear and separable from the continuous variables. The strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method, has been developed. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points. Successful implementation of these algorithms was achieved on various test problems.
Li, Yanning
2013-10-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
Li, Yanning; Canepa, Edward S.; Claudel, Christian G.
2013-01-01
This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using boundary flow control, as a Linear Program. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP (or MILP if the objective function depends on boolean variables). Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality. © 2013 IEEE.
Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Chen, Jiapei; Chen, Xiujuan; Li, Kailong
2017-03-01
As presented in the first companion paper, distributed mixed-integer fuzzy hierarchical programming (DMIFHP) was developed for municipal solid waste management (MSWM) under complexities of heterogeneities, hierarchy, discreteness, and interactions. Beijing was selected as a representative case. This paper focuses on presenting the obtained schemes and the revealed mechanisms of the Beijing MSWM system. The optimal MSWM schemes for Beijing under various solid waste treatment policies and their differences are deliberated. The impacts of facility expansion, hierarchy, and spatial heterogeneities and potential extensions of DMIFHP are also discussed. A few of findings are revealed from the results and a series of comparisons and analyses. For instance, DMIFHP is capable of robustly reflecting these complexities in MSWM systems, especially for Beijing. The optimal MSWM schemes are of fragmented patterns due to the dominant role of the proximity principle in allocating solid waste treatment resources, and they are closely related to regulated ratios of landfilling, incineration, and composting. Communities without significant differences among distances to different types of treatment facilities are more sensitive to these ratios than others. The complexities of hierarchy and heterogeneities pose significant impacts on MSWM practices. Spatial dislocation of MSW generation rates and facility capacities caused by unreasonable planning in the past may result in insufficient utilization of treatment capacities under substantial influences of transportation costs. The problems of unreasonable MSWM planning, e.g., severe imbalance among different technologies and complete vacancy of ten facilities, should be gained deliberation of the public and the municipal or local governments in Beijing. These findings are helpful for gaining insights into MSWM systems under these complexities, mitigating key challenges in the planning of these systems, improving the related management
Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A
2016-03-01
In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/. © 2016 Wiley Periodicals, Inc.
International Nuclear Information System (INIS)
Mashayekh, Salman; Stadler, Michael; Cardoso, Gonçalo; Heleno, Miguel
2017-01-01
Highlights: • This paper presents a MILP model for optimal design of multi-energy microgrids. • Our microgrid design includes optimal technology portfolio, placement, and operation. • Our model includes microgrid electrical power flow and heat transfer equations. • The case study shows advantages of our model over aggregate single-node approaches. • The case study shows the accuracy of the integrated linearized power flow model. - Abstract: Optimal microgrid design is a challenging problem, especially for multi-energy microgrids with electricity, heating, and cooling loads as well as sources, and multiple energy carriers. To address this problem, this paper presents an optimization model formulated as a mixed-integer linear program, which determines the optimal technology portfolio, the optimal technology placement, and the associated optimal dispatch, in a microgrid with multiple energy types. The developed model uses a multi-node modeling approach (as opposed to an aggregate single-node approach) that includes electrical power flow and heat flow equations, and hence, offers the ability to perform optimal siting considering physical and operational constraints of electrical and heating/cooling networks. The new model is founded on the existing optimization model DER-CAM, a state-of-the-art decision support tool for microgrid planning and design. The results of a case study that compares single-node vs. multi-node optimal design for an example microgrid show the importance of multi-node modeling. It has been shown that single-node approaches are not only incapable of optimal DER placement, but may also result in sub-optimal DER portfolio, as well as underestimation of investment costs.
Jonrinaldi, Hadiguna, Rika Ampuh; Salastino, Rades
2017-11-01
Environmental consciousness has paid many attention nowadays. It is not only about how to recycle, remanufacture or reuse used end products but it is also how to optimize the operations of the reverse system. A previous research has proposed a design of reverse supply chain of biodiesel network from used cooking oil. However, the research focused on the design of the supply chain strategy not the operations of the supply chain. It only decided how to design the structure of the supply chain in the next few years, and the process of each stage will be conducted in the supply chain system in general. The supply chain system has not considered operational policies to be conducted by the companies in the supply chain. Companies need a policy for each stage of the supply chain operations to be conducted so as to produce the optimal supply chain system, including how to use all the resources that have been designed in order to achieve the objectives of the supply chain system. Therefore, this paper proposes a model to optimize the operational planning of a biodiesel supply chain network from used cooking oil. A mixed integer linear programming is developed to model the operational planning of biodiesel supply chain in order to minimize the total operational cost of the supply chain. Based on the implementation of the model developed, the total operational cost of the biodiesel supply chain incurred by the system is less than the total operational cost of supply chain based on the previous research during seven days of operational planning about amount of 2,743,470.00 or 0.186%. Production costs contributed to 74.6 % of total operational cost and the cost of purchasing the used cooking oil contributed to 24.1 % of total operational cost. So, the system should pay more attention to these two aspects as changes in the value of these aspects will cause significant effects to the change in the total operational cost of the supply chain.
A fuzzy-stochastic power system planning model: Reflection of dual objectives and dual uncertainties
International Nuclear Information System (INIS)
Zhang, X.Y.; Huang, G.H.; Zhu, H.; Li, Y.P.
2017-01-01
In this study, a fuzzy stochastic dynamic fractional programming (FSDFP) method is proposed for supporting sustainable management of electric power system (EPS) under dual uncertainties. As an improvement upon the mixed-integer linear fractional programming, FSDFP can not only tackle multi-objective issues effectively without setting weights, but also can deal with uncertain parameters which have both stochastic and fuzzy characteristics. Thus, the developed method can help provide valuable information for supporting capacity-expansion planning and in-depth policy analysis of EPS management problems. For demonstrating these advantages, FSDFP has been applied to a case study of a typical regional EPS planning, where the decision makers have to deal with conflicts between economic development that maximizes the system profit and environmental protection that minimizes the carbon dioxide emissions. The obtained results can be analyzed to generate several decision alternatives, and can then help decision makers make suitable decisions under different input scenarios. Furthermore, comparisons of the solution from FSDFP method with that from fuzzy stochastic dynamic linear programming, linear fractional programming and dynamic stochastic fractional programming methods are undertaken. The contrastive analysis reveals that FSDFP is a more effective approach that can better characterize the complexities and uncertainties of real EPS management problems. - Highlights: • A fuzzy stochastic dynamic fractional programming (FSDFP) method is proposed. • FSDFP can address multiple conflicting objectives without setting weights. • FSDFP can reflect dual uncertainties with both stochastic and fuzzy characteristics. • Some reasonable solutions for a case of power system sustainable planning are generated. • Comparisons of the solutions from FSDFP with other optimization methods are undertaken.
Urselmann, Maren; Emmerich, Michael T. M.; Till, Jochen; Sand, Guido; Engell, Sebastian
2007-07-01
Engineering optimization often deals with large, mixed-integer search spaces with a rigid structure due to the presence of a large number of constraints. Metaheuristics, such as evolutionary algorithms (EAs), are frequently suggested as solution algorithms in such cases. In order to exploit the full potential of these algorithms, it is important to choose an adequate representation of the search space and to integrate expert-knowledge into the stochastic search operators, without adding unnecessary bias to the search. Moreover, hybridisation with mathematical programming techniques such as mixed-integer programming (MIP) based on a problem decomposition can be considered for improving algorithmic performance. In order to design problem-specific EAs it is desirable to have a set of design guidelines that specify properties of search operators and representations. Recently, a set of guidelines has been proposed that gives rise to so-called Metric-based EAs (MBEAs). Extended by the minimal moves mutation they allow for a generalization of EA with self-adaptive mutation strength in discrete search spaces. In this article, a problem-specific EA for process engineering task is designed, following the MBEA guidelines and minimal moves mutation. On the background of the application, the usefulness of the design framework is discussed, and further extensions and corrections proposed. As a case-study, a two-stage stochastic programming problem in chemical batch process scheduling is considered. The algorithm design problem can be viewed as the choice of a hierarchical decision structure, where on different layers of the decision process symmetries and similarities can be exploited for the design of minimal moves. After a discussion of the design approach and its instantiation for the case-study, the resulting problem-specific EA/MIP is compared to a straightforward application of a canonical EA/MIP and to a monolithic mathematical programming algorithm. In view of the
International Nuclear Information System (INIS)
Wang, Xingwei; Cai, Yanpeng; Chen, Jiajun; Dai, Chao
2013-01-01
In this study, a GFIPMIP (grey-forecasting interval-parameter mixed-integer programming) approach was developed for supporting IEEM (integrated electric-environmental management) in Beijing. It was an attempt to incorporate an energy-forecasting model within a general modeling framework at the municipal level. The developed GFIPMIP model can not only forecast electric demands, but also reflect dynamic, interactive, and uncertain characteristics of the IEEM system in Beijing. Moreover, it can address issues regarding power supply, and emission reduction of atmospheric pollutants and GHG (greenhouse gas). Optimal solutions were obtained related to power generation patterns and facility capacity expansion schemes under a series of system constraints. Two scenarios were analyzed based on multiple environmental policies. The results were useful for helping decision makers identify desired management strategies to guarantee the city's power supply and mitigate emissions of GHG and atmospheric pollutants. The results also suggested that the developed GFIPMIP model be applicable to similar engineering problems. - Highlights: • A grey-forecasting interval-parameter mixed integer programming (GFIPMIP) approach was developed. • It could reflect dynamic, interactive, and uncertain characteristics of an IEEM system. • The developed GFIPMIP approach was used for supporting IEEM system planning in Beijing. • Two scenarios were established based on different environmental policies and management targets. • Optimal schemes for power generation, energy supply, and environmental protection were identified
Directory of Open Access Journals (Sweden)
Jing Liu
2017-11-01
Full Text Available In this study, an interval fuzzy-stochastic chance-constrained programming based energy-water nexus (IFSCP-WEN model is developed for planning electric power system (EPS. The IFSCP-WEN model can tackle uncertainties expressed as possibility and probability distributions, as well as interval values. Different credibility (i.e., γ levels and probability (i.e., qi levels are set to reflect relationships among water supply, electricity generation, system cost, and constraint-violation risk. Results reveal that different γ and qi levels can lead to a changed system cost, imported electricity, electricity generation, and water supply. Results also disclose that the study EPS would tend to the transition from coal-dominated into clean energy-dominated. Gas-fired would be the main electric utility to supply electricity at the end of the planning horizon, occupying [28.47, 30.34]% (where 28.47% and 30.34% present the lower bound and the upper bound of interval value, respectively of the total electricity generation. Correspondingly, water allocated to gas-fired would reach the highest, occupying [33.92, 34.72]% of total water supply. Surface water would be the main water source, accounting for more than [40.96, 43.44]% of the total water supply. The ratio of recycled water to total water supply would increase by about [11.37, 14.85]%. Results of the IFSCP-WEN model present its potential for sustainable EPS planning by co-optimizing energy and water resources.
Energy Technology Data Exchange (ETDEWEB)
Waddell, Lucas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Muldoon, Frank [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Henry, Stephen Michael [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hoffman, Matthew John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zwerneman, April Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Backlund, Peter [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melander, Darryl J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lawton, Craig R. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rice, Roy Eugene [Teledyne Brown Engineering, Huntsville, AL (United States)
2017-09-01
In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor- ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.
Irmeilyana, Puspita, Fitri Maya; Indrawati
2016-02-01
The pricing for wireless networks is developed by considering linearity factors, elasticity price and price factors. Mixed Integer Nonlinear Programming of wireless pricing model is proposed as the nonlinear programming problem that can be solved optimally using LINGO 13.0. The solutions are expected to give some information about the connections between the acceptance factor and the price. Previous model worked on the model that focuses on bandwidth as the QoS attribute. The models attempt to maximize the total price for a connection based on QoS parameter. The QoS attributes used will be the bandwidth and the end to end delay that affect the traffic. The maximum goal to maximum price is achieved when the provider determine the requirement for the increment or decrement of price change due to QoS change and amount of QoS value.
Mixed integer evolution strategies for parameter optimization.
Li, Rui; Emmerich, Michael T M; Eggermont, Jeroen; Bäck, Thomas; Schütz, M; Dijkstra, J; Reiber, J H C
2013-01-01
Evolution strategies (ESs) are powerful probabilistic search and optimization algorithms gleaned from biological evolution theory. They have been successfully applied to a wide range of real world applications. The modern ESs are mainly designed for solving continuous parameter optimization problems. Their ability to adapt the parameters of the multivariate normal distribution used for mutation during the optimization run makes them well suited for this domain. In this article we describe and study mixed integer evolution strategies (MIES), which are natural extensions of ES for mixed integer optimization problems. MIES can deal with parameter vectors consisting not only of continuous variables but also with nominal discrete and integer variables. Following the design principles of the canonical evolution strategies, they use specialized mutation operators tailored for the aforementioned mixed parameter classes. For each type of variable, the choice of mutation operators is governed by a natural metric for this variable type, maximal entropy, and symmetry considerations. All distributions used for mutation can be controlled in their shape by means of scaling parameters, allowing self-adaptation to be implemented. After introducing and motivating the conceptual design of the MIES, we study the optimality of the self-adaptation of step sizes and mutation rates on a generalized (weighted) sphere model. Moreover, we prove global convergence of the MIES on a very general class of problems. The remainder of the article is devoted to performance studies on artificial landscapes (barrier functions and mixed integer NK landscapes), and a case study in the optimization of medical image analysis systems. In addition, we show that with proper constraint handling techniques, MIES can also be applied to classical mixed integer nonlinear programming problems.
Fuzzy stochastic multiobjective programming
Sakawa, Masatoshi; Katagiri, Hideki
2011-01-01
With a stress on interactive decision-making, this work breaks new ground by covering both the random nature of events related to environments, and the fuzziness of human judgements. The text runs from mathematical preliminaries to future research directions.
Chen, Pei-Hua
2017-05-01
This rejoinder responds to the commentary by van der Linden and Li entiled "Comment on Three-Element Item Selection Procedures for Multiple Forms Assembly: An Item Matching Approach" on the article "Three-Element Item Selection Procedures for Multiple Forms Assembly: An Item Matching Approach" by Chen. Van der Linden and Li made a strong statement calling for the cessation of test assembly heuristics development, and instead encouraged embracing mixed integer programming (MIP). This article points out the nondeterministic polynomial (NP)-hard nature of MIP problems and how solutions found using heuristics could be useful in an MIP context. Although van der Linden and Li provided several practical examples of test assembly supporting their view, the examples ignore the cases in which a slight change of constraints or item pool data might mean it would not be possible to obtain solutions as quickly as before. The article illustrates the use of heuristic solutions to improve both the performance of MIP solvers and the quality of solutions. Additional responses to the commentary by van der Linden and Li are included.
International Nuclear Information System (INIS)
Wouters, Carmen; Fraga, Eric S.; James, Adrian M.
2015-01-01
The integration of distributed generation units and microgrids in the current grid infrastructure requires an efficient and cost effective local energy system design. A mixed-integer linear programming model is presented to identify such optimal design. The electricity as well as the space heating and cooling demands of a small residential neighbourhood are satisfied through the consideration and combined use of distributed generation technologies, thermal units and energy storage with an optional interconnection with the central grid. Moreover, energy integration is allowed in the form of both optimised pipeline networks and microgrid operation. The objective is to minimise the total annualised cost of the system to meet its yearly energy demand. The model integrates the operational characteristics and constraints of the different technologies for several scenarios in a South Australian setting and is implemented in GAMS. The impact of energy integration is analysed, leading to the identification of key components for residential energy systems. Additionally, a multi-microgrid concept is introduced to allow for local clustering of households within neighbourhoods. The robustness of the model is shown through sensitivity analysis, up-scaling and an effort to address the variability of solar irradiation. - Highlights: • Distributed energy system planning is employed on a small residential scale. • Full energy integration is employed based on microgrid operation and tri-generation. • An MILP for local clustering of households in multi-microgrids is developed. • Micro combined heat and power units are key components for residential microgrids
2013-01-01
that these constraints can often lead to significant reductions in the gap between the optimal solution and its non-integral linear programming bound relative to the prior art as well as often substantially faster processing of moderately hard problem instances. Conclusion We provide an indication of the conditions under which such an optimal enumeration approach is likely to be feasible, suggesting that these strategies are usable for relatively large numbers of taxa, although with stricter limits on numbers of variable sites. The work thus provides methodology suitable for provably optimal solution of some harder instances that resist all prior approaches. PMID:23343437
Energy Technology Data Exchange (ETDEWEB)
Koa, A.S.; Chang, N.B. [University of Central Florida, Orlando, FL (United States). Dept. for Civil & Environmental Engineering
2008-07-15
Energy supply and use is of fundamental importance to society. Although the interactions between energy and environment were originally local in character, they have now widened to cover regional and global issues, such as acid rain and the greenhouse effect. It is for this reason that there is a need for covering the direct and indirect economic and environmental impacts of energy acquisition, transport, production and use. In this paper, particular attention is directed to ways of resolving conflict between economic and environmental goals by encouraging a power plant to consider co-firing biomass and refuse-derived fuel (RDF) with coal simultaneously. It aims at reducing the emission level of sulfur dioxide (SO{sub 2}) in an uncertain environment, using the power plant in Michigan City, Indiana as an example. To assess the uncertainty by a comparative way both deterministic and grey nonlinear mixed integer programming (MIP) models were developed to minimize the net operating cost with respect to possible fuel combinations. It aims at generating the optimal portfolio of alternative fuels while maintaining the same electricity generation simultaneously. To case the solution procedure stepwise relaxation algorithm was developed for solving the grey nonlinear MIP model. Breakeven alternative fuel value can be identified in the post-optimization stage for decision-making. Research findings show that the inclusion of RDF does not exhibit comparative advantage in terms of the net cost, albeit relatively lower air pollution impact. Yet it can be sustained by a charge system, subsidy program, or emission credit as the price of coal increases over time.
Ko, Andi Setiady; Chang, Ni-Bin
2008-07-01
Energy supply and use is of fundamental importance to society. Although the interactions between energy and environment were originally local in character, they have now widened to cover regional and global issues, such as acid rain and the greenhouse effect. It is for this reason that there is a need for covering the direct and indirect economic and environmental impacts of energy acquisition, transport, production and use. In this paper, particular attention is directed to ways of resolving conflict between economic and environmental goals by encouraging a power plant to consider co-firing biomass and refuse-derived fuel (RDF) with coal simultaneously. It aims at reducing the emission level of sulfur dioxide (SO(2)) in an uncertain environment, using the power plant in Michigan City, Indiana as an example. To assess the uncertainty by a comparative way both deterministic and grey nonlinear mixed integer programming (MIP) models were developed to minimize the net operating cost with respect to possible fuel combinations. It aims at generating the optimal portfolio of alternative fuels while maintaining the same electricity generation simultaneously. To ease the solution procedure stepwise relaxation algorithm was developed for solving the grey nonlinear MIP model. Breakeven alternative fuel value can be identified in the post-optimization stage for decision-making. Research findings show that the inclusion of RDF does not exhibit comparative advantage in terms of the net cost, albeit relatively lower air pollution impact. Yet it can be sustained by a charge system, subsidy program, or emission credit as the price of coal increases over time.
Zeng, X T; Huang, G H; Li, Y P; Zhang, J L; Cai, Y P; Liu, Z P; Liu, L R
2016-12-01
This study developed a fuzzy-stochastic programming with Green Z-score criterion (FSGZ) method for water resources allocation and water quality management with a trading-mechanism (WAQT) under uncertainties. FSGZ can handle uncertainties expressed as probability distributions, and it can also quantify objective/subjective fuzziness in the decision-making process. Risk-averse attitudes and robustness coefficient are joined to express the relationship between the expected target and outcome under various risk preferences of decision makers and systemic robustness. The developed method is applied to a real-world case of WAQT in the Kaidu-Kongque River Basin in northwest China, where an effective mechanism (e.g., market trading) to simultaneously confront severely diminished water availability and degraded water quality is required. Results of water transaction amounts, water allocation patterns, pollution mitigation schemes, and system benefits under various scenarios are analyzed, which indicate that a trading-mechanism is a more sustainable method to manage water-environment crisis in the study region. Additionally, consideration of anthropogenic (e.g., a risk-averse attitude) and systemic factors (e.g., the robustness coefficient) can support the generation of a robust plan associated with risk control for WAQT when uncertainty is present. These findings assist local policy and decision makers to gain insights into water-environment capacity planning to balance the basin's social and economic growth with protecting the region's ecosystems.
International Nuclear Information System (INIS)
Yu, L.; Li, Y.P.; Huang, G.H.
2016-01-01
In this study, a FSSOM (fuzzy-stochastic simulation-optimization model) is developed for planning EPS (electric power systems) with considering peak demand under uncertainty. FSSOM integrates techniques of SVR (support vector regression), Monte Carlo simulation, and FICMP (fractile interval chance-constrained mixed-integer programming). In FSSOM, uncertainties expressed as fuzzy boundary intervals and random variables can be effectively tackled. In addition, SVR coupled Monte Carlo technique is used for predicting the peak-electricity demand. The FSSOM is applied to planning EPS for the City of Qingdao, China. Solutions of electricity generation pattern to satisfy the city's peak demand under different probability levels and p-necessity levels have been generated. Results reveal that the city's electricity supply from renewable energies would be low (only occupying 8.3% of the total electricity generation). Compared with the energy model without considering peak demand, the FSSOM can better guarantee the city's power supply and thus reduce the system failure risk. The findings can help decision makers not only adjust the existing electricity generation/supply pattern but also coordinate the conflict interaction among system cost, energy supply security, pollutant mitigation, as well as constraint-violation risk. - Highlights: • FSSOM (Fuzzy-stochastic simulation-optimization model) is developed for planning EPS. • It can address uncertainties as fuzzy-boundary intervals and random variables. • FSSOM can satisfy peak-electricity demand and optimize power allocation. • Solutions under different probability levels and p-necessity levels are analyzed. • Results create tradeoff among system cost and peak-electricity demand violation risk.
Fuzzy stochastic damage mechanics (FSDM based on fuzzy auto-adaptive control theory
Directory of Open Access Journals (Sweden)
Ya-jun Wang
2012-06-01
Full Text Available In order to fully interpret and describe damage mechanics, the origin and development of fuzzy stochastic damage mechanics were introduced based on the analysis of the harmony of damage, probability, and fuzzy membership in the interval of [0,1]. In a complete normed linear space, it was proven that a generalized damage field can be simulated through β probability distribution. Three kinds of fuzzy behaviors of damage variables were formulated and explained through analysis of the generalized uncertainty of damage variables and the establishment of a fuzzy functional expression. Corresponding fuzzy mapping distributions, namely, the half-depressed distribution, swing distribution, and combined swing distribution, which can simulate varying fuzzy evolution in diverse stochastic damage situations, were set up. Furthermore, through demonstration of the generalized probabilistic characteristics of damage variables, the cumulative distribution function and probability density function of fuzzy stochastic damage variables, which show β probability distribution, were modified according to the expansion principle. The three-dimensional fuzzy stochastic damage mechanical behaviors of the Longtan rolled-concrete dam were examined with the self-developed fuzzy stochastic damage finite element program. The statistical correlation and non-normality of random field parameters were considered comprehensively in the fuzzy stochastic damage model described in this paper. The results show that an initial damage field based on the comprehensive statistical evaluation helps to avoid many difficulties in the establishment of experiments and numerical algorithms for damage mechanics analysis.
Fuzzy Stochastic Optimization Theory, Models and Applications
Wang, Shuming
2012-01-01
Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...
Directory of Open Access Journals (Sweden)
Jiafu Yin
2018-02-01
Full Text Available With the increasing penetration of wind power and demand response integrated into the grid, the combined uncertainties from wind power and demand response have been a challenging concern for system operators. It is necessary to develop an approach to accommodate the combined uncertainties in the source side and load side. In this paper, the fuzzy stochastic conditional value-at-risk criterions are proposed as the risk measure of the combination of both wind power uncertainty and demand response uncertainty. To improve the computational tractability without sacrificing the accuracy, the fuzzy stochastic chance-constrained goal programming is proposed to transfer the fuzzy stochastic conditional value-at-risk to a deterministic equivalent. The operational risk of forecast error under fuzzy stochastic conditional value-at-risk assessment is represented by the shortage of reserve resource, which can be further divided into the load-shedding risk and the wind curtailment risk. To identify different priority levels for the different objective functions, the three-stage day-ahead unit commitment model is proposed through preemptive goal programming, in which the reliability requirement has the priority over the economic operation. Finally, a case simulation is performed on the IEEE 39-bus system to verify the effectiveness and efficiency of the proposed model.
Bipartite Fuzzy Stochastic Differential Equations with Global Lipschitz Condition
Directory of Open Access Journals (Sweden)
Marek T. Malinowski
2016-01-01
Full Text Available We introduce and analyze a new type of fuzzy stochastic differential equations. We consider equations with drift and diffusion terms occurring at both sides of equations. Therefore we call them the bipartite fuzzy stochastic differential equations. Under the Lipschitz and boundedness conditions imposed on drifts and diffusions coefficients we prove existence of a unique solution. Then, insensitivity of the solution under small changes of data of equation is examined. Finally, we mention that all results can be repeated for solutions to bipartite set-valued stochastic differential equations.
Mixed-integer nonlinear approach for the optimal scheduling of a head-dependent hydro chain
Energy Technology Data Exchange (ETDEWEB)
Catalao, J.P.S.; Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)
2010-08-15
This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain. We propose a novel mixed-integer nonlinear programming (MINLP) approach, considering hydroelectric power generation as a nonlinear function of water discharge and of the head. As a new contribution to earlier studies, we model the on-off behavior of the hydro plants using integer variables, in order to avoid water discharges at forbidden areas. Thus, an enhanced STHS is provided due to the more realistic modeling presented in this paper. Our approach has been applied successfully to solve a test case based on one of the Portuguese cascaded hydro systems with a negligible computational time requirement. (author)
Mixed-integer representations in control design mathematical foundations and applications
Prodan, Ionela; Olaru, Sorin; Niculescu, Silviu-Iulian
2016-01-01
In this book, the authors propose efficient characterizations of the non-convex regions that appear in many control problems, such as those involving collision/obstacle avoidance and, in a broader sense, in the description of feasible sets for optimization-based control design involving contradictory objectives. The text deals with a large class of systems that require the solution of appropriate optimization problems over a feasible region, which is neither convex nor compact. The proposed approach uses the combinatorial notion of hyperplane arrangement, partitioning the space by a finite collection of hyperplanes, to describe non-convex regions efficiently. Mixed-integer programming techniques are then applied to propose acceptable formulations of the overall problem. Multiple constructions may arise from the same initial problem, and their complexity under various parameters - space dimension, number of binary variables, etc. - is also discussed. This book is a useful tool for academic researchers and grad...
Stochastic Dynamic Mixed-Integer Programming (SD-MIP)
2015-05-05
et al (2009), there is continuing interest in using SA methods for SP problems. This genre of methods creates a sequence of sampled subgradients...Sampling and Convergence) In current sampling-based methods motivated by Benders’ decomposition the essential role of sampling is to reduce the number of...Kleywegt, A, Shapiro, A, and Homem- de -Mello, T, (2002) SIAM Journal on Optimization archive, vol. 12Journal SIAM Journal on Optimization archive
Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks
Lee, Charles H.; Cheung, Kar-Ming
2012-01-01
In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.
Combinatorial therapy discovery using mixed integer linear programming.
Pang, Kaifang; Wan, Ying-Wooi; Choi, William T; Donehower, Lawrence A; Sun, Jingchun; Pant, Dhruv; Liu, Zhandong
2014-05-15
Combinatorial therapies play increasingly important roles in combating complex diseases. Owing to the huge cost associated with experimental methods in identifying optimal drug combinations, computational approaches can provide a guide to limit the search space and reduce cost. However, few computational approaches have been developed for this purpose, and thus there is a great need of new algorithms for drug combination prediction. Here we proposed to formulate the optimal combinatorial therapy problem into two complementary mathematical algorithms, Balanced Target Set Cover (BTSC) and Minimum Off-Target Set Cover (MOTSC). Given a disease gene set, BTSC seeks a balanced solution that maximizes the coverage on the disease genes and minimizes the off-target hits at the same time. MOTSC seeks a full coverage on the disease gene set while minimizing the off-target set. Through simulation, both BTSC and MOTSC demonstrated a much faster running time over exhaustive search with the same accuracy. When applied to real disease gene sets, our algorithms not only identified known drug combinations, but also predicted novel drug combinations that are worth further testing. In addition, we developed a web-based tool to allow users to iteratively search for optimal drug combinations given a user-defined gene set. Our tool is freely available for noncommercial use at http://www.drug.liuzlab.org/. zhandong.liu@bcm.edu Supplementary data are available at Bioinformatics online.
Mixed-Integer Conic Linear Programming: Challenges and Perspectives
2013-10-01
The novel DCCs for MISOCO may be used in branch- and-cut algorithms when solving MISOCO problems. The experimental software CICLO was developed to...perform limited, but rigorous computational experiments. The CICLO solver utilizes continuous SOCO solvers, MOSEK, CPLES or SeDuMi, builds on the open...submitted Fall 2013. Software: 1. CICLO : Integer conic linear optimization package. Authors: J.C. Góez, T.K. Ralphs, Y. Fu, and T. Terlaky
Directory of Open Access Journals (Sweden)
Deisemara Ferreira
2008-01-01
Full Text Available Neste artigo propomos um modelo de otimização inteira mista para o problema de dimensionamento e seqüenciamento dos lotes de produção em fábricas de refrigerantes de pequeno porte, com tempos e custos de set up de produção dependentes do seqüenciamento dos lotes. O modelo considera o estágio de envase como sendo o gargalo da produção da planta, o que é comum em fábricas de pequeno porte com uma única linha de envase, e restrições de lote mínimo do estágio de xaroparia. Variações da heurística relax and fix são propostas e comparadas na solução de exemplares do modelo, gerados com dados reais de uma fábrica localizada no interior do Estado de São Paulo. Os resultados mostram que as abordagens são capazes de gerar soluções melhores do que as utilizadas pela empresa.In this paper we propose a mixed integer programming model to the lot sizing and sequencing problem of a soft drink plant with sequence-dependent set up costs and times. The model considers that the bottling stage is the production bottleneck, which is common in small plants with only one production line, and minimum lot size constrains of the syrup stage. Variations of the relax and fix heuristic are proposed and compared. A computational study with instances generated based on real data from a plant situated in the State of São Paulo-Brazil is also presented. The results show that the approaches are capable to produce better solutions than the ones from the company.
Presolving and regularization in mixed-integer second-order cone optimization
DEFF Research Database (Denmark)
Friberg, Henrik Alsing
Mixed-integer second-order cone optimization is a powerful mathematical framework capable of representing both logical conditions and nonlinear relationships in mathematical models of industrial optimization problems. What is more, solution methods are already part of many major commercial solvers...... both continuous and mixed-integer conic optimization in general, is discovered and treated. This part of the thesis continues the studies of facial reduction preceding the work of Borwein and Wolkowicz [17] in 1981, when the first algorithmic cure for these kinds of reliability issues were formulated....... An important distinction to make between continuous and mixed-integer optimization, however, is that the reliability issues occurring in mixed-integer optimization cannot be blamed on the practitioner’s formulation of the problem. Specifically, as shown, the causes for these issues may well lie within...
Directory of Open Access Journals (Sweden)
Alexander Abuabara
2008-12-01
Full Text Available Este trabalho busca otimizar o planejamento do processo de corte unidimensional de tubos estruturais metálicos utilizados na fabricação de aeronaves leves agrícolas. Dois modelos de programação linear inteira mista são apresentados com o objetivo de minimizar as perdas do material cortado e considerando a possibilidade de gerar sobras com tamanhos suficientes para reaproveitamento (retalhos. Os modelos são resolvidos por meio de uma linguagem de modelagem usando um software de otimização. Para a validação dos modelos, dois experimentos computacionais foram realizados com dados reais de uma carteira de pedidos de uma aeronave leve voltada para o segmento do mercado agrícola, o Ipanema, produzido pela empresa brasileira Neiva/Embraer. As soluções dos modelos são comparadas com as soluções de uma heurística residual de arredondamento guloso da literatura e também com as soluções utilizadas pela empresa. Os resultados mostram que os modelos são úteis para apoiar as decisões envolvidas no planejamento deste processo de corte.This study aims to optimize the one-dimensional cutting process planning of structural metallic tubes used to build agricultural light aircrafts. Two mixed integer linear programming models are presented to minimize the waste of material cut and considering the possibility of generating surpluses with sizes sufficiently large for reuse (leftovers. The models are solved using a commercial modeling language and an optimization solver. For the validation of the models, two computational experiments were performed with actual data from the portfolio of a light aircraft designed for agricultural purposes, the Ipanema, produced by the Brazilian company Neiva/Embraer. The solutions of the models are compared with the solutions of a constructive heuristic of the literature and the solutions used by the company. The results show that the models are useful for being used in the planning of this cutting process.
Directory of Open Access Journals (Sweden)
Sílvia Maria Santana Mapa
2012-01-01
Full Text Available O objetivo do trabalho é avaliar a qualidade das soluções para o problema de localização-alocação de instalações geradas por um SIG-T (Sistema de Informação Geográfica para Transportes, obtidas após a utilização combinada das rotinas Localização de Facilidades e Problema do Transporte, quando comparadas com as soluções ótimas obtidas a partir de modelo matemático exato baseado em Programação Linear Inteira Mista (PLIM, desenvolvido externamente ao SIG. Os modelos foram aplicados a três simulações: a primeira propõe a abertura de fábricas e alocação de clientes no Estado de São Paulo; a segunda envolve um atacadista e um estudo de localização de centros de distribuição e alocação dos clientes varejistas; a terceira localiza creches em um contexto urbano, alocando a demanda. Os resultados mostraram que, quando se considera a capacidade das instalações, o modelo otimizante PLIM chegou a apresentar, em um dos cenários simulados, resultados até 37% melhores do que o SIG, além de propor locais diferentes para abertura de novas instalações. Quando não se considera a capacidade, o modelo SIG se mostrou tão eficiente quanto o modelo exato PLIM, chegando exatamente às mesmas soluções.This study aims to evaluate the quality of the solutions for facility location-allocation problems generated by a GIS-T (Geographic Information System for Transportation software. These solutions were obtained from combining the Facility Location and Transportation Problem routines, when compared with the optimal solutions, which were obtained using the exact mathematical model based on the Mixed Integer Linear Programming (MILP developed externally to the GIS. The models were applied to three simulations: the first one proposes set up businesses and customers' allocation in the state of São Paulo; the second involves a wholesaler and an investigation of distribution center location and retailers' allocation; and the third one
CBLIB 2014: a benchmark library for conic mixed-integer and continuous optimization
DEFF Research Database (Denmark)
Friberg, Henrik Alsing
2016-01-01
The Conic Benchmark Library is an ongoing community-driven project aiming to challenge commercial and open source solvers on mainstream cone support. In this paper, 121 mixed-integer and continuous second-order cone problem instances have been selected from 11 categories as representative...
Li, Rui
2009-01-01
The target of this work is to extend the canonical Evolution Strategies (ES) from traditional real-valued parameter optimization domain to mixed-integer parameter optimization domain. This is necessary because there exist numerous practical optimization problems from industry in which the set of
Obstacle avoidance handling and mixed integer predictive control for space robots
Zong, Lijun; Luo, Jianjun; Wang, Mingming; Yuan, Jianping
2018-04-01
This paper presents a novel obstacle avoidance constraint and a mixed integer predictive control (MIPC) method for space robots avoiding obstacles and satisfying physical limits during performing tasks. Firstly, a novel kind of obstacle avoidance constraint of space robots, which needs the assumption that the manipulator links and the obstacles can be represented by convex bodies, is proposed by limiting the relative velocity between two closest points which are on the manipulator and the obstacle, respectively. Furthermore, the logical variables are introduced into the obstacle avoidance constraint, which have realized the constraint form is automatically changed to satisfy different obstacle avoidance requirements in different distance intervals between the space robot and the obstacle. Afterwards, the obstacle avoidance constraint and other system physical limits, such as joint angle ranges, the amplitude boundaries of joint velocities and joint torques, are described as inequality constraints of a quadratic programming (QP) problem by using the model predictive control (MPC) method. To guarantee the feasibility of the obtained multi-constraint QP problem, the constraints are treated as soft constraints and assigned levels of priority based on the propositional logic theory, which can realize that the constraints with lower priorities are always firstly violated to recover the feasibility of the QP problem. Since the logical variables have been introduced, the optimization problem including obstacle avoidance and system physical limits as prioritized inequality constraints is termed as MIPC method of space robots, and its computational complexity as well as possible strategies for reducing calculation amount are analyzed. Simulations of the space robot unfolding its manipulator and tracking the end-effector's desired trajectories with the existence of obstacles and physical limits are presented to demonstrate the effectiveness of the proposed obstacle avoidance
Roy, Satadru
Traditional approaches to design and optimize a new system, often, use a system-centric objective and do not take into consideration how the operator will use this new system alongside of other existing systems. This "hand-off" between the design of the new system and how the new system operates alongside other systems might lead to a sub-optimal performance with respect to the operator-level objective. In other words, the system that is optimal for its system-level objective might not be best for the system-of-systems level objective of the operator. Among the few available references that describe attempts to address this hand-off, most follow an MDO-motivated subspace decomposition approach of first designing a very good system and then provide this system to the operator who decides the best way to use this new system along with the existing systems. The motivating example in this dissertation presents one such similar problem that includes aircraft design, airline operations and revenue management "subspaces". The research here develops an approach that could simultaneously solve these subspaces posed as a monolithic optimization problem. The monolithic approach makes the problem a Mixed Integer/Discrete Non-Linear Programming (MINLP/MDNLP) problem, which are extremely difficult to solve. The presence of expensive, sophisticated engineering analyses further aggravate the problem. To tackle this challenge problem, the work here presents a new optimization framework that simultaneously solves the subspaces to capture the "synergism" in the problem that the previous decomposition approaches may not have exploited, addresses mixed-integer/discrete type design variables in an efficient manner, and accounts for computationally expensive analysis tools. The framework combines concepts from efficient global optimization, Kriging partial least squares, and gradient-based optimization. This approach then demonstrates its ability to solve an 11 route airline network
Optimal Airport Surface Traffic Planning Using Mixed-Integer Linear Programming
Roling, P.C.; Visser, H.G.
2008-01-01
We describe an ongoing research effort pertaining to the development of a surface traffic automation system that will help controllers to better coordinate surface traffic movements related to arrival and departure traffic. More specifically, we describe the concept for a taxi-planning support tool
Mixed-integer linear program for an optimal hybrid energy network topology
Mazairac, L.A.J.; Salenbien, R.; de Vries, B.
2015-01-01
Existing networks do not have the quantitative and qualitative capacity to facilitate the transition towards distributed renewable energy sources. Irregular production of energy over time at different locations will alter the current patters of energy flow, necessitating the implementation of short-
A Mixed-Integer Linear Programming Problem which is Efficiently Solvable.
1987-10-01
ger prongramn rg versions or the problem is not ac’hievable in genieral for sparse inistancves of’ P rolem(r Mi. Th le remrai nder or thris paper is...rClazes c:oIh edge (i,I*) by comlpli urg +- rnirr(z 3, ,x + a,j). A sirnI) le analysis (11 vto Nei [131 indicates why whe Iellinan-Ford algorithm works...ari cl(cck to iceat reguilar rnct’vtuls. For c’xamiic, oi1cc Wwitiil pcroccc’ssicg svlstcici1 rccjcilrcc thicit I iisc wires ice repeated verr 200W
Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming
2016-01-01
PANAMA CITY DIVISION PANAMA CITY, FLORIDA 32407-7001 5(3257...task. This paper is outlined as follows: in Section 2, we discuss the general setup of the the MCM scheduling problem, including the definition of the...Suite 1425 Arlington, VA 22203-1995 Naval Surface Warfare Center, Panama City Division 1 ATTN: Technical Library 110 Vernon Avenue Panama City, FL 32407 27
The Neighborhood Covering Heuristic (NCH) Approach for the General Mixed Integer Programming Problem
2004-02-02
5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Creative Action LLC 680 N. Portage Path Akron, OH 44303; The...University of Akron Department of Theoretical and Applied Mathematics Akron OH 44325-4002 8. PERFORMING ORGANIZATION REPORT NUMBER SF309 9...algorithm is naturally adaptable to a parallel architechture . In particular, under NCH, one could parcel out pieces of the problem to many processors
On the Impact of using Mixed Integer Programming Techniques on Real-world Offshore Wind Parks
DEFF Research Database (Denmark)
Fischetti, Martina; Pisinger, David
2017-01-01
Wind power is a leading technology in the transition to sustainable energy. Being a new and still more competitive field, it is of major interest to investigate new techniques to solve the design challenges involved. In this paper, we consider optimization of the inter-array cable routing...... optimization problem considers two objectives: minimizing immediate costs (CAPEX) and minimizing costs due to power losses. This makes it possible to perform various what-if analyses to evaluate the impact of different preferences to CAPEX versus reduction of power losses. Thanks to the close collaboration...... with a leading energy company, we have been able to report results on a set of real-world instances, based on six existing wind parks, studying the economical impact of considering power losses in the cable routing design phase....
Wu, C. Z.; Huang, G. H.; Yan, X. P.; Cai, Y. P.; Li, Y. P.
2010-05-01
Large crowds are increasingly common at political, social, economic, cultural and sports events in urban areas. This has led to attention on the management of evacuations under such situations. In this study, we optimise an approximation method for vehicle allocation and route planning in case of an evacuation. This method, based on an interval-parameter multi-objective optimisation model, has potential for use in a flexible decision support system for evacuation management. The modeling solutions are obtained by sequentially solving two sub-models corresponding to lower- and upper-bounds for the desired objective function value. The interval solutions are feasible and stable in the given decision space, and this may reduce the negative effects of uncertainty, thereby improving decision makers' estimates under different conditions. The resulting model can be used for a systematic analysis of the complex relationships among evacuation time, cost and environmental considerations. The results of a case study used to validate the proposed model show that the model does generate useful solutions for planning evacuation management and practices. Furthermore, these results are useful for evacuation planners, not only in making vehicle allocation decisions but also for providing insight into the tradeoffs among evacuation time, environmental considerations and economic objectives.
Directory of Open Access Journals (Sweden)
J. Fabian Lopez
2010-01-01
Full Text Available We consider a Pickup and Delivery Vehicle Routing Problem (PDP commonly encountered in real-world logistics operations. The problem involves a set of practical complications that have received little attention in the vehicle routing literature. In this problem, there are multiple vehicle types available to cover a set of pickup and delivery requests, each of which has pickup time windows and delivery time windows. Transportation orders and vehicle types must satisfy a set of compatibility constraints that specify which orders cannot be covered by which vehicle types. In addition we include some dock service capacity constraints as is required on common real world operations. This problem requires to be attended on large scale instances (orders ≥ 500, (vehicles ≥ 150. As a generalization of the traveling salesman problem, clearly this problem is NP-hard. The exact algorithms are too slow for large scale instances. The PDP-TWDS is both a packing problem (assign order to vehicles, and a routing problem (find the best route for each vehicle. We propose to solve the problem in three stages. The first stage constructs initials solutions at aggregate level relaxing some constraints on the original problem. The other two stages imposes time windows and dock service constraints. Our results are favorable finding good quality solutions in relatively short computational times.
Asset liability management modeling using multi-stage mixed-integer stochastic programming
Drijver, S.J.; Klein Haneveld, W.K.; van der Vlerk, Maarten H.
2000-01-01
A pension fund has to match the portfolio of long-term liabilities with the portfolio of assets. Key instruments in strategic Asset Liability Management (ALM) are the adjustments of the contribution rate of the sponsor and the reallocation of the investments in several asset classes at various
Canepa, Edward S.; Bayen, Alexandre M.; Claudel, Christian G.
2013-01-01
Traffic sensing systems rely more and more on user generated (insecure) data, which can pose a security risk whenever the data is used for traffic flow control. In this article, we propose a new formulation for detecting malicious data injection
Canepa, Edward S.; Claudel, Christian G.
2013-01-01
in traffic flow monitoring systems by using the underlying traffic flow model. The state of traffic is modeled by the Lighthill-Whitham- Richards traffic flow model, which is a first order scalar conservation law with concave flux function. Given a set
CSIR Research Space (South Africa)
Mahlathi, Christopher
2016-10-01
Full Text Available Instream water quality management encompasses field monitoring and utilisation of mathematical models. These models can be coupled with optimisation techniques to determine more efficient water quality management alternatives. Among these activities...
Gorissen, B.L.; den Hertog, D.; Hoffmann, A.L.
2013-01-01
Current inverse treatment planning methods that optimize both catheter positions and dwell times in prostate HDR brachytherapy use surrogate linear or quadratic objective functions that have no direct interpretation in terms of dose-volume histogram (DVH) criteria, do not result in an optimum or
Mixed Integer Linear Programming for new trends in wind farm cable routing
DEFF Research Database (Denmark)
Fischetti, Martina; Pisinger, David
2018-01-01
The efficient production of green energy plays an import role in modern economies. In this paper we address the optimization of cable connections between turbines in an offshore wind park. Different versions of this problem have been studied recently. In a previous joint project with Vattenfall BA...
Directory of Open Access Journals (Sweden)
Wang Yajun
2008-12-01
Full Text Available In order to address the complex uncertainties caused by interfacing between the fuzziness and randomness of the safety problem for embankment engineering projects, and to evaluate the safety of embankment engineering projects more scientifically and reasonably, this study presents the fuzzy logic modeling of the stochastic finite element method (SFEM based on the harmonious finite element (HFE technique using a first-order approximation theorem. Fuzzy mathematical models of safety repertories were introduced into the SFEM to analyze the stability of embankments and foundations in order to describe the fuzzy failure procedure for the random safety performance function. The fuzzy models were developed with membership functions with half depressed gamma distribution, half depressed normal distribution, and half depressed echelon distribution. The fuzzy stochastic mathematical algorithm was used to comprehensively study the local failure mechanism of the main embankment section near Jingnan in the Yangtze River in terms of numerical analysis for the probability integration of reliability on the random field affected by three fuzzy factors. The result shows that the middle region of the embankment is the principal zone of concentrated failure due to local fractures. There is also some local shear failure on the embankment crust. This study provides a referential method for solving complex multi-uncertainty problems in engineering safety analysis.
Set-valued and fuzzy stochastic integral equations driven by semimartingales under Osgood condition
Directory of Open Access Journals (Sweden)
Malinowski Marek T.
2015-01-01
Full Text Available We analyze the set-valued stochastic integral equations driven by continuous semimartingales and prove the existence and uniqueness of solutions to such equations in the framework of the hyperspace of nonempty, bounded, convex and closed subsets of the Hilbert space L2 (consisting of square integrable random vectors. The coefficients of the equations are assumed to satisfy the Osgood type condition that is a generalization of the Lipschitz condition. Continuous dependence of solutions with respect to data of the equation is also presented. We consider equations driven by semimartingale Z and equations driven by processes A;M from decomposition of Z, where A is a process of finite variation and M is a local martingale. These equations are not equivalent. Finally, we show that the analysis of the set-valued stochastic integral equations can be extended to a case of fuzzy stochastic integral equations driven by semimartingales under Osgood type condition. To obtain our results we use the set-valued and fuzzy Maruyama type approximations and Bihari’s inequality.
Li, Zukui; Ding, Ran; Floudas, Christodoulos A.
2011-01-01
Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263
International Nuclear Information System (INIS)
Binh, Do Quang; Huy, Ngo Quang; Hai, Nguyen Hoang
2014-01-01
This paper presents a new approach based on a binary mixed integer coded genetic algorithm in conjunction with the weighted sum method for multi-objective optimization of fuel loading patterns for nuclear research reactors. The proposed genetic algorithm works with two types of chromosomes: binary and integer chromosomes, and consists of two types of genetic operators: one working on binary chromosomes and the other working on integer chromosomes. The algorithm automatically searches for the most suitable weighting factors of the weighting function and the optimal fuel loading patterns in the search process. Illustrative calculations are implemented for a research reactor type TRIGA MARK II loaded with the Russian VVR-M2 fuels. Results show that the proposed genetic algorithm can successfully search for both the best weighting factors and a set of approximate optimal loading patterns that maximize the effective multiplication factor and minimize the power peaking factor while satisfying operational and safety constraints for the research reactor.
Energy Technology Data Exchange (ETDEWEB)
Binh, Do Quang [University of Technical Education Ho Chi Minh City (Viet Nam); Huy, Ngo Quang [University of Industry Ho Chi Minh City (Viet Nam); Hai, Nguyen Hoang [Centre for Research and Development of Radiation Technology, Ho Chi Minh City (Viet Nam)
2014-12-15
This paper presents a new approach based on a binary mixed integer coded genetic algorithm in conjunction with the weighted sum method for multi-objective optimization of fuel loading patterns for nuclear research reactors. The proposed genetic algorithm works with two types of chromosomes: binary and integer chromosomes, and consists of two types of genetic operators: one working on binary chromosomes and the other working on integer chromosomes. The algorithm automatically searches for the most suitable weighting factors of the weighting function and the optimal fuel loading patterns in the search process. Illustrative calculations are implemented for a research reactor type TRIGA MARK II loaded with the Russian VVR-M2 fuels. Results show that the proposed genetic algorithm can successfully search for both the best weighting factors and a set of approximate optimal loading patterns that maximize the effective multiplication factor and minimize the power peaking factor while satisfying operational and safety constraints for the research reactor.
International Nuclear Information System (INIS)
Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu
2013-01-01
Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management
Subagadis, Yohannes Hagos; Schütze, Niels; Grundmann, Jens
2014-05-01
An amplified interconnectedness between a hydro-environmental and socio-economic system brings about profound challenges of water management decision making. In this contribution, we present a fuzzy stochastic approach to solve a set of decision making problems, which involve hydrologically, environmentally, and socio-economically motivated criteria subjected to uncertainty and ambiguity. The proposed methodological framework combines objective and subjective criteria in a decision making procedure for obtaining an acceptable ranking in water resources management alternatives under different type of uncertainty (subjective/objective) and heterogeneous information (quantitative/qualitative) simultaneously. The first step of the proposed approach involves evaluating the performance of alternatives with respect to different types of criteria. The ratings of alternatives with respect to objective and subjective criteria are evaluated by simulation-based optimization and fuzzy linguistic quantifiers, respectively. Subjective and objective uncertainties related to the input information are handled through linking fuzziness and randomness together. Fuzzy decision making helps entail the linguistic uncertainty and a Monte Carlo simulation process is used to map stochastic uncertainty. With this framework, the overall performance of each alternative is calculated using an Order Weighted Averaging (OWA) aggregation operator accounting for decision makers' experience and opinions. Finally, ranking is achieved by conducting pair-wise comparison of management alternatives. This has been done on the basis of the risk defined by the probability of obtaining an acceptable ranking and mean difference in total performance for the pair of management alternatives. The proposed methodology is tested in a real-world hydrosystem, to find effective and robust intervention strategies for the management of a coastal aquifer system affected by saltwater intrusion due to excessive groundwater
Energy Technology Data Exchange (ETDEWEB)
Hu, Yan; Wen, Jing-ya; Li, Xiao-li; Wang, Da-zhou; Li, Yu, E-mail: liyuxx8@hotmail.com
2013-10-15
Highlights: • Using interval mathematics to describe spatial and temporal variability and parameter uncertainty. • Using fuzzy theory to quantify variability of environmental guideline values. • Using probabilistic approach to integrate interval concentrations and fuzzy environmental guideline. • Establishment of dynamic multimedia environmental integrated risk assessment framework. -- Abstract: A dynamic multimedia fuzzy-stochastic integrated environmental risk assessment approach was developed for contaminated sites management. The contaminant concentrations were simulated by a validated interval dynamic multimedia fugacity model, and different guideline values for the same contaminant were represented as a fuzzy environmental guideline. Then, the probability of violating environmental guideline (Pv) can be determined by comparison between the modeled concentrations and the fuzzy environmental guideline, and the constructed relationship between the Pvs and environmental risk levels was used to assess the environmental risk level. The developed approach was applied to assess the integrated environmental risk at a case study site in China, simulated from 1985 to 2020. Four scenarios were analyzed, including “residential land” and “industrial land” environmental guidelines under “strict” and “loose” strictness. It was found that PAH concentrations will increase steadily over time, with soil found to be the dominant sink. Source emission in soil was the leading input and atmospheric sedimentation was the dominant transfer process. The integrated environmental risks primarily resulted from petroleum spills and coke ovens, while the soil environmental risks came from coal combustion. The developed approach offers an effective tool for quantifying variability and uncertainty in the dynamic multimedia integrated environmental risk assessment and the contaminated site management.
Subagadis, Y. H.; Schütze, N.; Grundmann, J.
2014-09-01
The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.
Directory of Open Access Journals (Sweden)
Y. H. Subagadis
2014-09-01
Full Text Available The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water–society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.
Bilevel programming problems theory, algorithms and applications to energy networks
Dempe, Stephan; Pérez-Valdés, Gerardo A; Kalashnykova, Nataliya; Kalashnikova, Nataliya
2015-01-01
This book describes recent theoretical findings relevant to bilevel programming in general, and in mixed-integer bilevel programming in particular. It describes recent applications in energy problems, such as the stochastic bilevel optimization approaches used in the natural gas industry. New algorithms for solving linear and mixed-integer bilevel programming problems are presented and explained.
Henriques, David; Rocha, Miguel; Saez-Rodriguez, Julio; Banga, Julio R
2015-09-15
Systems biology models can be used to test new hypotheses formulated on the basis of previous knowledge or new experimental data, contradictory with a previously existing model. New hypotheses often come in the shape of a set of possible regulatory mechanisms. This search is usually not limited to finding a single regulation link, but rather a combination of links subject to great uncertainty or no information about the kinetic parameters. In this work, we combine a logic-based formalism, to describe all the possible regulatory structures for a given dynamic model of a pathway, with mixed-integer dynamic optimization (MIDO). This framework aims to simultaneously identify the regulatory structure (represented by binary parameters) and the real-valued parameters that are consistent with the available experimental data, resulting in a logic-based differential equation model. The alternative to this would be to perform real-valued parameter estimation for each possible model structure, which is not tractable for models of the size presented in this work. The performance of the method presented here is illustrated with several case studies: a synthetic pathway problem of signaling regulation, a two-component signal transduction pathway in bacterial homeostasis, and a signaling network in liver cancer cells. Supplementary data are available at Bioinformatics online. julio@iim.csic.es or saezrodriguez@ebi.ac.uk. © The Author 2015. Published by Oxford University Press.
Energy Technology Data Exchange (ETDEWEB)
He, Li, E-mail: li.he@iseis.org [MOE Key Laboratory of Regional Energy Systems Optimization, S and C Academy of Energy and Environmental Research, North China Electric Power University, Beijing 102206 (China); Huang, G.H.; Lu, Hongwei [MOE Key Laboratory of Regional Energy Systems Optimization, S and C Academy of Energy and Environmental Research, North China Electric Power University, Beijing 102206 (China)
2011-10-15
Highlights: {yields} We used bilevel analysis to treat two objectives at different levels. {yields} The model can identify allocation schemes for waste flows. {yields} The model can support waste timing, sizing, and siting for facility expansions. {yields} The model can estimate minimized total management cost and GHG emissions. - Abstract: Recent studies indicated that municipal solid waste (MSW) is a major contributor to global warming due to extensive emissions of greenhouse gases (GHGs). However, most of them focused on investigating impacts of MSW on GHG emission amounts. This study presents two mixed integer bilevel decision-making models for integrated municipal solid waste management and GHG emissions control: MGU-MCL and MCU-MGL. The MGU-MCL model represents a top-down decision process, with the environmental sectors at the national level dominating the upper-level objective and the waste management sectors at the municipal level providing the lower-level objective. The MCU-MGL model implies a bottom-up decision process where municipality plays a leading role. Results from the models indicate that: the top-down decisions would reduce metric tonne carbon emissions (MTCEs) by about 59% yet increase about 8% of the total management cost; the bottom-up decisions would reduce MTCE emissions by about 13% but increase the total management cost very slightly; on-site monitoring and downscaled laboratory experiments are still required for reducing uncertainty in GHG emission rate from the landfill facility.
International Nuclear Information System (INIS)
Oluleye, Gbemi; Smith, Robin
2016-01-01
Highlights: • MILP model developed for integration of waste heat recovery technologies in process sites. • Five thermodynamic cycles considered for exploitation of industrial waste heat. • Temperature and quantity of multiple waste heat sources considered. • Interactions with the site utility system considered. • Industrial case study presented to illustrate application of the proposed methodology. - Abstract: Thermodynamic cycles such as organic Rankine cycles, absorption chillers, absorption heat pumps, absorption heat transformers, and mechanical heat pumps are able to utilize wasted thermal energy in process sites for the generation of electrical power, chilling and heat at a higher temperature. In this work, a novel systematic framework is presented for optimal integration of these technologies in process sites. The framework is also used to assess the best design approach for integrating waste heat recovery technologies in process sites, i.e. stand-alone integration or a systems-oriented integration. The developed framework allows for: (1) selection of one or more waste heat sources (taking into account the temperatures and thermal energy content), (2) selection of one or more technology options and working fluids, (3) selection of end-uses of recovered energy, (4) exploitation of interactions with the existing site utility system and (5) the potential for heat recovery via heat exchange is also explored. The methodology is applied to an industrial case study. Results indicate a systems-oriented design approach reduces waste heat by 24%; fuel consumption by 54% and CO_2 emissions by 53% with a 2 year payback, and stand-alone design approach reduces waste heat by 12%; fuel consumption by 29% and CO_2 emissions by 20.5% with a 4 year payback. Therefore, benefits from waste heat utilization increase when interactions between the existing site utility system and the waste heat recovery technologies are explored simultaneously. The case study also shows that the novel methodology can select and design optimal solutions for waste heat exploitation which are technically, economically and environmentally feasible from a range of technology options, heat sources and end-uses of recovered energy.
Cafieri , Sonia; Omheni , Riadh
2016-01-01
International audience; We consider the problem of aircraft conflict avoidance in Air Traffic Management systems. Given an initial configuration of a number of aircraft sharing the same airspace, the main goal of conflict avoidance is to guarantee that a minimum safety distance between each pair of aircraft is always respected during their flights. We consider aircraft separation achieved by heading angle deviations, and propose a mixed 0-1 nonlinear optimization model, that is then combined ...
Moreno-Camacho, Carlos A.; Montoya-Torres, Jairo R.; Vélez-Gallego, Mario C.
2018-06-01
Only a few studies in the available scientific literature address the problem of having a group of workers that do not share identical levels of productivity during the planning horizon. This study considers a workforce scheduling problem in which the actual processing time is a function of the scheduling sequence to represent the decline in workers' performance, evaluating two classical performance measures separately: makespan and maximum tardiness. Several mathematical models are compared with each other to highlight the advantages of each approach. The mathematical models are tested with randomly generated instances available from a public e-library.
International Nuclear Information System (INIS)
Canizes, Bruno; Soares, João; Faria, Pedro; Vale, Zita
2013-01-01
Highlights: • Ancillary services market management. • Ancillary services requirements forecast based on Artificial Neural Network. • Ancillary services clearing mechanisms without complex bids and with complex bids. - Abstract: Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids
International Nuclear Information System (INIS)
Kler, Alexandr M.; Potanina, Yulia M.
2017-01-01
One of the ways to enhance the energy efficiency of thermal power plants is to increase thermodynamic parameters of steam. A sufficient level of reliability and longevity can be provided by the application of advanced construction materials (in particular, high-alloy steel can be used to manufacture the most loaded heating surfaces of a boiler unit). A rational choice of technical and economic parameters of energy plants as the most complex technical systems should be made using the methods of mathematical modeling and optimization. The paper considers an original approach to an economically sound optimal choice of steel grade to manufacture heating surfaces for boiler units. A case study of optimization of the discrete-continuous parameters of an energy unit operating at ultra-supercritical steam parameters, in combination with construction of a variant selection tree is presented. - Highlights: • A case study on optimization of an ultra-supercritical power plant is demonstrated. • Optimization is based on the minimization of electricity price. • An approach is proposed to optimize the selection of boiler steel grades. • The approach is based on the construction of a variant tree. • The selection of steel grades for a boiler unit is shown.
Lütke Entrup, M.; Günther, H.O.; Beek, van P.; Grunow, M.; Seiler, T.
2005-01-01
In the production of perishable products such as dairy, meat or bakery goods, the consideration of shelf life in production planning is of particular importance. Retail customers with relatively low inventory turns can benefit significantly from longer product shelf life as wastage and out-of-stock
Smalley, Hannah K; Keskinocak, Pinar; Swann, Julie; Hinman, Alan
2015-11-17
In addition to improved sanitation, hygiene, and better access to safe water, oral cholera vaccines can help to control the spread of cholera in the short term. However, there is currently no systematic method for determining the best allocation of oral cholera vaccines to minimize disease incidence in a population where the disease is endemic and resources are limited. We present a mathematical model for optimally allocating vaccines in a region under varying levels of demographic and incidence data availability. The model addresses the questions of where, when, and how many doses of vaccines to send. Considering vaccine efficacies (which may vary based on age and the number of years since vaccination), we analyze distribution strategies which allocate vaccines over multiple years. Results indicate that, given appropriate surveillance data, targeting age groups and regions with the highest disease incidence should be the first priority, followed by other groups primarily in order of disease incidence, as this approach is the most life-saving and cost-effective. A lack of detailed incidence data results in distribution strategies which are not cost-effective and can lead to thousands more deaths from the disease. The mathematical model allows for what-if analysis for various vaccine distribution strategies by providing the ability to easily vary parameters such as numbers and sizes of regions and age groups, risk levels, vaccine price, vaccine efficacy, production capacity and budget. Copyright © 2015 Elsevier Ltd. All rights reserved.
Wouda, H.E.; Beek, van P.; Vorst, van der J.G.A.J.; Tacke, H.
2002-01-01
Between 1995 and 1998 Nutricia acquired a number of dairy companies in Hungary. Each of these companies produced a wide variety of products for its regional market. Although alterations had been made to the production system in the last few years, production and transportation costs were still
Pacino, Dario
2012-01-01
Containerization has changed the way the world perceives shipping. It is now possible to establish complex international supply chains that have minimized shipping costs. Over the past two decades, the demand for cost efficient containerized transportation has seen a continuous increase. In order to answer to this demand, shipping companies have deployed bigger container vessels, that nowadays can transport up to 18,000 containers and are wider than the extended Panama Canal. Like busses, con...
International Nuclear Information System (INIS)
Esmaeily, Ali; Ahmadi, Abdollah; Raeisi, Fatima; Ahmadi, Mohammad Reza; Esmaeel Nezhad, Ali; Janghorbani, Mohammadreza
2017-01-01
A new optimization framework based on MILP model is introduced in the paper for the problem of stochastic self-scheduling of hydrothermal units known as HTSS Problem implemented in a joint energy and reserve electricity market with day-ahead mechanism. The proposed MILP framework includes some practical constraints such as the cost due to valve-loading effect, the limit due to DRR and also multi-POZs, which have been less investigated in electricity market models. For the sake of more accuracy, for hydro generating units’ model, multi performance curves are also used. The problem proposed in this paper is formulated using a model on the basis of a stochastic optimization technique while the objective function is maximizing the expected profit utilizing MILP technique. The suggested stochastic self-scheduling model employs the price forecast error in order to take into account the uncertainty due to price. Besides, LMCS is combined with roulette wheel mechanism so that the scenarios corresponding to the non-spinning reserve price and spinning reserve price as well as the energy price at each hour of the scheduling are generated. Finally, the IEEE 118-bus power system is used to indicate the performance and the efficiency of the suggested technique. - Highlights: • Characterizing the uncertainties of price and FOR of units. • Replacing the fixed ramping rate constraints with the dynamic ones. • Proposing linearized model for the valve-point effects of thermal units. • Taking into consideration the multi-POZs relating to the thermal units. • Taking into consideration the multi-performance curves of hydroelectric units.
Directory of Open Access Journals (Sweden)
Peng Li
2017-01-01
Full Text Available According to the case-based reasoning method and prospect theory, this paper mainly focuses on finding a way to obtain decision-makers’ preferences and the criterion weights for stochastic multicriteria decision-making problems and classify alternatives. Firstly, we construct a new score function for an intuitionistic fuzzy number (IFN considering the decision-making environment. Then, we aggregate the decision-making information in different natural states according to the prospect theory and test decision-making matrices. A mathematical programming model based on a case-based reasoning method is presented to obtain the criterion weights. Moreover, in the original decision-making problem, we integrate all the intuitionistic fuzzy decision-making matrices into an expectation matrix using the expected utility theory and classify or rank the alternatives by the case-based reasoning method. Finally, two illustrative examples are provided to illustrate the implementation process and applicability of the developed method.
Directory of Open Access Journals (Sweden)
Hideki Katagiri
2017-10-01
Full Text Available This paper considers linear programming problems (LPPs where the objective functions involve discrete fuzzy random variables (fuzzy set-valued discrete random variables. New decision making models, which are useful in fuzzy stochastic environments, are proposed based on both possibility theory and probability theory. In multi-objective cases, Pareto optimal solutions of the proposed models are newly defined. Computational algorithms for obtaining the Pareto optimal solutions of the proposed models are provided. It is shown that problems involving discrete fuzzy random variables can be transformed into deterministic nonlinear mathematical programming problems which can be solved through a conventional mathematical programming solver under practically reasonable assumptions. A numerical example of agriculture production problems is given to demonstrate the applicability of the proposed models to real-world problems in fuzzy stochastic environments.
Menu-Driven Solver Of Linear-Programming Problems
Viterna, L. A.; Ferencz, D.
1992-01-01
Program assists inexperienced user in formulating linear-programming problems. A Linear Program Solver (ALPS) computer program is full-featured LP analysis program. Solves plain linear-programming problems as well as more-complicated mixed-integer and pure-integer programs. Also contains efficient technique for solution of purely binary linear-programming problems. Written entirely in IBM's APL2/PC software, Version 1.01. Packed program contains licensed material, property of IBM (copyright 1988, all rights reserved).
Integer programming for the generalized high school timetabling problem
DEFF Research Database (Denmark)
Kristiansen, Simon; Sørensen, Matias; Stidsen, Thomas Riis
2015-01-01
, the XHSTT format serves as a common ground for researchers within this area. This paper describes the first exact method capable of handling an arbitrary instance of the XHSTT format. The method is based on a mixed-integer linear programming (MIP) model, which is solved in two steps with a commercial...
The effect of workload constraints in mathematical programming models for production planning
Jansen, M.M.; Kok, de A.G.; Adan, I.J.B.F.
2010-01-01
Linear and mixed integer programming models for production planning incorporate a model of the manufacturing system that is necessarily deterministic. Although these eterministic models are the current-state-of-art, it should be recognized that they are used in an environment that is inherently
DEFF Research Database (Denmark)
Escudero, Laureano F.; Monge, Juan Francisco; Morales, Dolores Romero
2015-01-01
In this paper we consider multiperiod mixed 0–1 linear programming models under uncertainty. We propose a risk averse strategy using stochastic dominance constraints (SDC) induced by mixed-integer linear recourse as the risk measure. The SDC strategy extends the existing literature to the multist...
Ferencz, Donald C.; Viterna, Larry A.
1991-01-01
ALPS is a computer program which can be used to solve general linear program (optimization) problems. ALPS was designed for those who have minimal linear programming (LP) knowledge and features a menu-driven scheme to guide the user through the process of creating and solving LP formulations. Once created, the problems can be edited and stored in standard DOS ASCII files to provide portability to various word processors or even other linear programming packages. Unlike many math-oriented LP solvers, ALPS contains an LP parser that reads through the LP formulation and reports several types of errors to the user. ALPS provides a large amount of solution data which is often useful in problem solving. In addition to pure linear programs, ALPS can solve for integer, mixed integer, and binary type problems. Pure linear programs are solved with the revised simplex method. Integer or mixed integer programs are solved initially with the revised simplex, and the completed using the branch-and-bound technique. Binary programs are solved with the method of implicit enumeration. This manual describes how to use ALPS to create, edit, and solve linear programming problems. Instructions for installing ALPS on a PC compatible computer are included in the appendices along with a general introduction to linear programming. A programmers guide is also included for assistance in modifying and maintaining the program.
Applied Integer Programming Modeling and Solution
Chen, Der-San; Dang, Yu
2011-01-01
An accessible treatment of the modeling and solution of integer programming problems, featuring modern applications and software In order to fully comprehend the algorithms associated with integer programming, it is important to understand not only how algorithms work, but also why they work. Applied Integer Programming features a unique emphasis on this point, focusing on problem modeling and solution using commercial software. Taking an application-oriented approach, this book addresses the art and science of mathematical modeling related to the mixed integer programming (MIP) framework and
Water pollution control in river basin by interactive fuzzy interval multiobjective programming
Energy Technology Data Exchange (ETDEWEB)
Chang, N.B.; Chen, H.W. [National Cheng-Kung Univ., Tainan (Taiwan, Province of China). Dept. of Environmental Engineering; Shaw, D.G.; Yang, C.H. [Academia Sinica, Taipei (Taiwan, Province of China). Inst. of Economics
1997-12-01
The potential conflict between protection of water quality and economic development by different uses of land within river basins is a common problem in regional planning. Many studies have applied multiobjective decision analysis under uncertainty to problems of this kind. This paper presents the interactive fuzzy interval multiobjective mixed integer programming (IFIMOMIP) model to evaluate optimal strategies of wastewater treatment levels within a river system by considering the uncertainties in decision analysis. The interactive fuzzy interval multiobjective mixed integer programming approach is illustrated in a case study for the evaluation of optimal wastewater treatment strategies for water pollution control in a river basin. In particular, it demonstrates how different types of uncertainty in a water pollution control system can be quantified and combined through the use of interval numbers and membership functions. The results indicate that such an approach is useful for handling system complexity and generating more flexible policies for water quality management in river basins.
He, Li; Huang, Guo-He; Zeng, Guang-Ming; Lu, Hong-Wei
2009-01-01
The previous inexact mixed-integer linear programming (IMILP) method can only tackle problems with coefficients of the objective function and constraints being crisp intervals, while the existing inexact mixed-integer semi-infinite programming (IMISIP) method can only deal with single-objective programming problems as it merely allows the number of constraints to be infinite. This study proposes, an inexact mixed-integer bi-infinite programming (IMIBIP) method by incorporating the concept of functional intervals into the programming framework. Different from the existing methods, the IMIBIP can tackle the inexact programming problems that contain both infinite objectives and constraints. The developed method is applied to capacity planning of waste management systems under a variety of uncertainties. Four scenarios are considered for comparing the solutions of IMIBIP with those of IMILP. The results indicate that reasonable solutions can be generated by the IMIBIP method. Compared with IMILP, the system cost from IMIBIP would be relatively high since the fluctuating market factors are considered; however, the IMILP solutions are associated with a raised system reliability level and a reduced constraint violation risk level.
Optimization Research of Generation Investment Based on Linear Programming Model
Wu, Juan; Ge, Xueqian
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.
Cunha, P.S.A.; Oliveira, F.; Raupp, Fernanda M.P.
2017-01-01
ABSTRACT Here, we propose a novel methodology for replenishment and control systems for inventories of two-echelon logistics networks using a two-stage stochastic programming, considering periodic review and uncertain demands. In addition, to achieve better customer services, we introduce a variable rationing rule to address quantities of the item in short. The devised models are reformulated into their deterministic equivalent, resulting in nonlinear mixed-integer programming models, which a...
Multi-Target Tracking via Mixed Integer Optimization
2016-05-13
an easily interpretable global objective function. Furthermore, we propose a greedy heuristic which quickly finds good solutions. We extend both the... heuristic and the MIO model to scenarios with missed detections and false alarms. Index Terms—optimization; multi-target tracking; data asso- ciation...energy in [14] and then again as a minimization of discrete-continuous energy in [15]. These algorithms aim to more accurately represent the nature of the
Mixed-Integer Nonconvex Quadratic Optimization Relaxations and Performance Analysis
2016-10-11
stationary point. These results are the state of art in complexity analysis of non-convex optimization. “Complexity of Unconstrained L2-Lp Minimization...Parameter Optimized Radiation Therapy ( SPORT )” (M Zarepisheh, Y Ye, S Boyd, R Li, L Xing), Medical Physics 41(6) (2014) 292-292. Station parameter...optimized radiation therapy ( SPORT ) was recently proposed to fully utilize the technical capability of emerging digital linear accelerators, in
A novel progressively swarmed mixed integer genetic algorithm for ...
African Journals Online (AJOL)
MIGA) which inherits the advantages of binary and real coded Genetic Algorithm approach. The proposed algorithm is applied for the conventional generation cost minimization Optimal Power Flow (OPF) problem and for the Security ...
Network interdiction and stochastic integer programming
2003-01-01
On March 15, 2002 we held a workshop on network interdiction and the more general problem of stochastic mixed integer programming at the University of California, Davis. Jesús De Loera and I co-chaired the event, which included presentations of on-going research and discussion. At the workshop, we decided to produce a volume of timely work on the topics. This volume is the result. Each chapter represents state-of-the-art research and all of them were refereed by leading investigators in the respective fields. Problems - sociated with protecting and attacking computer, transportation, and social networks gain importance as the world becomes more dep- dent on interconnected systems. Optimization models that address the stochastic nature of these problems are an important part of the research agenda. This work relies on recent efforts to provide methods for - dressing stochastic mixed integer programs. The book is organized with interdiction papers first and the stochastic programming papers in the second part....
Generic Mathematical Programming Formulation and Solution for Computer-Aided Molecular Design
DEFF Research Database (Denmark)
Zhang, Lei; Cignitti, Stefano; Gani, Rafiqul
2015-01-01
This short communication presents a generic mathematical programming formulation for Computer-Aided Molecular Design (CAMD). A given CAMD problem, based on target properties, is formulated as a Mixed Integer Linear/Non-Linear Program (MILP/MINLP). The mathematical programming model presented here......, which is formulated as an MILP/MINLP problem, considers first-order and second-order molecular groups for molecular structure representation and property estimation. It is shown that various CAMD problems can be formulated and solved through this model....
Short-term hydropower production planning by stochastic programming
DEFF Research Database (Denmark)
Fleten, Stein-Erik; Kristoffersen, Trine
2008-01-01
-term production planning a matter of spatial distribution among the reservoirs of the plant. Day-ahead market prices and reservoir inflows are, however, uncertain beyond the current operation day and water must be allocated among the reservoirs in order to strike a balance between current profits and expected......Within the framework of multi-stage mixed-integer linear stochastic programming we develop a short-term production plan for a price-taking hydropower plant operating under uncertainty. Current production must comply with the day-ahead commitments of the previous day which makes short...
DEFF Research Database (Denmark)
Zhan, Yiduo; Zheng, Qipeng; Wang, Jianhui
2016-01-01
, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming......Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined...
Optimal installation program for reprocessing plants
International Nuclear Information System (INIS)
Kubokawa, Toshihiko; Kiyose, Ryohei
1976-01-01
Optimization of the program of installation of reprocessing plants is mathematically formulated as problem of mixed integer programming, which is numerically solved by the branch-and-bound method. A new concept of quasi-penalty is used to obviate the difficulties associated with dual degeneracy. The finiteness of the useful life of the plant is also taken into consideration. It is shown that an analogous formulation is possible for the cases in which the demand forecasts and expected plant lives cannot be predicted with certainty. The scale of the problem is found to have kN binary variables, (k+2)N continuous variables, and (k+3)N constraint conditions, where k is the number of intervals used in the piece-wise linear approximation of a nonlinear objective function, and N the overall duration of the period covered by the installation program. Calculations are made for N=24 yr and k=3, with the assumption that the plant life is 15 yr, the plant scale factor 0.5, and the maximum plant capacity 900 (t/yr). The results are calculated and discussed for four different demand forecasts. The difference of net profit between optimal and non-optimal installation programs is found to be in the range of 50 -- 100 M$. The pay-off matrix is calculated, and the optimal choice of action when the demand cannot be forecast with certainty is determined by applying Bayes' theory. The optimal installation program under such conditions of uncertainty is obtained also with a stochastic mixed integer programming model. (auth.)
DEFF Research Database (Denmark)
Zhou, Bo; Ai, Xiaomeng; Fang, Jiakun
2017-01-01
With the rapid development and deployment of voltage source converter (VSC) based HVDC, the traditional power system is evolving to the hybrid AC-DC grid. New optimization methods are urgently needed for these hybrid AC-DC power systems. In this paper, mixed-integer second order cone programming...... (MISOCP) for the hybrid AC-DC power systems is proposed. The second order cone (SOC) relaxation is adopted to transform the AC and DC power flow constraints to MISOCP. Several IEEE test systems are used to validate the proposed MISCOP formulation of the optimal power flow (OPF) and unit commitment (UC...
Theoretical and algorithmic advances in multi-parametric programming and control
Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar
2012-01-01
This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
Theoretical and algorithmic advances in multi-parametric programming and control
Pistikopoulos, Efstratios N.
2012-04-21
This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.
ARSTEC, Nonlinear Optimization Program Using Random Search Method
International Nuclear Information System (INIS)
Rasmuson, D. M.; Marshall, N. H.
1979-01-01
1 - Description of problem or function: The ARSTEC program was written to solve nonlinear, mixed integer, optimization problems. An example of such a problem in the nuclear industry is the allocation of redundant parts in the design of a nuclear power plant to minimize plant unavailability. 2 - Method of solution: The technique used in ARSTEC is the adaptive random search method. The search is started from an arbitrary point in the search region and every time a point that improves the objective function is found, the search region is centered at that new point. 3 - Restrictions on the complexity of the problem: Presently, the maximum number of independent variables allowed is 10. This can be changed by increasing the dimension of the arrays
Solving the Single-Sink, Fixed-Charge, Multiple-Choice Transportation Problem by Dynamic Programming
DEFF Research Database (Denmark)
Christensen, Tue; Andersen, Kim Allan; Klose, Andreas
2013-01-01
This paper considers a minimum-cost network flow problem in a bipartite graph with a single sink. The transportation costs exhibit a staircase cost structure because such types of transportation cost functions are often found in practice. We present a dynamic programming algorithm for solving...... this so-called single-sink, fixed-charge, multiple-choice transportation problem exactly. The method exploits heuristics and lower bounds to peg binary variables, improve bounds on flow variables, and reduce the state-space variable. In this way, the dynamic programming method is able to solve large...... instances with up to 10,000 nodes and 10 different transportation modes in a few seconds, much less time than required by a widely used mixed-integer programming solver and other methods proposed in the literature for this problem....
International Nuclear Information System (INIS)
Nikzad, Mehdi; Mozafari, Babak; Bashirvand, Mahdi; Solaymani, Soodabeh; Ranjbar, Ali Mohamad
2012-01-01
Recently in electricity markets, a massive focus has been made on setting up opportunities for participating demand side. Such opportunities, also known as demand response (DR) options, are triggered by either a grid reliability problem or high electricity prices. Two important challenges that market operators are facing are appropriate designing and reasonable pricing of DR options. In this paper, time-of-use program (TOU) as a prevalent time-varying program is modeled linearly based on own and cross elasticity definition. In order to decide on TOU rates, a stochastic model is proposed in which the optimum TOU rates are determined based on grid reliability index set by the operator. Expected Load Not Supplied (ELNS) is used to evaluate reliability of the power system in each hour. The proposed stochastic model is formulated as a two-stage stochastic mixed-integer linear programming (SMILP) problem and solved using CPLEX solver. The validity of the method is tested over the IEEE 24-bus test system. In this regard, the impact of the proposed pricing method on system load profile; operational costs and required capacity of up- and down-spinning reserve as well as improvement of load factor is demonstrated. Also the sensitivity of the results to elasticity coefficients is investigated. -- Highlights: ► Time-of-use demand response program is linearly modeled. ► A stochastic model is proposed to determine the optimum TOU rates based on ELNS index set by the operator. ► The model is formulated as a short-term two-stage stochastic mixed-integer linear programming problem.
Lima, Ricardo
2016-06-16
This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
A mathematical programming framework for early stage design of wastewater treatment plants
DEFF Research Database (Denmark)
Bozkurt, Hande; Quaglia, Alberto; Gernaey, Krist
2015-01-01
The increasing number of alternative wastewater treatment technologies and stricter effluent requirements make the optimal treatment process selection for wastewater treatment plant design a complicated problem. This task, defined as wastewater treatment process synthesis, is currently based on e...... the design problem is formulated as a Mixed Integer (Non)linear Programming problem e MI(N)LP e and solved. A case study is formulated and solved to highlight the application of the framework. © 2014 Elsevier Ltd. All rights reserved....... on expert decisions and previous experiences. This paper proposes a new approach based on mathematical programming to manage the complexity of the problem. The approach generates/identifies novel and optimal wastewater treatment process selection, and the interconnection between unit operations to create...
Lima, Ricardo; Grossmann, Ignacio E.
2016-01-01
This paper addresses the solution of a cardinality Boolean quadratic programming problem using three different approaches. The first transforms the original problem into six mixed-integer linear programming (MILP) formulations. The second approach takes one of the MILP formulations and relies on the specific features of an MILP solver, namely using starting incumbents, polishing, and callbacks. The last involves the direct solution of the original problem by solvers that can accomodate the nonlinear combinatorial problem. Particular emphasis is placed on the definition of the MILP reformulations and their comparison with the other approaches. The results indicate that the data of the problem has a strong influence on the performance of the different approaches, and that there are clear-cut approaches that are better for some instances of the data. A detailed analysis of the results is made to identify the most effective approaches for specific instances of the data. © 2016 Springer Science+Business Media New York
Baran, Ismet; Tutum, Cem C.; Hattel, Jesper H.
2013-01-01
In this paper thermo-chemical simulation of the pultrusion process of a composite rod is first used as a validation case to ensure that the utilized numerical scheme is stable and converges to results given in literature. Following this validation case, a cylindrical die block with heaters is added
DEFF Research Database (Denmark)
Baran, Ismet; Tutum, Cem Celal; Hattel, Jesper Henri
2013-01-01
In this paper thermo-chemical simulation of the pultrusion process of a composite rod is first used as a validation case to ensure that the utilized numerical scheme is stable and converges to results given in literature. Following this validation case, a cylindrical die block with heaters is add...
Mixed Integer PDE Constrained Optimization for the Control of a Wildfire Hazard
2017-01-01
Constrained Optimization for the Control of a Wildfire Hazard Herausgegeben von der Professor fur Angewandte Mathematik Professor Dr. rer. nat. Armin...and H.H. Tan . Finite difference methods for solving the two-dimensional advection-diffusion equation. Int. J. Numer. Meth. Fluids, 9:75-98, 1989. 6
Commercial Aircraft Trajectory Planning based on Multiphase Mixed-Integer Optimal Control
Soler Arnedo, Manuel Fernando
2017-01-01
The main goal of this dissertation is to develop optimal control techniques for aircraft trajectory planning looking at reduction of fuel consumption, emissions and overfly charges in flight plans. The calculation of a flight plan involves the consideration of multiple factors. They can be classified as either continuous or discrete, and include nonlinear aircraft performance, atmospheric conditions, wind conditions, airspace structure, amount of departure fuel, and operational...
National Research Council Canada - National Science Library
Homaifar, Abdollah; Esterline, Albert; Kimiaghalam, Bahram
2005-01-01
The Hybrid Projected Gradient-Evolutionary Search Algorithm (HPGES) algorithm uses a specially designed evolutionary-based global search strategy to efficiently create candidate solutions in the solution space...
International Nuclear Information System (INIS)
Zakariazadeh, Alireza; Jadid, Shahram; Siano, Pierluigi
2014-01-01
Highlights: • Environmental/economical scheduling of energy and reserve. • Simultaneous participation of loads in both energy and reserve scheduling. • Aggregate wind generation and demand uncertainties in a stochastic model. • Stochastic scheduling of energy and reserve in a distribution system. • Demand response providers’ participation in energy and reserve scheduling. - Abstract: In this paper a stochastic multi-objective economical/environmental operational scheduling method is proposed to schedule energy and reserve in a smart distribution system with high penetration of wind generation. The proposed multi-objective framework, based on augmented ε-constraint method, is used to minimize the total operational costs and emissions and to generate Pareto-optimal solutions for the energy and reserve scheduling problem. Moreover, fuzzy decision making process is employed to extract one of the Pareto-optimal solutions as the best compromise non-dominated solution. The wind power and demand forecast errors are considered in this approach and the reserve can be furnished by the main grid as well as distributed generators and responsive loads. The consumers participate in both energy and reserve markets using various demand response programs. In order to facilitate small and medium loads participation in demand response programs, a Demand Response Provider (DRP) aggregates offers for load reduction. In order to solve the proposed optimization model, the Benders decomposition technique is used to convert the large scale mixed integer non-linear problem into mixed-integer linear programming and non-linear programming problems. The effectiveness of the proposed scheduling approach is verified on a 41-bus distribution test system over a 24-h period
Directory of Open Access Journals (Sweden)
Yailet Albernas-Carvajal
2015-10-01
Full Text Available The biorefineries concept from renewable sources has gained much attention in recent years because they improve sustainability with regard to fossil fuel refineries that are limited by the depletion of petroleum reserves. In this perspective, the production of ethanol from sugar cane bagasse is highly attractive because it reduces the fossil fuels consumption, the energy costs and the greenhouse gases emission. In this context, this paper aims to develop an optimal model design of an ethanol plant, considering bagasse pretreatment stages for subsequent simultaneous saccharification and fermentation (SSF. SSF variant, as its name suggests, has the advantage that enzymatic hydrolysis and fermentation stages are simultaneously carried out on the same equipment, obtaining directly the ethanol as a main product. The proposed approach is based on a mixed integer linear programming model which is optimized by GAMS-CPLEX package.
An Integer Programming Model for Multi-Echelon Supply Chain Decision Problem Considering Inventories
Harahap, Amin; Mawengkang, Herman; Siswadi; Effendi, Syahril
2018-01-01
In this paper we address a problem that is of significance to the industry, namely the optimal decision of a multi-echelon supply chain and the associated inventory systems. By using the guaranteed service approach to model the multi-echelon inventory system, we develop a mixed integer; programming model to simultaneously optimize the transportation, inventory and network structure of a multi-echelon supply chain. To solve the model we develop a direct search approach using a strategy of releasing nonbasic variables from their bounds, combined with the “active constraint” method. This strategy is used to force the appropriate non-integer basic variables to move to their neighbourhood integer points.
A Mathematical Programming Approach to the Optimal Sustainable Product Mix for the Process Industry
Directory of Open Access Journals (Sweden)
Noha M. Galal
2015-09-01
Full Text Available The increasing concerns about the environment and the depletion of natural resources are the main drivers for the growing interest in sustainability. Manufacturing operations are frequently considered to have an adverse effect on the environment. Hence, the sustainable operation of manufacturing facilities is a vital practice to ensure sustainability. The aim of this paper is to find the optimum product mix of a manufacturing facility to maximize its sustainability. A mixed integer non-linear programming model is developed to specify the product mix in order to maximize a proposed sustainability index (SI of a manufacturing facility. The sustainability index comprises the economic, environmental and social pillars of sustainability in a weighted form using the analytic hierarchy process (AHP. The model results allow the identification of the prospective improvements of manufacturing sustainability.
International Nuclear Information System (INIS)
Jannati, Jamil; Nazarpour, Daryoosh
2017-01-01
Highlights: • Energy management of IPL is considered in the presence of wind turbine and PV system. • The optimal charge and discharge powers of EVs, dispatch power of LDG are determined. • Charging/discharging decisions of electrolyser and fuel cell are determined. • Demand response program is used to manage the peak load to reduce the operation cost. • Global optimal is guaranteed in proposed model by mixed-integer linear programming. - Abstract: Nowadays, utilization of distributed generation sources and electric vehicles (EVs) are increased to reduce air pollution and greenhouse gas emissions. Also, intelligent parking lots (IPL) are increased in response to the increase in the number of EVs. Therefore, optimal operation of distributed generation sources and IPL in the power market without technical scheduling will follow some economic problems for the owner of IPL and some technical problems for the operator of distribution network. Therefore, in this paper, an optimal energy management has been proposed for an IPL which includes renewable energy sources (wind turbine and photovoltaic system) and local dispatchable generators (micro-turbines). Also, determination of optimal charge and discharge powers of hydrogen storage system (HSS) containing electrolyser, hydrogen storage tanks and fuel cell has been considered in the proposed model. Furthermore, the time-of-use rates of demand response program are proposed to flatten the load curve to reduce the operation cost of IPL. The objective function includes minimizing the operation costs of upstream grid and local dispatchable generators as well as charging and discharging cost of IPL subject to the technical and physical constraints under demand response program in the presence of HSS. The proposed model is formulated as a mixed-integer linear programming and solved using GAMS optimization software under CPLEX solver. Four case studies are investigated to validate the proposed model to show the positive
Directory of Open Access Journals (Sweden)
P.S.A. Cunha
Full Text Available ABSTRACT Here, we propose a novel methodology for replenishment and control systems for inventories of two-echelon logistics networks using a two-stage stochastic programming, considering periodic review and uncertain demands. In addition, to achieve better customer services, we introduce a variable rationing rule to address quantities of the item in short. The devised models are reformulated into their deterministic equivalent, resulting in nonlinear mixed-integer programming models, which are then approximately linearized. To deal with the uncertain nature of the item demand levels, we apply a Monte Carlo simulation-based method to generate finite and discrete sets of scenarios. Moreover, the proposed approach does not require restricted assumptions to the behavior of the probabilistic phenomena, as does several existing methods in the literature. Numerical experiments with the proposed approach for randomly generated instances of the problem show results with errors around 1%.
International Nuclear Information System (INIS)
Oh, S.-D.; Kwak, H.-Y.
2005-01-01
An optimal planning for gas turbine cogeneration system has been studied. The planning problem considered in this study is to determine the optimal configuration of the system equipments and optimal operational policy of the system when the annual energy demands of electric power, heat and cooling are given a priori. The main benefit of the optimal planning is to minimize operational costs and to save energy by efficient energy utilization. A mixed-integer linear programming and the branch and bound algorithm have been adopted to obtain the optimal solution. Both the optimal configuration of the system equipments and the optimal operation policy has been obtained based on annual cost method. The planning method employed here may be applied to the planning problem of the cogeneration plant to any specific building or hotel. (author)
Final Report---Optimization Under Nonconvexity and Uncertainty: Algorithms and Software
Energy Technology Data Exchange (ETDEWEB)
Jeff Linderoth
2011-11-06
the goal of this work was to develop new algorithmic techniques for solving large-scale numerical optimization problems, focusing on problems classes that have proven to be among the most challenging for practitioners: those involving uncertainty and those involving nonconvexity. This research advanced the state-of-the-art in solving mixed integer linear programs containing symmetry, mixed integer nonlinear programs, and stochastic optimization problems. The focus of the work done in the continuation was on Mixed Integer Nonlinear Programs (MINLP)s and Mixed Integer Linear Programs (MILP)s, especially those containing a great deal of symmetry.
International Nuclear Information System (INIS)
Cai, Y.P.; Huang, G.H.; Yang, Z.F.; Tan, Q.
2009-01-01
Management of energy resources is crucial for many regions throughout the world. Many economic, environmental and political factors are having significant effects on energy management practices, leading to a variety of uncertainties in relevant decision making. The objective of this research is to identify optimal strategies in the planning of energy management systems under multiple uncertainties through the development of a fuzzy-random interval programming (FRIP) model. The method is based on an integration of the existing interval linear programming (ILP), superiority-inferiority-based fuzzy-stochastic programming (SI-FSP) and mixed integer linear programming (MILP). Such a FRIP model allows multiple uncertainties presented as interval values, possibilistic and probabilistic distributions, as well as their combinations within a general optimization framework. It can also be used for facilitating capacity-expansion planning of energy-production facilities within a multi-period and multi-option context. Complexities in energy management systems can be systematically reflected, thus applicability of the modeling process can be highly enhanced. The developed method has then been applied to a case of long-term energy management planning for a region with three cities. Useful solutions for the planning of energy management systems were generated. Interval solutions associated with different risk levels of constraint violation were obtained. They could be used for generating decision alternatives and thus help decision makers identify desired policies under various economic and system-reliability constraints. The solutions can also provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs and constraint-violation risks could be successfully tackled, i.e., higher costs will increase system stability, while a desire for lower
Kala, Zdeněk; Sandovič, GiedrÄ--
2012-09-01
The paper deals with non-linear analysis of ultimate and serviceability limit states of two-span pedestrian steel bridge. The effects of random material and geometrical characteristics on limit states are analyzed. The Monte Carlo method was applied to stochastic analysis. For the serviceability limit state, also influence of fuzzy uncertainty of the limit deflection value on random characteristics of load capacity of variable action was studied. The results prove that, for the type of structure studied, the serviceability limit state is decisive from the point of view of design. The present paper opens a discussion on the use of stochastic analysis to verify the limit deflections given in the standards EUROCODES.
Fuzzy Stochastic Optimal Guaranteed Cost Control of Bio-Economic Singular Markovian Jump Systems.
Li, Li; Zhang, Qingling; Zhu, Baoyan
2015-11-01
This paper establishes a bio-economic singular Markovian jump model by considering the price of the commodity as a Markov chain. The controller is designed for this system such that its biomass achieves the specified range with the least cost in a finite-time. Firstly, this system is described by Takagi-Sugeno fuzzy model. Secondly, a new design method of fuzzy state-feedback controllers is presented to ensure not only the regularity, nonimpulse, and stochastic singular finite-time boundedness of this kind of systems, but also an upper bound achieved for the cost function in the form of strict linear matrix inequalities. Finally, two examples including a practical example of eel seedling breeding are given to illustrate the merit and usability of the approach proposed in this paper.
Directory of Open Access Journals (Sweden)
Liudong Zhang
2014-01-01
Full Text Available An uncertain monthly reservoirs operation and multicrop deficit irrigation model was proposed under conjunctive use of underground and surface water for water resources optimization management. The objective is to maximize the total crop yield of the entire irrigation districts. Meanwhile, ecological water remained for the downstream demand. Because of the shortage of water resources, the monthly crop water production function was adopted for multiperiod deficit irrigation management. The model reflects the characteristics of water resources repetitive transformation in typical inland rivers irrigation system. The model was used as an example for water resources optimization management in Shiyang River Basin, China. Uncertainties in reservoir management shown as fuzzy probability were treated through chance-constraint parameter for decision makers. Necessity of dominance (ND was used to analyse the advantages of the method. The optimization results including reservoirs real-time operation policy, deficit irrigation management, and the available water resource allocation could be used to provide decision support for local irrigation management. Besides, the strategies obtained could help with the risk analysis of reservoirs operation stochastically.
Oil sands mine planning and waste management using goal programming
Energy Technology Data Exchange (ETDEWEB)
Ben-Awuah, E.; Askari-Nasab, H. [Alberta Univ., Edmonton, AB (Canada). Dept. of Civil and Environmental Engineering; Alberta Univ., Edmonton, AB (Canada). Mining Optimization Laboratory
2010-07-01
A goal programming method was used to plan waste management processes at an oil sands mine. This method requires the decision maker (DM) to set goals. Mine planning is used to determine a block extraction schedule that maximizes net present value (NPV). Due to land restrictions, tailings facilities are sited within the pit area and dykes are used to contain the tailings. Many of the materials used to construct the dykes come from the mining operation. The mine plan scheduled both ore and dyke material concurrently. Dykes were constructed simultaneously as the mine phase advanced. A model was used to classify an oil sands block model into different material types. A mixed integer goal programming (MIGP) method was used to generate a strategic schedule. Block clustering techniques were used to large-scale mine planning projects. The method was used to verify and validate synthetic and real case data related to the cost of mining all material as waste, and the extra cost of mining dyke material. A case study of an oil sands project was used to demonstrate the method. The study showed that the developed model generates a smooth and uniform strategic schedule for large-scale mine planning projects. tabs., figs.
A mathematical programming approach for sequential clustering of dynamic networks
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
Determining on-fault earthquake magnitude distributions from integer programming
Geist, Eric L.; Parsons, Thomas E.
2018-01-01
Earthquake magnitude distributions among faults within a fault system are determined from regional seismicity and fault slip rates using binary integer programming. A synthetic earthquake catalog (i.e., list of randomly sampled magnitudes) that spans millennia is first formed, assuming that regional seismicity follows a Gutenberg-Richter relation. Each earthquake in the synthetic catalog can occur on any fault and at any location. The objective is to minimize misfits in the target slip rate for each fault, where slip for each earthquake is scaled from its magnitude. The decision vector consists of binary variables indicating which locations are optimal among all possibilities. Uncertainty estimates in fault slip rates provide explicit upper and lower bounding constraints to the problem. An implicit constraint is that an earthquake can only be located on a fault if it is long enough to contain that earthquake. A general mixed-integer programming solver, consisting of a number of different algorithms, is used to determine the optimal decision vector. A case study is presented for the State of California, where a 4 kyr synthetic earthquake catalog is created and faults with slip ≥3 mm/yr are considered, resulting in >106 variables. The optimal magnitude distributions for each of the faults in the system span a rich diversity of shapes, ranging from characteristic to power-law distributions.
Oil sands mine planning and waste management using goal programming
International Nuclear Information System (INIS)
Ben-Awuah, E.; Askari-Nasab, H.; Alberta Univ., Edmonton, AB
2010-01-01
A goal programming method was used to plan waste management processes at an oil sands mine. This method requires the decision maker (DM) to set goals. Mine planning is used to determine a block extraction schedule that maximizes net present value (NPV). Due to land restrictions, tailings facilities are sited within the pit area and dykes are used to contain the tailings. Many of the materials used to construct the dykes come from the mining operation. The mine plan scheduled both ore and dyke material concurrently. Dykes were constructed simultaneously as the mine phase advanced. A model was used to classify an oil sands block model into different material types. A mixed integer goal programming (MIGP) method was used to generate a strategic schedule. Block clustering techniques were used to large-scale mine planning projects. The method was used to verify and validate synthetic and real case data related to the cost of mining all material as waste, and the extra cost of mining dyke material. A case study of an oil sands project was used to demonstrate the method. The study showed that the developed model generates a smooth and uniform strategic schedule for large-scale mine planning projects. tabs., figs.
Optimising an integrated crop-livestock farm using risk programming
Directory of Open Access Journals (Sweden)
SE Visagie
2004-06-01
Full Text Available Numerous studies have analysed farm planning decisions focusing on producer risk preferences. Few studies have focussed on the farm planning decisions in an integrated croplivestock farm context. Income variability and means of managing risk continues to receive much attention in farm planning research. Different risk programming models have attempted to focus on minimising the income variability of farm activities. This study attempts to identify the optimal mix of crops and the number of animals the farm needs to keep in the presence of crop production risk for a range of risk levels. A mixed integer linear programming model was developed to model the decision environment faced by an integrated crop-livestock farmer. The deviation of income from the expected value was used as a measure of risk. A case study is presented with representative data from a farm in the Swartland area. An investigation of the results of the model under different constraints shows that, in general, strategies that depend on crop rotation principles are preferred to strategies that follow mono-crop production practices.
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...
International Nuclear Information System (INIS)
Pisciella, P.; Vespucci, M.T.; Bertocchi, M.; Zigrino, S.
2016-01-01
We propose a multi-stage stochastic optimization model for the generation capacity expansion problem of a price-taker power producer. Uncertainties regarding the evolution of electricity prices and fuel costs play a major role in long term investment decisions, therefore the objective function represents a trade-off between expected profit and risk. The Conditional Value at Risk is the risk measure used and is defined by a nested formulation that guarantees time consistency in the multi-stage model. The proposed model allows one to determine a long term expansion plan which takes into account uncertainty, while the LCoE approach, currently used by decision makers, only allows one to determine which technology should be chosen for the next power plant to be built. A sensitivity analysis is performed with respect to the risk weighting factor and budget amount. - Highlights: • We propose a time consistent risk averse multi-stage model for capacity expansion. • We introduce a case study with uncertainty on electricity prices and fuel costs. • Increased budget moves the investment from gas towards renewables and then coal. • Increased risk aversion moves the investment from coal towards renewables. • Time inconsistency leads to a profit gap between planned and implemented policies.
ALPS - A LINEAR PROGRAM SOLVER
Viterna, L. A.
1994-01-01
Linear programming is a widely-used engineering and management tool. Scheduling, resource allocation, and production planning are all well-known applications of linear programs (LP's). Most LP's are too large to be solved by hand, so over the decades many computer codes for solving LP's have been developed. ALPS, A Linear Program Solver, is a full-featured LP analysis program. ALPS can solve plain linear programs as well as more complicated mixed integer and pure integer programs. ALPS also contains an efficient solution technique for pure binary (0-1 integer) programs. One of the many weaknesses of LP solvers is the lack of interaction with the user. ALPS is a menu-driven program with no special commands or keywords to learn. In addition, ALPS contains a full-screen editor to enter and maintain the LP formulation. These formulations can be written to and read from plain ASCII files for portability. For those less experienced in LP formulation, ALPS contains a problem "parser" which checks the formulation for errors. ALPS creates fully formatted, readable reports that can be sent to a printer or output file. ALPS is written entirely in IBM's APL2/PC product, Version 1.01. The APL2 workspace containing all the ALPS code can be run on any APL2/PC system (AT or 386). On a 32-bit system, this configuration can take advantage of all extended memory. The user can also examine and modify the ALPS code. The APL2 workspace has also been "packed" to be run on any DOS system (without APL2) as a stand-alone "EXE" file, but has limited memory capacity on a 640K system. A numeric coprocessor (80X87) is optional but recommended. The standard distribution medium for ALPS is a 5.25 inch 360K MS-DOS format diskette. IBM, IBM PC and IBM APL2 are registered trademarks of International Business Machines Corporation. MS-DOS is a registered trademark of Microsoft Corporation.
Zhang, Xiaodong; Huang, Gordon
2013-02-15
Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p(i) levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help the decision makers justify and/or adjust their waste management strategies based on their implicit knowledge and preferences. Copyright © 2012 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Yan Sun
2018-01-01
Full Text Available Capacity uncertainty is a common issue in the transportation planning field. However, few studies discuss the intermodal routing problem with service capacity uncertainty. Based on our previous study on the intermodal routing under deterministic capacity consideration, we systematically explore how service capacity uncertainty influences the intermodal routing decision. First of all, we adopt trapezoidal fuzzy numbers to describe the uncertain information of the service capacity, and further transform the deterministic capacity constraint into a fuzzy chance constraint based on fuzzy credibility measure. We then integrate such fuzzy chance constraint into the mixed-integer linear programming (MILP model proposed in our previous study to develop a fuzzy chance-constrained programming model. To enable the improved model to be effectively programmed in the standard mathematical programming software and solved by exact solution algorithms, a crisp equivalent linear reformulation of the fuzzy chance constraint is generated. Finally, we modify the empirical case presented in our previous study by replacing the deterministic service capacities with trapezoidal fuzzy ones. Using the modified empirical case, we utilize sensitivity analysis and fuzzy simulation to analyze the influence of service capacity uncertainty on the intermodal routing decision, and summarize some interesting insights that are helpful for decision makers.
Energy Technology Data Exchange (ETDEWEB)
Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami
2017-03-27
Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.
International Nuclear Information System (INIS)
Piacentino, A.; Cardona, F.
2008-01-01
The optimization of synthesis, design and operation in trigeneration systems for building applications is a quite complex task, due to the high number of decision variables, the presence of irregular heat, cooling and electric load profiles and the variable electricity price. Consequently, computer-aided techniques are usually adopted to achieve the optimal solution, based either on iterative techniques, linear or non-linear programming or evolutionary search. Large efforts have been made in improving algorithm efficiency, which have resulted in an increasingly rapid convergence to the optimal solution and in reduced calculation time; robust algorithm have also been formulated, assuming stochastic behaviour for energy loads and prices. This paper is based on the assumption that margins for improvements in the optimization of trigeneration systems still exist, which require an in-depth understanding of plant's energetic behaviour. Robustness in the optimization of trigeneration systems has more to do with a 'correct and comprehensive' than with an 'efficient' modelling, being larger efforts required to energy specialists rather than to experts in efficient algorithms. With reference to a mixed integer linear programming model implemented in MatLab for a trigeneration system including a pressurized (medium temperature) heat storage, the relevant contribute of thermoeconomics and energo-environmental analysis in the phase of mathematical modelling and code testing are shown
Risk averse optimal operation of a virtual power plant using two stage stochastic programming
International Nuclear Information System (INIS)
Tajeddini, Mohammad Amin; Rahimi-Kian, Ashkan; Soroudi, Alireza
2014-01-01
VPP (Virtual Power Plant) is defined as a cluster of energy conversion/storage units which are centrally operated in order to improve the technical and economic performance. This paper addresses the optimal operation of a VPP considering the risk factors affecting its daily operation profits. The optimal operation is modelled in both day ahead and balancing markets as a two-stage stochastic mixed integer linear programming in order to maximize a GenCo (generation companies) expected profit. Furthermore, the CVaR (Conditional Value at Risk) is used as a risk measure technique in order to control the risk of low profit scenarios. The uncertain parameters, including the PV power output, wind power output and day-ahead market prices are modelled through scenarios. The proposed model is successfully applied to a real case study to show its applicability and the results are presented and thoroughly discussed. - Highlights: • Virtual power plant modelling considering a set of energy generating and conversion units. • Uncertainty modelling using two stage stochastic programming technique. • Risk modelling using conditional value at risk. • Flexible operation of renewable energy resources. • Electricity price uncertainty in day ahead energy markets
Energy Technology Data Exchange (ETDEWEB)
Zhan, Yiduo; Zheng, Qipeng P.; Wang, Jianhui; Pinson, Pierre
2017-07-01
Power generation expansion planning needs to deal with future uncertainties carefully, given that the invested generation assets will be in operation for a long time. Many stochastic programming models have been proposed to tackle this challenge. However, most previous works assume predetermined future uncertainties (i.e., fixed random outcomes with given probabilities). In several recent studies of generation assets' planning (e.g., thermal versus renewable), new findings show that the investment decisions could affect the future uncertainties as well. To this end, this paper proposes a multistage decision-dependent stochastic optimization model for long-term large-scale generation expansion planning, where large amounts of wind power are involved. In the decision-dependent model, the future uncertainties are not only affecting but also affected by the current decisions. In particular, the probability distribution function is determined by not only input parameters but also decision variables. To deal with the nonlinear constraints in our model, a quasi-exact solution approach is then introduced to reformulate the multistage stochastic investment model to a mixed-integer linear programming model. The wind penetration, investment decisions, and the optimality of the decision-dependent model are evaluated in a series of multistage case studies. The results show that the proposed decision-dependent model provides effective optimization solutions for long-term generation expansion planning.
International Nuclear Information System (INIS)
Jackson, M.A.
1982-01-01
The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, this model is elaborated to produce the required program outputs; third, the resulting program is transformed to run efficiently in the execution environment. The first two stages deal in network structures of sequential processes; only the third is concerned with procedure hierarchies. (orig.)
Jackson, M A
1982-01-01
The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, thi...
International Nuclear Information System (INIS)
Mavrotas, George; Florios, Kostas; Vlachou, Dimitra
2010-01-01
For more than 40 years, Mathematical Programming is the traditional tool for energy planning at the national or regional level aiming at cost minimization subject to specific technological, political and demand satisfaction constraints. The liberalization of the energy market along with the ongoing technical progress increased the level of competition and forced energy consumers, even at the unit level, to make their choices among a large number of alternative or complementary energy technologies, fuels and/or suppliers. In the present work we develop a modelling framework for energy planning in units of the tertiary sector giving special emphasis to model reduction and to the uncertainty of the economic parameters. In the given case study, the energy rehabilitation of a hospital in Athens is examined and the installation of a cogeneration, absorption and compression unit is examined for the supply of the electricity, heating and cooling load. The basic innovation of the given energy model lies in the uncertainty modelling through the combined use of Mathematical Programming (namely, Mixed Integer Linear Programming, MILP) and Monte Carlo simulation that permits the risk management for the most volatile parameters of the objective function such as the fuel costs and the interest rate. The results come in the form of probability distributions that provide fruitful information to the decision maker. The effect of model reduction through appropriate data compression of the load data is also addressed.
Directory of Open Access Journals (Sweden)
Zhongwen Li
2016-06-01
Full Text Available Microgrids (MGs are presented as a cornerstone of smart grids. With the potential to integrate intermittent renewable energy sources (RES in a flexible and environmental way, the MG concept has gained even more attention. Due to the randomness of RES, load, and electricity price in MG, the forecast errors of MGs will affect the performance of the power scheduling and the operating cost of an MG. In this paper, a combined stochastic programming and receding horizon control (SPRHC strategy is proposed for microgrid energy management under uncertainty, which combines the advantages of two-stage stochastic programming (SP and receding horizon control (RHC strategy. With an SP strategy, a scheduling plan can be derived that minimizes the risk of uncertainty by involving the uncertainty of MG in the optimization model. With an RHC strategy, the uncertainty within the MG can be further compensated through a feedback mechanism with the lately updated forecast information. In our approach, a proper strategy is also proposed to maintain the SP model as a mixed integer linear constrained quadratic programming (MILCQP problem, which is solvable without resorting to any heuristics algorithms. The results of numerical experiments explicitly demonstrate the superiority of the proposed strategy for both island and grid-connected operating modes of an MG.
Directory of Open Access Journals (Sweden)
Kody M. Powell
2016-03-01
Full Text Available This work presents a methodology to represent logical decisions in differential algebraic equation simulation and constrained optimization problems using a set of continuous algebraic equations. The formulations may be used when state variables trigger a change in process dynamics, and introduces a pseudo-binary decision variable, which is continuous, but should only have valid solutions at values of either zero or one within a finite time horizon. This formulation enables dynamic optimization problems with logical disjunctions to be solved by simultaneous solution methods without using methods such as mixed integer programming. Several case studies are given to illustrate the value of this methodology including nonlinear model predictive control of a chemical reactor using a surge tank with overflow to buffer disturbances in feed flow rate. Although this work contains novel methodologies for solving dynamic algebraic equation (DAE constrained problems where the system may experience an abrupt change in dynamics that may otherwise require a conditional statement, there remain substantial limitations to this methodology, including a limited domain where problems may converge and the possibility for ill-conditioning. Although the problems presented use only continuous algebraic equations, the formulation has inherent non-smoothness. Hence, these problems must be solved with care and only in select circumstances, such as in simulation or situations when the solution is expected to be near the solver’s initial point.
International Nuclear Information System (INIS)
Partovi, Farzad; Nikzad, Mehdi; Mozafari, Babak; Ranjbar, Ali Mohamad
2011-01-01
In this paper a new algorithm for allocating energy and determining the optimum amount of network active power reserve capacity and the share of generating units and demand side contribution in providing reserve capacity requirements for day-ahead market is presented. In the proposed method, the optimum amount of reserve requirement is determined based on network security set by operator. In this regard, Expected Load Not Supplied (ELNS) is used to evaluate system security in each hour. The proposed method has been implemented over the IEEE 24-bus test system and the results are compared with a deterministic security approach, which considers certain and fixed amount of reserve capacity in each hour. This comparison is done from economic and technical points of view. The promising results show the effectiveness of the proposed model which is formulated as mixed integer linear programming (MILP) and solved by GAMS software. -- Highlights: → Determination of optimal spinning reserve capacity requirement in order to satisfy desired security level set by system operator based on stochastic approach. → Scheduling energy and spinning reserve markets simultaneously. → Comparing the stochastic approach with deterministic approach to determine the advantages and disadvantages of each. → Examine the effect of demand response participation in reserve market to provide spinning reserve.
Impact of Demand Response Programs on Optimal Operation of Multi-Microgrid System
Directory of Open Access Journals (Sweden)
Anh-Duc Nguyen
2018-06-01
Full Text Available The increased penetration of renewables is beneficial for power systems but it poses several challenges, i.e., uncertainty in power supply, power quality issues, and other technical problems. Backup generators or storage system have been proposed to solve this problem but there are limitations remaining due to high installation and maintenance cost. Furthermore, peak load is also an issue in the power distribution system. Due to the adjustable characteristics of loads, strategies on demand side such as demand response (DR are more appropriate in order to deal with these challenges. Therefore, this paper studies how DR programs influence the operation of the multi-microgrid (MMG. The implementation is executed based on a hierarchical energy management system (HiEMS including microgrid EMSs (MG-EMSs responsible for local optimization in each MG and community EMS (C-EMS responsible for community optimization in the MMG. Mixed integer linear programming (MILP-based mathematical models are built for MMG optimal operation. Five scenarios consisting of single DR programs and DR groups are tested in an MMG test system to evaluate their impact on MMG operation. Among the five scenarios, some DR programs apply curtailing strategies, resulting in a study about the influence of base load value and curtailable load percentage on the amount of curtailed load and shifted load as well as the operation cost of the MMG. Furthermore, the impact of DR programs on the amount of external and internal trading power in the MMG is also examined. In summary, each individual DR program or group could be handy in certain situations depending on the interest of the MMG such as external trading, self-sufficiency or operation cost minimization.
Yu, Hao; Solvang, Wei Deng
2016-05-31
Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
Directory of Open Access Journals (Sweden)
Hao Yu
2016-05-01
Full Text Available Hazardous waste location-routing problems are of importance due to the potential risk for nearby residents and the environment. In this paper, an improved mathematical formulation is developed based upon a multi-objective mixed integer programming approach. The model aims at assisting decision makers in selecting locations for different facilities including treatment plants, recycling plants and disposal sites, providing appropriate technologies for hazardous waste treatment, and routing transportation. In the model, two critical factors are taken into account: system operating costs and risk imposed on local residents, and a compensation factor is introduced to the risk objective function in order to account for the fact that the risk level imposed by one type of hazardous waste or treatment technology may significantly vary from that of other types. Besides, the policy instruments for promoting waste recycling are considered, and their influence on the costs and risk of hazardous waste management is also discussed. The model is coded and calculated in Lingo optimization solver, and the augmented ε-constraint method is employed to generate the Pareto optimal curve of the multi-objective optimization problem. The trade-off between different objectives is illustrated in the numerical experiment.
Directory of Open Access Journals (Sweden)
Masoud Rezaei
2013-10-01
Full Text Available In today’s competitive business environment, companies strive to increase their market shares. All companies clearly understand that they have to reach this goal by implementing cost effective methods and increase profits as much as possible. The cost of purchasing raw materials and component parts are significant portion of products in most manufacturing firms. Supplier selection and evaluation have been widely recognized to be one of the most substantial issues on material purchasing. In order to choose reliable suppliers it is necessary to have a trade-off between some tangible and intangible factors where some of them are in serious conflict. In this paper, an integrated technique of analytical network process improved by VIKOR and fuzzy sets theory and multi-objective mixed integer nonlinear programming is proposed to determine the appropriate suppliers. The proposed model of this paper also determines the order quantity allocated to each supplier in the case of multiple sourcing, multiple products and multi-period time horizon for an Iranian cable company.
Energy Technology Data Exchange (ETDEWEB)
Zhang, Xiaodong, E-mail: xiaodong.zhang@beg.utexas.edu [Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX 78713 (United States); Huang, Gordon [Institute of Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)
2013-02-15
Highlights: ► A dynamic stochastic possibilistic multiobjective programming model is developed. ► Greenhouse gas emission control is considered. ► Three planning scenarios are analyzed and compared. ► Optimal decision schemes under three scenarios and different p{sub i} levels are obtained. ► Tradeoffs between economics and environment are reflected. -- Abstract: Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p{sub i} levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help
International Nuclear Information System (INIS)
Ahmadi, Abdollah; Charwand, Mansour; Siano, Pierluigi; Nezhad, Ali Esmaeel; Sarno, Debora; Gitizadeh, Mohsen; Raeisi, Fatima
2016-01-01
In order to supply the demands of the end users in a competitive market, a distribution company purchases energy from the wholesale market while other options would be in access in the case of possessing distributed generation units and interruptible loads. In this regard, this study presents a two-stage stochastic programming model for a distribution company energy acquisition market model to manage the involvement of different electric energy resources characterized by uncertainties with the minimum cost. In particular, the distribution company operations planning over a day-ahead horizon is modeled as a stochastic mathematical optimization, with the objective of minimizing costs. By this, distribution company decisions on grid purchase, owned distributed generation units and interruptible load scheduling are determined. Then, these decisions are considered as boundary constraints to a second step, which deals with distribution company's operations in the hour-ahead market with the objective of minimizing the short-term cost. The uncertainties in spot market prices and wind speed are modeled by means of probability distribution functions of their forecast errors and the roulette wheel mechanism and lattice Monte Carlo simulation are used to generate scenarios. Numerical results show the capability of the proposed method. - Highlights: • Proposing a new a stochastic-based two-stage operations framework in retail competitive markets. • Proposing a Mixed Integer Non-Linear stochastic programming. • Employing roulette wheel mechanism and Lattice Monte Carlo Simulation.
Water SA - Vol 42, No 4 (2016)
African Journals Online (AJOL)
A feasibility and implementation model of small-scale hydropower ... Water quality modelling and optimisation of wastewater treatment network using mixed integer programming · EMAIL FREE FULL TEXT EMAIL FREE FULL TEXT
Flow Formulations for Curriculum-based Course Timetabling
DEFF Research Database (Denmark)
Bagger, Niels-Christian Fink; Kristiansen, Simon; Sørensen, Matias
2017-01-01
lower bound on one data instance in the benchmark data set from the second international timetabling competition. Regarding upper bounds, the formulation based on the minimum cost flow problem performs better on average than other mixed integer programming approaches for the CTT.......In this paper we present two mixed-integer programming formulations for the Curriculum based Course Timetabling Problem (CTT). We show that the formulations contain underlying network structures by dividing the CTT into two separate models and then connect the two models using flow formulation...... techniques. The first mixed-integer programming formulation is based on an underlying minimum cost flow problem, which decreases the number of integer variables significantly and improves the performance compared to an intuitive mixed-integer programming formulation. The second formulation is based...
Directory of Open Access Journals (Sweden)
Hao Yu
2016-12-01
Full Text Available Today, the increased public concern about sustainable development and more stringent environmental regulations have become important driving forces for value recovery from end-of-life and end-of use products through reverse logistics. Waste electrical and electronic equipment (WEEE contains both valuable components that need to be recycled and hazardous substances that have to be properly treated or disposed of, so the design of a reverse logistics system for sustainable treatment of WEEE is of paramount importance. This paper presents a stochastic mixed integer programming model for designing and planning a generic multi-source, multi-echelon, capacitated, and sustainable reverse logistics network for WEEE management under uncertainty. The model takes into account both economic efficiency and environmental impacts in decision-making, and the environmental impacts are evaluated in terms of carbon emissions. A multi-criteria two-stage scenario-based solution method is employed and further developed in this study for generating the optimal solution for the stochastic optimization problem. The proposed model and solution method are validated through a numerical experiment and sensitivity analyses presented later in this paper, and an analysis of the results is also given to provide a deep managerial insight into the application of the proposed stochastic optimization model.
International Nuclear Information System (INIS)
Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio; Morais, Hugo; Vale, Zita
2015-01-01
Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand. - Highlights: • Asset-light electricity retail providers subject to financial risks. • Incentive-based demand response program to manage the financial risks. • Maximizing the payoff of electricity retail providers in day-ahead market. • Mixed integer nonlinear programming to manage the risks
Energy Technology Data Exchange (ETDEWEB)
Kahn, Marcio [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil); Hamacher, Silvio [Pontificia Universidade Catolica do Rio de Janeiro (PUC-Rio), RJ (Brazil)
2012-07-01
A mathematical programming model to support the decision maker how to identify the optimal infrastructure design solution to the Development and Production of an oil field is proposed in this paper. The problem addressed is to maximize the economic return of the additional production of oil in a field with existing production infrastructure installed and as a proposed solution to this problem a model of mixed integer linear programming was developed. This formulation allows identifying the optimal level of exploration and production of a field subject to uncertainties. The variables to be defined are: Floating Production Units installed to be utilized and their oil production, the use of manifolds or not, and the number of wells that will be connected to the Floating Production Units. Finally, the model provides the optimal development plan with the best economic return considering the constraints and uncertainties of the problem. Besides the optimal solution, sensitivity analyzes were performed improving the understanding of the problem and providing useful information to the decision maker. (author)
Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami
2017-08-01
Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.
Mathematical programming model for heat exchanger design through optimization of partial objectives
International Nuclear Information System (INIS)
Onishi, Viviani C.; Ravagnani, Mauro A.S.S.; Caballero, José A.
2013-01-01
Highlights: • Rigorous design of shell-and-tube heat exchangers according to TEMA standards. • Division of the problem into sets of equations that are easier to solve. • Selected heuristic objective functions based on the physical behavior of the problem. • Sequential optimization approach to avoid solutions stuck in local minimum. • The results obtained with this model improved the values reported in the literature. - Abstract: Mathematical programming can be used for the optimal design of shell-and-tube heat exchangers (STHEs). This paper proposes a mixed integer non-linear programming (MINLP) model for the design of STHEs, following rigorously the standards of the Tubular Exchanger Manufacturers Association (TEMA). Bell–Delaware Method is used for the shell-side calculations. This approach produces a large and non-convex model that cannot be solved to global optimality with the current state of the art solvers. Notwithstanding, it is proposed to perform a sequential optimization approach of partial objective targets through the division of the problem into sets of related equations that are easier to solve. For each one of these problems a heuristic objective function is selected based on the physical behavior of the problem. The global optimal solution of the original problem cannot be ensured even in the case in which each of the sub-problems is solved to global optimality, but at least a very good solution is always guaranteed. Three cases extracted from the literature were studied. The results showed that in all cases the values obtained using the proposed MINLP model containing multiple objective functions improved the values presented in the literature
International Nuclear Information System (INIS)
Shaban Boloukat, Mohammad Hadi; Akbari Foroud, Asghar
2016-01-01
This paper represents a stochastic approach for long-term optimal resource expansion planning of a grid-connected microgrid (MG) containing different technologies as intermittent renewable energy resources, energy storage systems and thermal resources. Maximizing profit and reliability, along with minimizing investment and operation costs, are major objectives which have been considered in this model. Also, the impacts of intermittency and uncertainty in renewable energy resources were investigated. The interval linear programming (ILP) was applied for modelling inherent stochastic nature of the renewable energy resources. ILP presents some superiority in modelling of uncertainties in MG planning. The problem was formulated as a mixed-integer linear programming. It has been demonstrated previously that the benders decomposition (BD) served as an effective tool for solving such problems. BD divides the original problem into a master (investment) problem and operation and reliability subproblems. In this paper a multiperiod MG planning is presented, considering life time, maximum penetration limit of each technology, interest rate, capital recovery factor and investment fund. Real-time energy exchange with the utility is covered, with a consideration of variable tariffs at different load blocks. The presented approach can help MG planners to adopt best decision under various uncertainty levels based on their budgetary policies. - Highlights: • Considering uncertain nature of the renewable resources with applying ILP. • Considering the effect of intermittency of renewable in MG planning. • Multiobjective MG planning problem which covers cost, profit and reliability. • Multiperiod approach for MG planning considering life time and MPL of technologies. • Presenting real-time energy exchange with the utility considering variable tariffs.
International Nuclear Information System (INIS)
Majidi, Majid; Nojavan, Sayyad; Zare, Kazem
2017-01-01
Highlights: • On-grid photovoltaic/battery/fuel cell system is considered as hybrid system. • Thermal and electrical operation of hybrid energy system is studied. • Hybrid energy system is used to reduce dependency on upstream grid for load serving. • Demand response program is proposed to manage the electrical load. • Demand response program is proposed to reduce hybrid energy system’s operation cost. - Abstract: In this paper, cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system has been evaluated in the presence of demand response program. Each load curve has off-peak, mid and peak time periods in which the energy prices are different. Demand response program transfers some amount of load from peak periods to other periods to flatten the load curve and minimize total cost. So, the main goal is to meet the energy demand and propose a cost-efficient approach to minimize system’s total cost including system’s electrical cost and thermal cost and the revenue from exporting power to the upstream grid. A battery has been utilized as an electrical energy storage system and a heat storage tank is used as a thermal energy storage system to save energy in off-peak and mid-peak hours and then supply load in peak hours which leads to reduction of cost. The proposed cost-efficient operation problem of photovoltaic/battery/fuel cell hybrid energy system is modeled by a mixed-integer linear program and solved by General algebraic modeling system optimization software under CPLEX solver. Two case studies are investigated to show the effects of demand response program on reduction of total cost.
International Nuclear Information System (INIS)
Tabar, Vahid Sohrabi; Jirdehi, Mehdi Ahmadi; Hemmati, Reza
2017-01-01
Renewable energy resources are often known as cost-effective and lucrative resources and have been widely developed due to environmental-economic issues. Renewable energy utilization even in small scale (e.g., microgrid networks) has attracted significant attention. Energy management in microgrid can be carried out based on the generating side management or demand side management. In this paper, portable renewable energy resource are modeled and included in microgrid energy management as a demand response option. Utilizing such resources could supply the load when microgrid cannot serve the demand. This paper addresses energy management and scheduling in microgrid including thermal and electrical loads, renewable energy sources (solar and wind), CHP, conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical ones), and portable renewable energy resource (PRER). Operational cost of microgrid and air pollution are considered as objective functions. Uncertainties related to the parameters are incorporated to make a stochastic programming. The proposed problem is expressed as a constrained, multi-objective, linear, and mixed-integer programing. Augmented Epsilon-constraint method is used to solve the problem. Final results and calculations are achieved using GAMS24.1.3/CPLEX12.5.1. Simulation results demonstrate the viability and effectiveness of the proposed method in microgrid energy management. - Highlights: • Introducing portable renewable energy resource (PRER) and considering effect of them. • Considering reserve margin and sensitivity analysis for validate robustness. • Multi objective and stochastic management with considering various loads and sources. • Using augmented Epsilon-constraint method to solve multi objective program. • Highly decreasing total cost and pollution with PRER in stochastic state.
System network planning expansion using mathematical programming, genetic algorithms and tabu search
International Nuclear Information System (INIS)
Sadegheih, A.; Drake, P.R.
2008-01-01
In this paper, system network planning expansion is formulated for mixed integer programming, a genetic algorithm (GA) and tabu search (TS). Compared with other optimization methods, GAs are suitable for traversing large search spaces, since they can do this relatively rapidly and because the use of mutation diverts the method away from local minima, which will tend to become more common as the search space increases in size. GA's give an excellent trade off between solution quality and computing time and flexibility for taking into account specific constraints in real situations. TS has emerged as a new, highly efficient, search paradigm for finding quality solutions to combinatorial problems. It is characterized by gathering knowledge during the search and subsequently profiting from this knowledge. The attractiveness of the technique comes from its ability to escape local optimality. The cost function of this problem consists of the capital investment cost in discrete form, the cost of transmission losses and the power generation costs. The DC load flow equations for the network are embedded in the constraints of the mathematical model to avoid sub-optimal solutions that can arise if the enforcement of such constraints is done in an indirect way. The solution of the model gives the best line additions and also provides information regarding the optimal generation at each generation point. This method of solution is demonstrated on the expansion of a 10 bus bar system to 18 bus bars. Finally, a steady-state genetic algorithm is employed rather than generational replacement, also uniform crossover is used
International Nuclear Information System (INIS)
Ghalelou, Afshin Najafi; Fakhri, Alireza Pashaei; Nojavan, Sayyad; Majidi, Majid; Hatami, Hojat
2016-01-01
Highlights: • Optimal stochastic energy management of renewable energy sources (RESs) is proposed. • The compressed air energy storage (CAES) besides RESs is used in the presence of DRP. • Determination charge and discharge of CAES in order to reduce the expected operation cost. • Moreover, demand response program (DRP) is proposed to minimize the operation cost. • The uncertainty modeling of input data are considered in the proposed stochastic framework. - Abstract: In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of-use (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive period to the cheap one in order to flatten the load curve and minimize the operation cost, consequently. The proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering technical and physical constraints. The proposed model is formulated as mixed integer linear programming (MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package. Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained, which indicate the validity of the proposed stochastic program.
Li, Y P; Huang, G H
2010-09-15
Considerable public concerns have been raised in the past decades since a large amount of pollutant emissions from municipal solid waste (MSW) disposal of processes pose risks on surrounding environment and human health. Moreover, in MSW management, various uncertainties exist in the related costs, impact factors and objectives, which can affect the optimization processes and the decision schemes generated. In this study, an interval-based possibilistic programming (IBPP) method is developed for planning the MSW management with minimized system cost and environmental impact under uncertainty. The developed method can deal with uncertainties expressed as interval values and fuzzy sets in the left- and right-hand sides of constraints and objective function. An interactive algorithm is provided for solving the IBPP problem, which does not lead to more complicated intermediate submodels and has a relatively low computational requirement. The developed model is applied to a case study of planning a MSW management system, where mixed integer linear programming (MILP) technique is introduced into the IBPP framework to facilitate dynamic analysis for decisions of timing, sizing and siting in terms of capacity expansion for waste-management facilities. Three cases based on different waste-management policies are examined. The results obtained indicate that inclusion of environmental impacts in the optimization model can change the traditional waste-allocation pattern merely based on the economic-oriented planning approach. The results obtained can help identify desired alternatives for managing MSW, which has advantages in providing compromised schemes under an integrated consideration of economic efficiency and environmental impact under uncertainty. Copyright 2010 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Nojavan, Sayyad; Majidi, Majid; Najafi-Ghalelou, Afshin; Ghahramani, Mehrdad; Zare, Kazem
2017-01-01
Highlights: • Cost-emission performance of PV/battery/fuel cell hybrid energy system is studied. • Multi-objective optimization model for cost-emission performance is proposed. • ε-constraint method is proposed to produce Pareto solutions of multi-objective model. • Fuzzy satisfying approach selected the best optimal solution from Pareto solutions. • Demand response program is proposed to reduce both cost and emission. - Abstract: Optimal operation of hybrid energy systems is a big challenge in power systems. Nowadays, in addition to the optimum performance of energy systems, their pollution issue has been a hot topic between researchers. In this paper, a multi-objective model is proposed for economic and environmental operation of a battery/fuel cell/photovoltaic (PV) hybrid energy system in the presence of demand response program (DRP). In the proposed paper, the first objective function is minimization of total cost of hybrid energy system. The second objective function is minimization of total CO_2 emission which is in conflict with the first objective function. So, a multi-objective optimization model is presented to model the hybrid system’s optimal and environmental performance problem with considering DRP. The proposed multi-objective model is solved by ε-constraint method and then fuzzy satisfying technique is employed to select the best possible solution. Also, positive effects of DRP on the economic and environmental performance of hybrid system are analyzed. A mixed-integer linear program is used to simulate the proposed model and the obtained results are compared with weighted sum approach to show the effectiveness of proposed method.
Multistage Stochastic Programming and its Applications in Energy Systems Modeling and Optimization
Golari, Mehdi
Electric energy constitutes one of the most crucial elements to almost every aspect of life of people. The modern electric power systems face several challenges such as efficiency, economics, sustainability, and reliability. Increase in electrical energy demand, distributed generations, integration of uncertain renewable energy resources, and demand side management are among the main underlying reasons of such growing complexity. Additionally, the elements of power systems are often vulnerable to failures because of many reasons, such as system limits, weak conditions, unexpected events, hidden failures, human errors, terrorist attacks, and natural disasters. One common factor complicating the operation of electrical power systems is the underlying uncertainties from the demands, supplies and failures of system components. Stochastic programming provides a mathematical framework for decision making under uncertainty. It enables a decision maker to incorporate some knowledge of the intrinsic uncertainty into the decision making process. In this dissertation, we focus on application of two-stage and multistage stochastic programming approaches to electric energy systems modeling and optimization. Particularly, we develop models and algorithms addressing the sustainability and reliability issues in power systems. First, we consider how to improve the reliability of power systems under severe failures or contingencies prone to cascading blackouts by so called islanding operations. We present a two-stage stochastic mixed-integer model to find optimal islanding operations as a powerful preventive action against cascading failures in case of extreme contingencies. Further, we study the properties of this problem and propose efficient solution methods to solve this problem for large-scale power systems. We present the numerical results showing the effectiveness of the model and investigate the performance of the solution methods. Next, we address the sustainability issue
International Nuclear Information System (INIS)
Sun Wei; Huang, Guo H.; Lv Ying; Li Gongchen
2012-01-01
Highlights: ► Inexact piecewise-linearization-based fuzzy flexible programming is proposed. ► It’s the first application to waste management under multiple complexities. ► It tackles nonlinear economies-of-scale effects in interval-parameter constraints. ► It estimates costs more accurately than the linear-regression-based model. ► Uncertainties are decreased and more satisfactory interval solutions are obtained. - Abstract: To tackle nonlinear economies-of-scale (EOS) effects in interval-parameter constraints for a representative waste management problem, an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model is developed. In IPFP, interval parameters for waste amounts and transportation/operation costs can be quantified; aspiration levels for net system costs, as well as tolerance intervals for both capacities of waste treatment facilities and waste generation rates can be reflected; and the nonlinear EOS effects transformed from objective function to constraints can be approximated. An interactive algorithm is proposed for solving the IPFP model, which in nature is an interval-parameter mixed-integer quadratically constrained programming model. To demonstrate the IPFP’s advantages, two alternative models are developed to compare their performances. One is a conventional linear-regression-based inexact fuzzy programming model (IPFP2) and the other is an IPFP model with all right-hand-sides of fussy constraints being the corresponding interval numbers (IPFP3). The comparison results between IPFP and IPFP2 indicate that the optimized waste amounts would have the similar patterns in both models. However, when dealing with EOS effects in constraints, the IPFP2 may underestimate the net system costs while the IPFP can estimate the costs more accurately. The comparison results between IPFP and IPFP3 indicate that their solutions would be significantly different. The decreased system uncertainties in IPFP’s solutions demonstrate
Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2018-01-01
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP
Liang, Bin; Li, Yongbao; Wei, Ran; Guo, Bin; Xu, Xuang; Liu, Bo; Li, Jiafeng; Wu, Qiuwen; Zhou, Fugen
2018-01-05
With robot-controlled linac positioning, robotic radiotherapy systems such as CyberKnife significantly increase freedom of radiation beam placement, but also impose more challenges on treatment plan optimization. The resampling mechanism in the vendor-supplied treatment planning system (MultiPlan) cannot fully explore the increased beam direction search space. Besides, a sparse treatment plan (using fewer beams) is desired to improve treatment efficiency. This study proposes a singular value decomposition linear programming (SVDLP) optimization technique for circular collimator based robotic radiotherapy. The SVDLP approach initializes the input beams by simulating the process of covering the entire target volume with equivalent beam tapers. The requirements on dosimetry distribution are modeled as hard and soft constraints, and the sparsity of the treatment plan is achieved by compressive sensing. The proposed linear programming (LP) model optimizes beam weights by minimizing the deviation of soft constraints subject to hard constraints, with a constraint on the l 1 norm of the beam weight. A singular value decomposition (SVD) based acceleration technique was developed for the LP model. Based on the degeneracy of the influence matrix, the model is first compressed into lower dimension for optimization, and then back-projected to reconstruct the beam weight. After beam weight optimization, the number of beams is reduced by removing the beams with low weight, and optimizing the weights of the remaining beams using the same model. This beam reduction technique is further validated by a mixed integer programming (MIP) model. The SVDLP approach was tested on a lung case. The results demonstrate that the SVD acceleration technique speeds up the optimization by a factor of 4.8. Furthermore, the beam reduction achieves a similar plan quality to the globally optimal plan obtained by the MIP model, but is one to two orders of magnitude faster. Furthermore, the SVDLP
Optimal Design of Composite Structures Under Manufacturing Constraints
DEFF Research Database (Denmark)
Marmaras, Konstantinos
determination of the appropriate laminate thickness and the material choice in the structure. The optimal design problems that arise are stated as nonconvex mixed integer programming problems. We resort to different reformulation techniques to state the optimization problems as either linear or nonlinear convex....... The continuous relaxation of the mixed integer programming problems is being solved by an implementation of a primal–dual interior point method for nonlinear programming that updates the barrier parameter adaptively. The method is chosen for its excellent convergence properties and the ability of the method...... design phase results in structures with better structural performance reducing the need of manually post–processing the found designs....
Rehmer, Donald E.
Analysis of results from a mathematical programming model were examined to 1) determine the least cost options for infrastructure development of geologic storage of CO2 in the Illinois Basin, and 2) perform an analysis of a number of CO2 emission tax and oil price scenarios in order to implement development of the least-cost pipeline networks for distribution of CO2. The model, using mixed integer programming, tested the hypothesis of whether viable EOR sequestration sites can serve as nodal points or hubs to expand the CO2 delivery infrastructure to more distal locations from the emissions sources. This is in contrast to previous model results based on a point-to- point model having direct pipeline segments from each CO2 capture site to each storage sink. There is literature on the spoke and hub problem that relates to airline scheduling as well as maritime shipping. A large-scale ship assignment problem that utilized integer linear programming was run on Excel Solver and described by Mourao et al., (2001). Other literature indicates that aircraft assignment in spoke and hub routes can also be achieved using integer linear programming (Daskin and Panayotopoulos, 1989; Hane et al., 1995). The distribution concept is basically the reverse of the "tree and branch" type (Rothfarb et al., 1970) gathering systems for oil and natural gas that industry has been developing for decades. Model results indicate that the inclusion of hubs as variables in the model yields lower transportation costs for geologic carbon dioxide storage over previous models of point-to-point infrastructure geometries. Tabular results and GIS maps of the selected scenarios illustrate that EOR sites can serve as nodal points or hubs for distribution of CO2 to distal oil field locations as well as deeper saline reservoirs. Revenue amounts and capture percentages both show an improvement over solutions when the hubs are not allowed to come into the solution. Other results indicate that geologic
International Nuclear Information System (INIS)
Azadeh, A.; Asadzadeh, S.M.; Saberi, M.; Nadimi, V.; Tajvidi, A.; Sheikalishahi, M.
2011-01-01
Highlights: → This paper presents a unique approach for long-term natural gas consumption estimation. → It is applied to selected Arab countries to show its superiority and applicability. → It may be used for other real cases for optimum gas consumption estimation. → It is compared with current studies to show its advantages. → It is capable of dealing with complexity, ambiguity, fuzziness, and randomness. -- Abstract: This paper presents an adaptive network-based fuzzy inference system-stochastic frontier analysis (ANFIS-SFA) approach for long-term natural gas (NG) consumption prediction and analysis of the behavior of NG consumption. The proposed models consist of input variables of Gross Domestic Product (GDP) and population (POP). Six distinct models based on different inputs are defined. All of trained ANFIS are then compared with respect to mean absolute percentage error (MAPE). To meet the best performance of the intelligent based approaches, data are pre-processed (scaled) and finally the outputs are post-processed (returned to its original scale). To show the applicability and superiority of the integrated ANFIS-SFA approach, gas consumption in four Middle Eastern countries i.e. Bahrain, Saudi Arabia, Syria, and United Arab Emirates is forecasted and analyzed based on the data of the time period 1980-2007. With the aid of autoregressive model, GDP and population are projected for the period 2008-2015. These projected data are used as the input of ANFIS model to predict the gas consumption in the selected countries for 2008-2015. SFA is then used to examine the behavior of gas consumption in the past and also to make insights for the forthcoming years. The ANFIS-SFA approach is capable of dealing with complexity, uncertainty, and randomness as well as several other unique features discussed in this paper.
A note on a model for quay crane scheduling with non-crossing constraints
DEFF Research Database (Denmark)
Santini, Alberto; Friberg, Henrik Alsing; Røpke, Stefan
2015-01-01
This article studies the quay crane scheduling problem with non-crossing constraints, which is an operational problem that arises in container terminals. An enhancement to a mixed integer programming model for the problem is proposed and a new class of valid inequalities is introduced. Computatio......This article studies the quay crane scheduling problem with non-crossing constraints, which is an operational problem that arises in container terminals. An enhancement to a mixed integer programming model for the problem is proposed and a new class of valid inequalities is introduced...
A hybrid adaptive large neighborhood search heuristic for lot-sizing with setup times
DEFF Research Database (Denmark)
Muller, Laurent Flindt; Spoorendonk, Simon; Pisinger, David
2012-01-01
This paper presents a hybrid of a general heuristic framework and a general purpose mixed-integer programming (MIP) solver. The framework is based on local search and an adaptive procedure which chooses between a set of large neighborhoods to be searched. A mixed integer programming solver and its......, and the upper bounds found by the commercial MIP solver ILOG CPLEX using state-of-the-art MIP formulations. Furthermore, we improve the best known solutions on 60 out of 100 and improve the lower bound on all 100 instances from the literature...
Flow Formulation-based Model for the Curriculum-based Course Timetabling Problem
DEFF Research Database (Denmark)
Bagger, Niels-Christian Fink; Kristiansen, Simon; Sørensen, Matias
2015-01-01
problem. This decreases the number of integer variables signicantly and improves the performance compared to the basic formulation. It also shows competitiveness with other approaches based on mixed integer programming from the literature and improves the currently best known lower bound on one data...... instance in the benchmark data set from the second international timetabling competition.......In this work we will present a new mixed integer programming formulation for the curriculum-based course timetabling problem. We show that the model contains an underlying network model by dividing the problem into two models and then connecting the two models back into one model using a maximum ow...
Simultaneous Fleet Deployment and Network Design of Liner Shipping
DEFF Research Database (Denmark)
Gelareh, Shahin; Pisinger, David
A mixed integer linear programming formulation is proposed for the simultaneous design of network and fleet deployment of a liner service providers for deep-sea shipping. The underlying network design problem is based on a 4-index (5-index by considering capacity type) formulation of the hub...... location problem which are known for their tightness. The demand is considered to be elastic in the sense that the service provider can accept any fraction of the origin-destination demand. We then propose a primal decomposition method to solve instances of the problem to optimality. Numerical results...... confirm superiority of our approach in comparison with a general-purpose mixed integer programming solver....
Network-constrained AC unit commitment under uncertainty: A Benders' decomposition approach
DEFF Research Database (Denmark)
Nasri, Amin; Kazempour, Seyyedjalal; Conejo, Antonio J.
2015-01-01
. The proposed model is formulated as a two-stage stochastic programming problem, whose first-stage refers to the day-ahead market, and whose second-stage represents real-time operation. The proposed Benders’ approach allows decomposing the original problem, which is mixed-integer nonlinear and generally...... intractable, into a mixed-integer linear master problem and a set of nonlinear, but continuous subproblems, one per scenario. In addition, to temporally decompose the proposed ac unit commitment problem, a heuristic technique is used to relax the inter-temporal ramping constraints of the generating units...
Optimal Facility Location Tool for Logistics Battle Command (LBC)
2015-08-01
64 Appendix B. VBA Code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72 Appendix C. Story...should city planners have located emergency service facilities so that all households (the demand) had equal access to coverage?” The critical...programming language called Visual Basic for Applications ( VBA ). CPLEX is a commercial solver for linear, integer, and mixed integer linear programming problems
JPLEX: Java Simplex Implementation with Branch-and-Bound Search for Automated Test Assembly
Park, Ryoungsun; Kim, Jiseon; Dodd, Barbara G.; Chung, Hyewon
2011-01-01
JPLEX, short for Java simPLEX, is an automated test assembly (ATA) program. It is a mixed integer linear programming (MILP) solver written in Java. It reads in a configuration file, solves the minimization problem, and produces an output file for postprocessing. It implements the simplex algorithm to create a fully relaxed solution and…
Influence of TCSC on social welfare and spot price - A comparative ...
African Journals Online (AJOL)
user
Transmission System (FACTS) device such as Thyristor Controlled Series ... Linear Programming was used to find optimum number, locations and setting of ... A mixed integer nonlinear programming was used to locate UPFC to ... This paper has been organized as follows: Section 2 describes static modeling of TCSC.
Radar Resource Management in a Dense Target Environment
2014-03-01
linear programming MFR multifunction phased array radar MILP mixed integer linear programming NATO North Atlantic Treaty Organization PDF probability...1: INTRODUCTION Multifunction phased array radars ( MFRs ) are capable of performing various tasks in rapid succession. The performance of target search...detect, and track operations concurrently with missile guidance functions allow MFRs to deliver superior battle space awareness and air defense
A strategic assessment of biofuels development in the Western States
Kenneth E. Skog; Robert Rummer; Bryan Jenkins; Nathan Parker; Peter Tittman; Quinn Hart; Richard Nelson; Ed Gray; Anneliese Schmidt; Marcia Patton-Mallory; Gordon Gayle
2009-01-01
The Western Governors' Association assessment of biofuels potential in western states estimated the location and capacity of biofuels plants that could potentially be built for selected gasoline prices in 2015 using a mixed integer programming model. The model included information on forest biomass supply curves by county (developed using Forest Service FIA data...
Diseño de una red de distribución a través de un modelo de optimización considerando agotados
Gamez Alban, H.M.; Mejia Argueta, C.; León Espinosa de los Monteros, R.A.
2017-01-01
A multiperiod mixed integer programming is presented to minimize the total costs of the logistics network of a firm that sells veterinary products in Colombia. The products are imported through two ports and they are distributed from four distribution centers to the final customers in the country.
Design of planar articulated mechanisms using branch and bound
DEFF Research Database (Denmark)
Stolpe, Mathias; Kawamoto, Atsushi
2005-01-01
This paper considers an optimization model and a solution method for the design of two-dimensional mechanical mechanisms. The mechanism design problem is modeled as a nonconvex mixed integer program which allows the optimal topology and geometry of the mechanism to be determined simultaneously...
Generating Ship-to-Shore Bulk Fuel Delivery Schedules for the Marine Expeditionary Unit
2017-06-01
Requirements and Products . . . . . . . . . . . . . . . . 18 3 Mathematical Formulation 21 3.1 Quickest Flow Formulation...56 vii Appendix A Mixed Integer Linear Program 59 Appendix B Assignment Heuristic Pseudocode 65 List of...combination of competing requirements, insufficient fuel transport containers, and time-constrained planning factors create a sizable problem for planners
Santos, S.F.; Paterakis, N.G.; Catalao, J.P.S.; Camarinha-Matos, L.M.; Baldissera, T.A.; Di Orio, G.; Marques, F.
2015-01-01
The distribution systems (DS) reconfiguration problem is formulated in this paper as a multi-objective mixed-integer linear programming (MILP) multiperiod problem, enforcing that the obtained topology is radial in order to exploit several advantages those configurations offer. The effects of
Constructing Periodic Timetables using MIP - a case study from DSB S-train
DEFF Research Database (Denmark)
Nielsen, Morten N.; Hove, Bjørn; Clausen, Jens
2006-01-01
We describe a mathematical model to create operational timetable alternatives in DSB S-tog a/s. The model is a mixed integer program implemented in GAMS and solved by CPLEX. We investigate the impact of automatic merges of lines and perform scenario analysis for a subset of the parameters...
Learning curves in energy planning models
Energy Technology Data Exchange (ETDEWEB)
Barreto, L; Kypreos, S [Paul Scherrer Inst. (PSI), Villigen (Switzerland)
1999-08-01
This study describes the endogenous representation of investment cost learning curves into the MARKAL energy planning model. A piece-wise representation of the learning curves is implemented using Mixed Integer Programming. The approach is briefly described and some results are presented. (author) 3 figs., 5 refs.
Optimum use of air tankers in initial attack: selection, basing, and transfer rules
Francis E. Greulich; William G. O' Regan
1982-01-01
Fire managers face two interrelated problems in deciding the most efficient use of air tankers: where best to base them, and how best to reallocate them each day in anticipation of fire occurrence. A computerized model based on a mixed integer linear program can help in assigning air tankers throughout the fire season. The model was tested using information from...
Stochastic Pseudo-Boolean Optimization
2011-07-31
16 polyominoes. Given this notation, we provide the following nonlinear mixed integer programming (MIP) formulation of the exact tiling problem: PNL ...ri, cj ≥ 0 ∀ i, j, p, q, k. 8.3.3 Linear Set Partitioning Formulation We use value disjunctions to reformulate PNL as a linear MIP that can be
An MILP approach to shelf life integrated planning and scheduling in scalded sausage production
DEFF Research Database (Denmark)
Günther, H.O.; van Beek, P.; Grunow, Martin
2006-01-01
in which shelf life aspects are integrated into operational production planning and scheduling functions. Specifically we make use of so-called Mixed Integer Linear Programming (MILP) models. Our research is based on an industrial case study of yogurt production. Relying on the principle of block planning...
Optimal operation of smart houses by a real-time rolling horizon algorithm
Paterakis, N.G.; Pappi, I.N.; Catalão, J.P.S.; Erdinc, O.
2016-01-01
In this paper, a novel real-time rolling horizon optimization framework for the optimal operation of a smart household is presented. A home energy management system (HEMS) model based on mixed-integer linear programming (MILP) is developed in order to minimize the energy procurement cost considering
Power-Aware Rationale for Using Coarse-Grained Transponders in IP-Over-WDM Networks
DEFF Research Database (Denmark)
Saldaña Cercos, Silvia; Resendo, Leandro C.; Ribeiro, Moises R. N.
2015-01-01
.e., using 10 Gbps technology)? (2) What is the long-term cost of coarse-grained designs? We define a power-aware mixed integer linear programming (MILP) formulation based on actual modular architectures where modules are upgraded as the network traffic increases. We introduce, for the first time, important...
Marco A. Contreras; Woodam Chung; Greg Jones
2008-01-01
Forest transportation planning problems (FTPP) have evolved from considering only the financial aspects of timber management to more holistic problems that also consider the environmental impacts of roads. These additional requirements have introduced side constraints, making FTPP larger and more complex. Mixed-integer programming (MIP) has been used to solve FTPP, but...
Impact of Fluctuating Energy Prices on the Operation Strategy of a Trigeneration System
Directory of Open Access Journals (Sweden)
Dražen Balić
2015-09-01
The optimization method is based on two criteria – energy and economic criterion, which were applied hierarchically. Therefore, two optimal operation strategies are introduced. A mixed integer non-linear programming model provides energy and cost savings up to 32% and 28% respectively in comparison with conventional system. In addition, optimal capacity of trigeneration system is explored.
Realizing block planning concepts in make-and-pack production using MILP modelling and SAP APO
DEFF Research Database (Denmark)
Günther, H.O.; Grunow, M.; Neuhaus, U.
2006-01-01
of a major producer of hair dyes as a case study. We present two different implementations of the block planning concept. One utilizes the Production Planning/Detailed Scheduling module of the SAP APO© software. The other approach is based on a mixed-integer linear programming formulation. In contrast...
An Aggregated Optimization Model for Multi-Head SMD Placements
Ashayeri, J.; Ma, N.; Sotirov, R.
2010-01-01
In this article we propose an aggregate optimization approach by formulating the multi-head SMD placement optimization problem into a mixed integer program (MIP) with the variables based on batches of components. This MIP is tractable and effective in balancing workload among placement heads,
An aggregated optimization model for multi-head SMD placements
Ashayeri, J.; Ma, N.; Sotirov, R.
2011-01-01
In this article we propose an aggregate optimization approach by formulating the multi-head SMD placement optimization problem into a mixed integer program (MIP) with the variables based on batches of components. This MIP is tractable and effective in balancing workload among placement heads,
Automated Test-Form Generation
van der Linden, Wim J.; Diao, Qi
2011-01-01
In automated test assembly (ATA), the methodology of mixed-integer programming is used to select test items from an item bank to meet the specifications for a desired test form and optimize its measurement accuracy. The same methodology can be used to automate the formatting of the set of selected items into the actual test form. Three different…
Integrating Test-Form Formatting into Automated Test Assembly
Diao, Qi; van der Linden, Wim J.
2013-01-01
Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using…
Value assessment of hydrogen-based electrical energy storage in view of electricity spot market
DEFF Research Database (Denmark)
You, Shi; Hu, Junjie; Zong, Yi
2016-01-01
electricity spot market that has high price volatility due to its high share of wind power. An economic dispatch model is developed as a mixed-integer programming (MIP) problem to support the estimation of variable cost of such a system taking into account a good granularity of the technical details. Based...
Time-Varying FOPDT Modeling and On-line Parameter Identification
DEFF Research Database (Denmark)
Yang, Zhenyu; Sun, Zhen
2013-01-01
on the Mixed-Integer-Nonlinear Programming, Least-Mean-Square and sliding window techniques. The proposed approaches can simultaneously estimate the time-dependent system parameters, as well as the unknown disturbance input if it is the case, in an on-line manner. The proposed concepts and algorithms...
A hybrid multi-objective evolutionary algorithm approach for ...
Indian Academy of Sciences (India)
This paper addresses a fuzzy mixed-integer non-linear programming (FMINLP) model by considering machine-dependent and job-sequence-dependent set-up times that minimize the total completion time,the number of tardy jobs, the total flow time and the machine load variation in the context of unrelated parallel machine ...
An adaptive large neighborhood search heuristic for the Electric Vehicle Scheduling Problem
DEFF Research Database (Denmark)
Wen, M.; Linde, Esben; Røpke, Stefan
2016-01-01
to minimizing the total deadheading distance. A mixed integer programming formulation as well as an Adaptive Large Neighborhood Search (ALNS) heuristic for the E-VSP are presented. ALNS is tested on newly generated E-VSP benchmark instances. Result shows that the proposed heuristic can provide good solutions...
The Vehicle Routing Problem with Time Windows and Temporal Dependencies
DEFF Research Database (Denmark)
Rasmussen, Matias Sevel; Dohn, Anders Høeg; Larsen, Jesper
to be scheduled with a certain slack between them. They refer to the vehicle problem as having interdependent time windows. Temporal dependencies have been modeled for a home care routing problem in a mixed integer programming model (MIP) which was solved with a standard MIP solver. An application with general...
A Branch-and-Price approach to find optimal decision trees
Firat, M.; Crognier, Guillaume; Gabor, Adriana; Zhang, Y.
2018-01-01
In Artificial Intelligence (AI) field, decision trees have gained certain importance due to their effectiveness in solving classification and regression problems. Recently, in the literature we see finding optimal decision trees are formulated as Mixed Integer Linear Programming (MILP) models. This
Cluster Formation and Joint Power-Bandwidth Allocation for Imperfect NOMA in DL-HetNets
Celik, Abdulkadir; Al-Qahtani, Fawaz; Radaydeh, Redha; Alouini, Mohamed-Slim
2017-01-01
and estimation errors. Then, a generic cluster formation (CF) and Power-Bandwidth Allocation (PBA) is formulated as a mixed-integer non-linear programming (MINLP) problem for downlink (DL) heterogeneous networks (HetNets). After dividing the MINLP problem
Liner shipping hub network design in a competitive environment
DEFF Research Database (Denmark)
Gelareh, Shahin; Nickel, Stefan; Pisinger, David
2010-01-01
A mixed integer programming formulation is proposed for hub-and-spoke network design in a competitive environment. It addresses the competition between a newcomer liner service provider and an existing dominating operator, both operating on hub-and-spoke networks. The newcomer company maximizes i...
Celik, Abdulkadir; Radaydeh, Redha Mahmoud Mesleh; Al-Qahtani, Fawaz S.; Alouini, Mohamed-Slim
2017-01-01
known as downlink (DL)/UL decoupling (DUDe). Subject to quality of service (QoS) requirements and power constraints, we formulate a joint SB assignment and resource block (RB) allocation optimization as a mixed integer non-linear programming (MINLP
Species-specific spatial characteristics in reserve site selection
Groeneveld, R.A.
2010-01-01
This paper addresses the problem of selecting reserve sites cost-effectively, taking into account the mobility and habitat area requirements of each species. Many reserve site selection problems are analyzed in mixed-integer linear programming (MILP) models due to the mathematical solvers available
DEFF Research Database (Denmark)
Anvari-Moghaddam, Amjad; Quintero, Juan Carlos Vasquez; Guerrero, Josep M.
2015-01-01
In this paper, an intelligent energy management system based on energy saving and user’s comfort is introduced and applied to a residential smart home as a case study. The proposed multi-objective mixed-integer nonlinear programming (MINLP)-based architecture takes the advantages of several key...
Tarim, S.A.; Ozen, U.; Dogru, M.K.; Rossi, R.
2011-01-01
We provide an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman [8] for solving a stochastic lot-sizing problem with service level constraints under the static–dynamic uncertainty strategy. The effectiveness of the proposed method
Anticipation of lead time performance in supply chain operations planning
Jansen, M.M.; Kok, de A.G.; Fransoo, J.C.
2009-01-01
Whilst being predominantly used in practice, linear and mixed integer programming models for Supply Chain Operations Planning (SCOP) are not well suited for modeling the relationship between the release of work to a production unit and its output over time. In this paper we propose an approach where
Fleet deployment, network design and hub location of liner shipping companies
DEFF Research Database (Denmark)
Gelareh, Shahin; Pisinger, David
2011-01-01
A mixed integer linear programming formulation is proposed for the simultaneous design of network and fleet deployment of a deep-sea liner service provider. The underlying network design problem is based on a 4-index (5-index by considering capacity type) formulation of the hub location problem...
Chitil, Olaf
2009-01-01
Functional programming is a programming paradigm like object-oriented programming and logic programming. Functional programming comprises both a specific programming style and a class of programming languages that encourage and support this programming style. Functional programming enables the programmer to describe an algorithm on a high-level, in terms of the problem domain, without having to deal with machine-related details. A program is constructed from functions that only map inputs to ...
Marlet, Renaud
2013-01-01
This book presents the principles and techniques of program specialization - a general method to make programs faster (and possibly smaller) when some inputs can be known in advance. As an illustration, it describes the architecture of Tempo, an offline program specializer for C that can also specialize code at runtime, and provides figures for concrete applications in various domains. Technical details address issues related to program analysis precision, value reification, incomplete program specialization, strategies to exploit specialized program, incremental specialization, and data speci
Learn how the National Cancer Institute transitioned the former Cooperative Groups Program to the National Clinical Trials Network (NCTN) program. The NCTN gives funds and other support to cancer research organizations to conduct cancer clinical trials.
International Nuclear Information System (INIS)
Rawool-Sullivan, M.W.; Plagnol, E.
1990-01-01
The program AUTO was developed to be used in the analysis of dE vs E type spectra. This program is written in FORTRAN and calculates dE vs E lines in MeV. The provision is also made in the program to convert these lines from MeV to ADC channel numbers to facilitate the comparison with the raw data from the experiments. Currently the output of this program can be plotted with the display program, called VISU, but it can also be used independent of the program VISU, with little or no modification in the actual fortran code. The program AUTO has many useful applications. In this article the program AUTO is described along with its applications
Canonical Duality Theory for Topology Optimization
Gao, David Yang
2016-01-01
This paper presents a canonical duality approach for solving a general topology optimization problem of nonlinear elastic structures. By using finite element method, this most challenging problem can be formulated as a mixed integer nonlinear programming problem (MINLP), i.e. for a given deformation, the first-level optimization is a typical linear constrained 0-1 programming problem, while for a given structure, the second-level optimization is a general nonlinear continuous minimization pro...
Price-Taker Offering Strategy in Electricity Pay-as-Bid Markets
DEFF Research Database (Denmark)
Mazzi, Nicolò; Kazempour, Jalal; Pinson, Pierre
2017-01-01
The recent increase in the deployment of renewable energy sources may affect the offering strategy of conventional producers, mainly in the balancing market. The topics of optimal offering strategy and self-scheduling of thermal units have been extensively addressed in the literature. The feasible...... operating region of such units can be modeled using a mixed-integer linear programming approach, and the trading problem as a linear programming problem. However, the existing models mostly assume a uniform pricing scheme in all market stages, while several European balancing markets (e.g., in Germany...... and Italy) are settled under a pay-as-bid pricing scheme. The existing tools for solving the trading problem in pay-as-bid electricity markets rely on non-linear optimization models, which, combined with the unit commitment constraints, result in a mixed-integer non-linear programming problem. In contrast...
Radziszewska-Zielina, Elżbieta; Śladowski, Grzegorz
2017-10-01
The knowledge of a real estate developer regarding the possibilities of adapting a historical building to a particular form of use and the knowledge of the approximate costs associated with this process are some of the more important pieces of information that can influence the making of the final decision regarding commencing with such a project. The preliminary analysis of the process of adapting a historical building is a difficult task due to the specific character of this type of project. The specific character of such a project is proven by the fact that the often insufficient analysis of the structure and architecture of a building and its historical substance at the stage of carrying out the process of adaptation can generate the necessity to perform previously unforeseen additional actions. An equally important problem is the difficulty in estimating the funds required to conduct research and the analyses associated with developing design documentation, as well as carrying out construction and conservation work. This is why a real estate developer should analyse various scenarios of carrying out a project during the stage of the preliminary analysis of its feasibility, taking into account the fact that some of them can occur in a random manner. The authors of the paper propose the use of one of the planning tools known as stochastic networks, which can be used to model the undetermined structure of these types of projects. Fuzzy logic was used in order to estimate uncertain values of the parameters of a model (the probability of performing work and paying the associated costs). The approach proposed by the authors was used to perform a preliminary analysis of the adaptation of the Arsenal in Gdańsk to a particular form of use along with estimating the costs associated with it. The results that were obtained have confirmed the potential of this method for real-world application.
DEFF Research Database (Denmark)
Vallgårda, Anna; Boer, Laurens; Tsaknaki, Vasiliki
2017-01-01
. Consequently we ask what the practice of programming and giving form to such materials would be like? How would we be able to familiarize ourselves with the dynamics of these materials and their different combinations of cause and effect? Which tools would we need and what would they look like? Will we program......, and color, but additionally being capable of sensing, actuating, and computing. Indeed, computers will not be things in and by themselves, but embedded into the materials that make up our surroundings. This also means that the way we interact with computers and the way we program them, will change...... these computational composites through external computers and then transfer the code them, or will the programming happen closer to the materials? In this feature we outline a new research program that floats between imagined futures and the development of a material programming practice....
DEFF Research Database (Denmark)
Frost, Jacob
To investigate the use of VTLoE as a basis for formal derivation of functional programs with effects. As a part of the process, a number of issues central to effective formal programming are considered. In particular it is considered how to develop a proof system suitable for pratical reasoning......, how to implement this system in the generic proof assistant Isabelle and finally how to apply the logic and the implementation to programming....
DEFF Research Database (Denmark)
Wirz, Lukas; Peter, Schwerdtfeger,; Avery, James Emil
2013-01-01
Fullerene (Version 4.4), is a general purpose open-source program that can generate any fullerene isomer, perform topological and graph theoretical analysis, as well as calculate a number of physical and chemical properties. The program creates symmetric planar drawings of the fullerene graph, an......-Fowler, and Brinkmann-Fowler vertex insertions. The program is written in standard Fortran and C++, and can easily be installed on a Linux or UNIX environment....
Smith, Chris
2009-01-01
Why learn F#? This multi-paradigm language not only offers you an enormous productivity boost through functional programming, it also lets you develop applications using your existing object-oriented and imperative programming skills. With Programming F#, you'll quickly discover the many advantages of Microsoft's new language, which includes access to all the great tools and libraries of the .NET platform. Learn how to reap the benefits of functional programming for your next project -- whether it's quantitative computing, large-scale data exploration, or even a pursuit of your own. With th
International Nuclear Information System (INIS)
Lee, Seong Jae; Wi, Seong Dong; Yoo, Jong Seon; Kim, Se Chan
2001-02-01
This book tells of PLC programming for KGL-WIN with summary of PLC, performance and function of PLC like characteristic of KGL-WIN, connection method with PLC, basic performance of K200S/K300S/K1000S, diagram of input and output H/W, writing project, staring the program, editing of program, on-line function, debugging and instructions like control, timer and counter, data transmission, comparison, rotation and moving, system, data operating data conversion and application program.
Noble, Joshua
2009-01-01
Make cool stuff. If you're a designer or artist without a lot of programming experience, this book will teach you to work with 2D and 3D graphics, sound, physical interaction, and electronic circuitry to create all sorts of interesting and compelling experiences -- online and off. Programming Interactivity explains programming and electrical engineering basics, and introduces three freely available tools created specifically for artists and designers: Processing, a Java-based programming language and environment for building projects on the desktop, Web, or mobile phonesArduino, a system t
Modeling Electric Vehicle Benefits Connected to Smart Grids
International Nuclear Information System (INIS)
Stadler, Michael; Marnay, Chris; Mendes, Goncalo; Kloess, Maximillian; Cardoso, Goncalo; Megel, Olivier; Siddiqui, Afzal
2011-01-01
Connecting electric storage technologies to smartgrids will have substantial implications in building energy systems. Local storage will enable demand response. Mobile storage devices in electric vehicles (EVs) are in direct competition with conventional stationary sources at the building. EVs will change the financial as well as environmental attractiveness of on-site generation (e.g. PV, or fuel cells). In order to examine the impact of EVs on building energy costs and CO2 emissions in 2020, a distributed-energy-resources adoption problem is formulated as a mixed-integer linear program with minimization of annual building energy costs or CO2 emissions. The mixed-integer linear program is applied to a set of 139 different commercial buildings in California and example results as well as the aggregated economic and environmental benefits are reported. The research shows that considering second life of EV batteries might be very beneficial for commercial buildings.
Energy Technology Data Exchange (ETDEWEB)
Catalao, J.P.S.; Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)
2010-10-15
This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning head-dependent reservoirs under competitive environment. We propose a novel method, based on mixed-integer nonlinear programming (MINLP), for optimising power generation efficiency. This method considers hydroelectric power generation as a nonlinear function of water discharge and of the head. The main contribution of this paper is that discharge ramping constraints and start/stop of units are also considered, in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve two case studies based on Portuguese cascaded hydro systems, providing a higher profit at an acceptable computation time in comparison with classical optimisation methods based on mixed-integer linear programming (MILP). (author)
Research on three-phase unbalanced distribution network reconfiguration strategy
Hu, Shuang; Li, Ke-Jun; Xu, Yanshun; Liu, Zhijie; Guo, Jing; Wang, Zhuodi
2017-01-01
With the development of social economy, the loads installed in the distribution network become more and more complex which may cause the three-phase unbalance problems. This paper proposes an optimal reconfiguration approach based on mixed integer quadric programming (MIQP) method to address the three-phase unbalance problem. It aims to minimize the total network losses of the system. By using several square constraints to substitute the circular constraint, the original optimization problem is linearized and converted into a mixed-integer linear programming (MILP) model. Then this MILP problem is solved in general algebraic model system (GAMS) software using CPLEX solver. The additional losses caused by three-phase unbalanced are also considered. An IEEE 34 nodes test system is used to demonstrate the feasibility and effectiveness of the proposed method. The results show that the losses and the voltage violation mitigation in the network can be reduced significantly.
Benefit Analysis of Emergency Standby System Promoted to Cogeneration System
Directory of Open Access Journals (Sweden)
Shyi-Wen Wang
2016-07-01
Full Text Available Benefit analysis of emergency standby system combined with absorption chiller promoted to cogeneration system is introduced. Economic evaluations of such upgraded projects play a major part in the decisions made by investors. Time-of-use rate structure, fuel cost and system constraints are taken into account in the evaluation. Therefore, the problem is formulated as a mixed-integer programming problem. Using two-stage methodology and modified mixed-integer programming technique, a novel algorithm is developed and introduced here to solve the nonlinear optimization problem. The net present value (NPV method is used to evaluate the annual benefits and years of payback for the cogeneration system. The results indicate that upgrading standby generators to cogeneration systems is profitable and should be encouraged, especially for those utilities with insufficient spinning reserves, and moreover, for those having difficulty constructing new power plants.
Zarindast, Atousa; Seyed Hosseini, Seyed Mohamad; Pishvaee, Mir Saman
2017-06-01
Robust supplier selection problem, in a scenario-based approach has been proposed, when the demand and exchange rates are subject to uncertainties. First, a deterministic multi-objective mixed integer linear programming is developed; then, the robust counterpart of the proposed mixed integer linear programming is presented using the recent extension in robust optimization theory. We discuss decision variables, respectively, by a two-stage stochastic planning model, a robust stochastic optimization planning model which integrates worst case scenario in modeling approach and finally by equivalent deterministic planning model. The experimental study is carried out to compare the performances of the three models. Robust model resulted in remarkable cost saving and it illustrated that to cope with such uncertainties, we should consider them in advance in our planning. In our case study different supplier were selected due to this uncertainties and since supplier selection is a strategic decision, it is crucial to consider these uncertainties in planning approach.
Modeling Electric Vehicle Benefits Connected to Smart Grids
Energy Technology Data Exchange (ETDEWEB)
Stadler, Michael; Marnay, Chris; Mendes, Goncalo; Kloess, Maximillian; Cardoso, Goncalo; M& #233; gel, Olivier; Siddiqui, Afzal
2011-07-01
Connecting electric storage technologies to smartgrids will have substantial implications in building energy systems. Local storage will enable demand response. Mobile storage devices in electric vehicles (EVs) are in direct competition with conventional stationary sources at the building. EVs will change the financial as well as environmental attractiveness of on-site generation (e.g. PV, or fuel cells). In order to examine the impact of EVs on building energy costs and CO2 emissions in 2020, a distributed-energy-resources adoption problem is formulated as a mixed-integer linear program with minimization of annual building energy costs or CO2 emissions. The mixed-integer linear program is applied to a set of 139 different commercial buildings in California and example results as well as the aggregated economic and environmental benefits are reported. The research shows that considering second life of EV batteries might be very beneficial for commercial buildings.
Robust environmental closed-loop supply chain design under uncertainty
International Nuclear Information System (INIS)
MA, Ruimin; YAO, Lifei; JIN, Maozhu; REN, Peiyu; LV, Zhihan
2016-01-01
With the fast developments in product remanufacturing to improve economic and environmental performance, an environmental closed-loop supply (ECLSC) chain is important for enterprises' competitiveness. In this paper, a robust ECLSC network is investigated which includes multiple plants, collection centers, demand zones, and products, and consists of both forward and reverse supply chains. First, a robust multi-objective mixed integer nonlinear programming model is proposed to deal with ECLSC considering two conflicting objectives simultaneously, as well as the uncertain nature of the supply chain. Cost parameters of the supply chain and demand fluctuations are subject to uncertainty. The first objective function aims to minimize the economical cost and the second objective function is to minimize the environmental influence. Then, the proposed model is solved as a single-objective mixed integer programming model applying the LP-metrics method. Finally, numerical example has been presented to test the model. The results indicate that the proposed model is applicable in practice.
MILP Approach for Bilevel Transmission and Reactive Power Planning Considering Wind Curtailment
DEFF Research Database (Denmark)
Ugranli, Faruk; Karatepe, Engin; Nielsen, Arne Hejde
2017-01-01
In this study, two important planning problems in power systems that are transmission expansion and reactive power are formulated as a mixed-integer linear programming taking into account the bilevel structure due to the consideration of market clearing under several load-wind scenarios....... The objective of the proposed method is to minimize the installation cost of transmission lines, reactive power sources, and the annual operation costs of conventional generators corresponding to the curtailed wind energy while maintaining the reliable system operation. Lower level problems of the bilevel...... structure are designated for the market clearing which is formulated by using the linearized optimal power flow equations. In order to obtain mixed-integer linear programming formulation, the so-called lower level problems are represented by using primal-dual formulation. By using the proposed method, power...
Anderson, Tiffoni
This module provides information on development and use of a Material Safety Data Sheet (MSDS) software program that seeks to link literacy skills education, safety training, and human-centered design. Section 1 discusses the development of the software program that helps workers understand the MSDSs that accompany the chemicals with which they…
Jennings, Carol Ann
Designed for use by both secondary- and postsecondary-level business teachers, this curriculum guide consists of 10 units of instructional materials dealing with Beginners All-Purpose Symbol Instruction Code (BASIC) programing. Topics of the individual lessons are numbering BASIC programs and using the PRINT, END, and REM statements; system…
DEFF Research Database (Denmark)
Montesi, Fabrizio
, as they offer a concise view of the message flows enacted by a system. For this reason, in the last decade choreographies have been used in the development of programming languages, giving rise to a programming paradigm that in this dissertation we refer to as Choreographic Programming. Recent studies show...... endpoint described in a choreography can then be automatically generated, ensuring that such implementations are safe by construction. However, current formal models for choreographies do not deal with critical aspects of distributed programming, such as asynchrony, mobility, modularity, and multiparty...... sessions; it remains thus unclear whether choreographies can still guarantee safety when dealing with such nontrivial features. This PhD dissertation argues for the suitability of choreographic programming as a paradigm for the development of safe distributed systems. We proceed by investigating its...
Directory of Open Access Journals (Sweden)
Farzad Amirkhani
2017-03-01
The proposed method is implemented on classical job-shop problems with objective of makespan and results are compared with mixed integer programming model. Moreover, the appropriate dispatching priorities are achieved for dynamic job-shop problem minimizing a multi-objective criteria. The results show that simulation-based optimization are highly capable to capture the main characteristics of the shop and produce optimal/near-optimal solutions with highly credibility degree.
Single Machine Multi-product Capacitated Lotsizing with Sequence-dependent Setups
Almada-Lobo , Bernardo; Klabjan , Diego; Carravilla , Maria Antónia; Oliveira , Jose Fernando
2007-01-01
Abstract In production planning in the glass container industry, machine dependent setup times and costs are incurred for switchovers from one product to another. The resulting multi-item capacitated lot sizing problem has sequence-dependent setup times and costs. We present two novel linear mixed integer programming formulations for this problem, incorporating all the necessary features of setup carryovers. The compact formulation has polynomially many constraints, while, on the o...
2015-03-01
vulnerable people will have access to this airdropped consumable aid (since nobody 1 is necessarily coordinating the distribution on the ground... VBA ) platforms (see Appendix B). In particular, we used GAMS v.23.9.3 with IBM ILOG CPLEX 12.4.0.1 to solve the stochastic, mixed-integer weighted...goal programming model, and we used Excel/ VBA to create an auto- matic, user-friendly interface with the decision maker for model input and analysis of
Implementing and Bounding a Cascade Heuristic for Large-Scale Optimization
2017-06-01
aggregated Segment Length PM Production Model PMI Planned Maintenance Interval RMIP Relaxed Mixed Integer Program RSRP Rolling Stock Rescheduling...that can exist up to time t for facility f. ,p tB is the maximum amount of storage possible based on the total product limits. ,Ŕ"pB is the total ...simultaneously meeting aircraft maintenance requirements. Production delays of the F-35 Lightning II Joint Strike Fighter, the replacement aircraft for the F/A-18
Optimizing Ship Speed to Minimize Total Fuel Consumption with Multiple Time Windows
Directory of Open Access Journals (Sweden)
Jae-Gon Kim
2016-01-01
Full Text Available We study the ship speed optimization problem with the objective of minimizing the total fuel consumption. We consider multiple time windows for each port call as constraints and formulate the problem as a nonlinear mixed integer program. We derive intrinsic properties of the problem and develop an exact algorithm based on the properties. Computational experiments show that the suggested algorithm is very efficient in finding an optimal solution.
Selecting Large Portfolios of Social Projects in Public Organizations
Directory of Open Access Journals (Sweden)
Igor Litvinchev
2014-01-01
Full Text Available We address the portfolio selection of social projects in public organizations considering interdependencies (synergies affecting project funds requirements and tasks. A mixed integer linear programming model is proposed incorporating the most relevant aspects of the problem found in the literature. The model supports both complete (all or nothing and partial (a certain amount from a given interval of funding resource allocation policies. Numerical results for large-scale problem instances are presented.
Optimal Turbine Allocation for Offshore and Onshore Wind Farms
DEFF Research Database (Denmark)
Fischetti, Martina; Fischetti, Matteo; Monaci, Michele
2016-01-01
. In particular, lots of money and energy are spent on the optimal design of wind farms, as an efficient use of the available resources is instrumental for their economical success. In the present paper we address the optimization of turbine positions, which is one of the most relevant problems in the design...... of a wind farm, and propose a heuristic approach based on Mixed-Integer Linear Programming techniques. Computational results on very large scale instances prove the practical viability of the approach....
A solution approach to the ROADEF/EURO 2010 challenge based on Benders' Decomposition
DEFF Research Database (Denmark)
Lusby, Richard Martin; Muller, Laurent Flindt; Petersen, Bjørn
them satisfy the constraints not part of the mixed integer program. A number of experiments are performed on the available benchmark instances. These experiments show that the approach is competitive on the smaller instances, but not for the larger ones. We believe the exact approach gives insight...... into the problem and additionally makes it possible to find lower bounds on the problem, which is typically not the case for the competing heuristics....
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks
Harirchi, Farshad; Khalil, Omar A.; Liu, Sijia; Elvati, Paolo; Violi, Angela; Hero, Alfred O.
2017-01-01
In this paper, we propose an optimization-based sparse learning approach to identify the set of most influential reactions in a chemical reaction network. This reduced set of reactions is then employed to construct a reduced chemical reaction mechanism, which is relevant to chemical interaction network modeling. The problem of identifying influential reactions is first formulated as a mixed-integer quadratic program, and then a relaxation method is leveraged to reduce the computational comple...
Rao, Weizhen; Liu, Feng; Wang, Shengbin
2016-01-01
The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is ...
Daniela S. Arango González; Elias Olivares-Benitez; Pablo A. Miranda
2017-01-01
This paper presents a biobjective problem for a solid waste collection system in a set of islands in southern Chile. The first objective minimizes transportation cost and the second one reduces the environmental impact caused by the accumulation of solid waste at the collection points. To solve this problem, biobjective mixed integer linear programming is used. In the model, an itinerary scheme is considered for the visit to the islands. The model decides which collection points are visited p...
A reactive decision-making approach to reduce instability in a Master Production Schedule
Herrera , Carlos; Belmokhtar Berraf , Sana; Thomas , André; Parada , Victor
2016-01-01
International audience; One of the primary factors that impact the master production scheduling performance is demand fluctuation, which leads to frequently updated decisions, thereby causing instability. Consequently, global cost deteriorates, and productivity decreases. A reactive approach based on parametric mixed-integer programming is proposed that aims to provide a set of plans such that a compromise between production cost and production stability is ensured. Several stability measures...
Rich Ground State Chemical Ordering in Nanoparticles: Exact Solution of a Model for Ag-Au Clusters
DEFF Research Database (Denmark)
Larsen, Peter Mahler; Jacobsen, Karsten Wedel; Schiøtz, Jakob
2018-01-01
We show that nanoparticles can have very rich ground state chemical order. This is illustrated by determining the chemical ordering of Ag-Au 309-atom Mackay icosahedral nanoparticles. The energy of the nanoparticles is described using a cluster expansion model, and a Mixed Integer Programming (MIP......) approach is used to find the exact ground state configurations for all stoichiometries. The chemical ordering varies widely between the different stoichiometries, and display a rich zoo of structures with non-trivial ordering....
Linearization of Euclidean Norm Dependent Inequalities Applied to Multibeam Satellites Design
Camino , Jean-Thomas; Artigues , Christian; Houssin , Laurent; Mourgues , Stéphane
2016-01-01
Euclidean norm computations over continuous variables appear naturally in the constraints or in the objective of many problems in the optimization literature, possibly defining non-convex feasible regions or cost functions. When some other variables have discrete domains, it positions the problem in the challenging Mixed Integer Nonlinear Programming (MINLP) class. For any MINLP where the nonlinearity is only present in the form of inequality constraints involving the Euclidean norm, we propo...
IMI Workshop on Optimization in the Real World
Shinano, Yuji; Waki, Hayato
2016-01-01
This book clearly shows the importance, usefulness, and powerfulness of current optimization technologies, in particular, mixed-integer programming and its remarkable applications. It is intended to be the definitive study of state-of-the-art optimization technologies for students, academic researchers, and non-professionals in industry. The chapters of this book are based on a collection of selected and extended papers from the “IMI Workshop on Optimization in the Real World” held in October 2014 in Japan.
Capacity Planning for Batch and Perfusion Bioprocesses Across Multiple Biopharmaceutical Facilities
Siganporia, Cyrus C; Ghosh, Soumitra; Daszkowski, Thomas; Papageorgiou, Lazaros G; Farid, Suzanne S
2014-01-01
Production planning for biopharmaceutical portfolios becomes more complex when products switch between fed-batch and continuous perfusion culture processes. This article describes the development of a discrete-time mixed integer linear programming (MILP) model to optimize capacity plans for multiple biopharmaceutical products, with either batch or perfusion bioprocesses, across multiple facilities to meet quarterly demands. The model comprised specific features to account for products with fe...
A cost and operational effectiveness analysis of alternative anti-surface warfare platforms
Skinner, Walter Mark.
1993-01-01
Approved for public release; distribution is unlimited. A Cost and Operational Effectiveness Analysis (COEA) is performed for three alternative anti-surface warfare (ASUW) platforms that will conduct operations in multi-service regional scenarios. Estimated program costs, historical cost variances, and measures of operational effectiveness are determined for each COEA alternative, and service life extension effects are examined. The data is merged in a mixed-integer optimization model, MPA...
Optimal Reinsertion of Cancelled Train Lines
DEFF Research Database (Denmark)
Groth, Julie Jespersen; Clausen, Jens
2006-01-01
One recovery strategy in case of a major disruption in rail network is to cancel all trains on a specific line of the network. When the disturbance has ended, the cancelled line must be reinserted as soon as possible. In this article we present a mixed integer programming (MIP) model for calculat....... The model finds the optimal solution in an average of 0.5 CPU seconds in each test case....
Scheduling Additional Train Unit Services on Rail Transit Lines
Zhibin Jiang; Yuyan Tan; Özgür Yalçınkaya
2014-01-01
This paper deals with the problem of scheduling additional train unit (TU) services in a double parallel rail transit line, and a mixed integer programming (MIP) model is formulated for integration strategies of new trains connected by TUs with the objective of obtaining higher frequencies in some special sections and special time periods due to mass passenger volumes. We took timetable scheduling and TUs scheduling as an integrated optimization model with two objectives: minimizing travel ti...
Simultaneously Exploiting Two Formulations: an Exact Benders Decomposition Approach
DEFF Research Database (Denmark)
Lusby, Richard Martin; Gamst, Mette; Spoorendonk, Simon
When modelling a given problem using linear programming techniques several possibilities often exist, and each results in a different mathematical formulation of the problem. Usually, advantages and disadvantages can be identified in any single formulation. In this paper we consider mixed integer...... to the standard branch-and-price approach from the literature, the method shows promising performance and appears to be an attractive alternative....
Weighted thinned linear array design with the iterative FFT technique
CSIR Research Space (South Africa)
Du Plessis, WP
2011-09-01
Full Text Available techniques utilise simulated annealing [3]?[5], [10], mixed integer linear programming [7], genetic algorithms [9], and a hyrid approach combining a genetic algorithm and a local optimiser [8]. The iterative Fourier technique (IFT) developed by Keizer [2... algorithm being well- suited to obtaining low CTRs. Test problems from the literature are considered, and the results obtained with the IFT considerably exceed those achieved with other algorithms. II. DESCRIPTION OF THE ALGORITHM A flowchart describing...
Energy Technology Data Exchange (ETDEWEB)
Colnago, Glauber R.; Correia, Paulo B. [Universidade Estadual de Campinas (UNICAMP), Campinas, SP (Brazil). Faculdade de Engenharia Mecanica]. E-mails: grcolnago@fem.unicamp.br; pcorreia@fem.unicamp.br
2006-07-01
This work proposes a mixed integer nonlinear programming model to pre-dispatch of a hydroelectric power plant. In the model we want to minimize the losses in the electricity generation with conditions of electricity demand, operational prohibited zones and units' efficiency data. The Xingo Hydroelectric Power Plant was utilized in the mode tests. The solver used was Lingo 8.0. (author)
Boussinot , Frédéric
1996-01-01
A simple and fully graphical programming method is presented, using a powerful means to combine behaviors. This programming is based on the notion of an «icobj» which has a behavioral aspect («object» part), a graphical aspect («icon» part), with an «animation» aspect. Icobj programming provides parallelism, broadcast event communication and migration through the network. An experimental system based on this approach is described in details. Its implementation with reactive scripts is also pr...
Lutz, Mark
2011-01-01
If you've mastered Python's fundamentals, you're ready to start using it to get real work done. Programming Python will show you how, with in-depth tutorials on the language's primary application domains: system administration, GUIs, and the Web. You'll also explore how Python is used in databases, networking, front-end scripting layers, text processing, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Python's many roles in practical, real-world programming. You'll learn language syntax and programming techniques in a clear and co
International Nuclear Information System (INIS)
Anon.
1977-01-01
The program overview describes the following resources and facilities; laser facilities, main laser room, target room, energy storage, laboratory area, building support systems, general plant project, and the new trailer complex
Solow, Daniel
2014-01-01
This text covers the basic theory and computation for a first course in linear programming, including substantial material on mathematical proof techniques and sophisticated computation methods. Includes Appendix on using Excel. 1984 edition.
Laboratory Delivering science and technology to protect our nation and promote world stability Science & ; Innovation Collaboration Careers Community Environment Science & Innovation Facilities Science Pillars Research Library Science Briefs Science News Science Highlights Lab Organizations Science Programs Applied
Smith, Jason T.; Welsh, Sam J.; Farinetti, Antonio L.; Wegner, Tim; Blakeslee, James; Deboeck, Toni F.; Dyer, Daniel; Corley, Bryan M.; Ollivierre, Jarmaine; Kramer, Leonard;
2010-01-01
A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.
Csernoch, Mária; Biró, Piroska
2015-01-01
Spreadsheet management is a border-land between office applications and programming, however, it is rather communicated that spreadsheet is nothing more than an easily handled fun piece. Consequently, the complexity of spreadsheet handling, the unprepared end-users, their problem solving abilities and approaches do not match. To overcome these problems we have developed and introduced Sprego (Spreadsheet Lego). Sprego is a simplified functional programming language in spreadsheet environment,...
Pawlak , Renaud; Cuesta , Carlos; Younessi , Houman
2004-01-01
This research report presents a promising new approach to computation called Recombinant Programming. The novelty of our approach is that it separates the program into two layers of computation: the recombination and the interpretation layer. The recombination layer takes sequences as inputs and allows the programmer to recombine these sequences through the definition of cohesive code units called extensions. The output of such recombination is a mesh that can be used by the interpretation la...
District Heating Network Design and Configuration Optimization with Genetic Algorithm
DEFF Research Database (Denmark)
Li, Hongwei; Svendsen, Svend
2013-01-01
In this paper, the configuration of a district heating network which connects from the heating plant to the end users is optimized. Each end user in the network represents a building block. The connections between the heat generation plant and the end users are represented with mixed integer...... and the pipe friction and heat loss formulations are non-linear. In order to find the optimal district heating network configuration, genetic algorithm which handles the mixed integer nonlinear programming problem is chosen. The network configuration is represented with binary and integer encoding...... and it is optimized in terms of the net present cost. The optimization results indicates that the optimal DH network configuration is determined by multiple factors such as the consumer heating load, the distance between the heating plant to the consumer, the design criteria regarding the pressure and temperature...
Share-of-Surplus Product Line Optimisation with Price Levels
Directory of Open Access Journals (Sweden)
X. G. Luo
2014-01-01
Full Text Available Kraus and Yano (2003 established the share-of-surplus product line optimisation model and developed a heuristic procedure for this nonlinear mixed-integer optimisation model. In their model, price of a product is defined as a continuous decision variable. However, because product line optimisation is a planning process in the early stage of product development, pricing decisions usually are not very precise. In this research, a nonlinear integer programming share-of-surplus product line optimization model that allows the selection of candidate price levels for products is established. The model is further transformed into an equivalent linear mixed-integer optimisation model by applying linearisation techniques. Experimental results in different market scenarios show that the computation time of the transformed model is much less than that of the original model.
Conforti, Michele; Zambelli, Giacomo
2014-01-01
This book is an elegant and rigorous presentation of integer programming, exposing the subject’s mathematical depth and broad applicability. Special attention is given to the theory behind the algorithms used in state-of-the-art solvers. An abundance of concrete examples and exercises of both theoretical and real-world interest explore the wide range of applications and ramifications of the theory. Each chapter is accompanied by an expertly informed guide to the literature and special topics, rounding out the reader’s understanding and serving as a gateway to deeper study. Key topics include: formulations polyhedral theory cutting planes decomposition enumeration semidefinite relaxations Written by renowned experts in integer programming and combinatorial optimization, Integer Programming is destined to become an essential text in the field.
Malcolme-Lawes, D J
2014-01-01
Programming - ALGOL describes the basics of computer programming using Algol. Commands that could be added to Algol and could increase its scope are described, including multiplication and division and the use of brackets. The idea of labeling or naming a command is also explained, along with a command allowing two alternative results. Most of the important features of Algol syntax are discussed, and examples of compound statements (that is, sets of commands enclosed by a begin ... end command) are given.Comprised of 11 chapters, this book begins with an introduction to the digital computer an
Noble, Joshua
2012-01-01
Ready to create rich interactive experiences with your artwork, designs, or prototypes? This is the ideal place to start. With this hands-on guide, you'll explore several themes in interactive art and design-including 3D graphics, sound, physical interaction, computer vision, and geolocation-and learn the basic programming and electronics concepts you need to implement them. No previous experience is necessary. You'll get a complete introduction to three free tools created specifically for artists and designers: the Processing programming language, the Arduino microcontroller, and the openFr
A new computational method for reactive power market clearing
International Nuclear Information System (INIS)
Zhang, T.; Elkasrawy, A.; Venkatesh, B.
2009-01-01
After deregulation of electricity markets, ancillary services such as reactive power supply are priced separately. However, unlike real power supply, procedures for costing and pricing reactive power supply are still evolving and spot markets for reactive power do not exist as of now. Further, traditional formulations proposed for clearing reactive power markets use a non-linear mixed integer programming formulation that are difficult to solve. This paper proposes a new reactive power supply market clearing scheme. Novelty of this formulation lies in the pricing scheme that rewards transformers for tap shifting while participating in this market. The proposed model is a non-linear mixed integer challenge. A significant portion of the manuscript is devoted towards the development of a new successive mixed integer linear programming (MILP) technique to solve this formulation. The successive MILP method is computationally robust and fast. The IEEE 6-bus and 300-bus systems are used to test the proposed method. These tests serve to demonstrate computational speed and rigor of the proposed method. (author)
International Nuclear Information System (INIS)
Farkas, Z.D.
1977-04-01
A FORTRAN program is described which, for a given cavity and timing, yields all fields as a (piecewise) function of time, and which, for any mix of SLEDded and non-SLEDded klystrons of any given energy/klystron, yields the SLED operation parameters. The note explains the input and output parameters as they appear in the code output. 3 figures, 19 tables
Energy Technology Data Exchange (ETDEWEB)
none
1963-09-01
Parameter optimization studies for an ORGEL power plant are reported, and the ESSOR test reactor used in the program is described. Research at Ispra in reactor physics, technology, metallurgy, heat transfer, chemistry, and physical chemistry associated with ORGEL development is also summarized. (D.C.W.)
Energy Technology Data Exchange (ETDEWEB)
1988-01-01
This book contains the proceedings from the panel on program evaluation. Some of the papers included are the following: Seattle City Light's Industrial Retrofit Demonstration Project Uses Quasi-Experimental Research Design and Metering to Measure Savings, Evaluation for PUCs, and The Takeback Effect Low-income Weatherizations Fact or Fiction
Directory of Open Access Journals (Sweden)
Maria Csernoch
2015-02-01
Full Text Available Spreadsheet management is a border-land between office applications and programming, however, it is rather communicated that spreadsheet is nothing more than an easily handled fun piece. Consequently, the complexity of spreadsheet handling, the unprepared end-users, their problem solving abilities and approaches do not match. To overcome these problems we have developed and introduced Sprego (Spreadsheet Lego. Sprego is a simplified functional programming language in spreadsheet environment, and such as can be used both as introductory language and the language of end-user programmers. The essence of Sprego is that we use as few and simple functions as possible and based on these functions build multilevel formulas. With this approach, similar to high level programming, we are able solve advanced problems, developing algorithmic skills, computational thinking. The advantage of Sprego is the simplicity of the language, when the emphasis is not on the coding but on the problem. Beyond that spreadsheets would provide real life problems with authentic data and tables which students are more interested in than the artificial environment and semi-authentic problems of high level programming languages.
Jeuring, J.T.; Jansson, P.
1996-01-01
Many functions have to be written over and over again for different datatypes, either because datatypes change during the development of programs, or because functions with similar functionality are needed on different datatypes. Examples of such functions are pretty printers, debuggers, equality
International Nuclear Information System (INIS)
Irish, C.S.
2004-01-01
As nuclear plants age, equipment becomes obsolete, outdated or just simply unreliable. This puts a lot of emphasis on replacement of the subject equipment. This can be an expensive proposition for safety related equipment due to design changes, requalification charges and the cost of the new equipment, specifically when the original component is obsolete. The presentation will explain how comprehensive refurbishment programs on many different types of equipment can alleviate this situation. The refurbishment program is a systematic refurbishment of equipment to an as new condition by replacing all of the age sensitive components within the equipment. This is carried out on all of the same type of equipment in a scheduled program. For example the plant may to decide to refurbish all of their Lambda LME-24 power supplies, or all of their Bailey modules, or all of their Agastat DSC Series relays. Independent of the item the process is the same. Refurbish each piece of equipment to an as new condition by replacing all of the age sensitive equipment. The equipment is then returned to the client as safety related, existing qualification maintained and with a new service life/warranty. This is not a simple repair. It is a planned refurbishment to an as new condition of certain equipment types throughout the plant and then carried out from equipment piece to equipment piece. The refurbishment program may even include introducing new spares into the plant. This is normally performed by upgrading (dedicating for safety related use and refurbishing to an 'as new' condition) surplus equipment and using these equipment pieces in the rotation of the plant equipment to refurbish the entire population of a selected piece of equipment at the plant. This process can be performed on many equipment types including power supplies, circuit boards, modules, relays, motors, breakers, and many more. The refurbishment program greatly increases the reliability of the equipment without the
Planning and scheduling for petroleum refineries using mathematical programming
Directory of Open Access Journals (Sweden)
Joly M.
2002-01-01
Full Text Available The objective of this paper is the development and solution of nonlinear and mixed-integer (MIP optimization models for real-world planning and scheduling problems in petroleum refineries. Firstly, we present a nonlinear planning model that represents a general refinery topology and allows implementation of nonlinear process models as well as blending relations. The optimization model is able to define new operating points, thus increasing the production of the more valuable products and simultaneously satisfying all specification constraints. The second part addresses scheduling problems in oil refineries, which are formulated as MIP optimization models and rely on both continuous and discrete time representations. Three practical applications closely related to the current refinery scenario are presented. The first one addresses the problem of crude oil inventory management of a refinery that receives several types of crude oil delivered exclusively by a single oil pipeline. Subsequently, two optimization models intended to define the optimal production policy, inventory control and distribution are proposed and solved for the fuel oil and asphalt plant. Finally, the planning model of Moro et al. (1998 is extended in order to sequence decisions at the scheduling level in the liquefied petroleum gas (LPG area for maximization of the production of petrochemical-grade propane and product delivery.
Constraint Programming versus Mathematical Programming
DEFF Research Database (Denmark)
Hansen, Jesper
2003-01-01
Constraint Logic Programming (CLP) is a relatively new technique from the 80's with origins in Computer Science and Artificial Intelligence. Lately, much research have been focused on ways of using CLP within the paradigm of Operations Research (OR) and vice versa. The purpose of this paper...
A Program to Teach Programming.
Fenichel, Robert R.; And Others
1969-01-01
The TEACH system was developed to provide inexpensive, effective, virtually instructorless instruction in programing. The TEACH system employed an interactive language, UNCL. Two full sections of the TEACH course were taught. The results of this experience suggested ways in which the research and development effort on the system should be…
Program overview: Subsurface science program
International Nuclear Information System (INIS)
1994-03-01
The OHER Subsurface Science Program is DOE's core basic research program concerned with subsoils and groundwater. These practices have resulted in contamination by mixtures of organic chemicals, inorganic chemicals, and radionuclides. A primary long-term goal is to provide a foundation of knowledge that will lead to the reduction of environmental risks and to cost-effective cleanup strategies. Since the Program was initiated in 1985, a substantial amount of research in hydrogeology, subsurface microbiology, and the geochemistry of organically complexed radionuclides has been completed, leading to a better understanding of contaminant transport in groundwater and to new insights into microbial distribution and function in the subsurface environments. The Subsurface Science Program focuses on achieving long-term scientific advances that will assist DOE in the following key areas: providing the scientific basis for innovative in situ remediation technologies that are based on a concept of decontamination through benign manipulation of natural systems; understanding the complex mechanisms and process interactions that occur in the subsurface; determining the influence of chemical and geochemical-microbial processes on co-contaminant mobility to reduce environmental risks; improving predictions of contaminant transport that draw on fundamental knowledge of contaminant behavior in the presence of physical and chemical heterogeneities to improve cleanup effectiveness and to predict environmental risks
Karloff, Howard
1991-01-01
To this reviewer’s knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Method…via the Ellipsoid algorithm to Karmarkar’s algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study. —Choice Reviews The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming. —Mathematics of Computing This is a textbook intend...
International Nuclear Information System (INIS)
1982-07-01
The operating, construction, and development activities of the Department of Energy in the areas of uranium enrichment are described. The DOE supplies the enrichment service through toll enrichment contracts with foreign and domestic utilities by enriching uranium supplied by the utility to the desired U-235 level. This role will continue well into the next century. In addition it provides enriched uranium for US Government needs and for R and D purposes. At the present time, almost all the world's capacity to produce enriched uranium uses the gaseous diffusion process. The United States built the first gaseous diffusion plant during World War II. Later this plant was expanded and two additional plants were built. There is presently a $1.5 billion improvement and uprating program near completion which will improve the plant efficiency and increase the total capacity of the three plants by 60 percent to 27.3 million SWU per year. The Administration's energy message in 1977 provided for a further expansion of this capacity by using gas centrifuge technology. The new gas centrifuge plant is being built near the existing GDP near Portsmouth, Ohio. The normal capacity of an 8 building process plant will be 13.2 million SWU per year. The first 2.2 million SWU of capacity is scheduled to be available in 1989. The remaining capacity will be added as needed to meet demand and the overall goal of the program. The goal of the Uranium Enrichment Program is to meet domestic, foreign, and US Government requirements for uranium enrichment services in an economical, reliable, safe and environmentally acceptable manner. To ensure accomplishment of this goal, the overall program is broken down into three areas of implementation; Enrichment Operations; Capacity Upgrading Operations; and Business Operations
1982-12-01
Paris, France, June, 1982, 519-530. Latoinbe, J. C. "Equipe Intelligence Artificielle et Robotique: Etat d’avancement des recherches," Laboratoire...8217AD-A127 233 ROBOT PROGRRMMING(U) MASSACHUSETTS INST OFGTECHi/ CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T LOZANO-PEREZ UNCLASSIFIED DC8 AI-9 N884...NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA I WORK UNIT NUMBERS ,. 545 Technology Square Cambridge
Spanjersberg , Herman
2012-01-01
International audience; In the 1970s a need arose to perform special arithmetic operations on minicomputers much more quickly than had been possible in the past. This paper tells the story of why micro programming was needed for special arithmetic operations on mini computers in the 1970s and how it was implemented. The paper tells how the laboratory in which the first experiment took place had a PDP-9 minicomputer from Digital Equipment Corporation and how the author, with several colleagues...
Montesi, Fabrizio
2014-01-01
Choreographies are descriptions of distributed systems where the developer gives a global view of how messages are exchanged by endpoint nodes (endpoints for short), instead of separately defining the behaviour of each endpoint. They have a significant impact on the quality of software, as they offer a concise view of the message flows enacted by a system. For this reason, in the last decade choreographies have been used in the development of programming languages, giving rise to a programmin...
Girard, C.; Rinaudo, J. D.; Caballero, Y.; Pulido-Velazquez, M.
2012-04-01
This article presents a case study which illustrates how an integrated hydro-economic model can be applied to optimize a program of measures (PoM) at the river basin level. By allowing the integration of hydrological, environmental and economic aspects at a local scale, this model is indeed useful to assist water policy decision making processes. The model identifies the least cost PoM to satisfy the predicted 2030 urban and agricultural water demands while meeting the in-stream flow constraints. The PoM mainly consists of water saving and conservation measures at the different demands. It includes as well some measures mobilizing additional water resources coming from groundwater, inter-basin transfers and improvement in reservoir operating rules. The flow constraints are defined to ensure a good status of the surface water bodies, as defined by the EU Water Framework Directive (WFD). The case study is conducted in the Orb river basin, a coastal basin in Southern France. It faces a significant population growth, changes in agricultural patterns and limited water resources. It is classified at risk of not meeting the good status by 2015. Urban demand is calculated by type of water users at municipality level in 2006 and projected to 2030 with user specific scenarios. Agricultural water demand is estimated at irrigation district (canton) level in 2000 and projected to 2030 under three agricultural development scenarios. The total annual cost of each measure has been calculated taken into account operation and maintenance costs as well as investment cost. A first optimization model was developed using GAMS, General Algebraic Modeling System, applying Mixed Integer Linear Programming. The optimization is run to select the set of measures that minimizes the objective function, defined as the total cost of the applied measures, while meeting the demands and environmental constraints (minimum in-stream flows) for the 2030 time horizon. The first result is an optimized Po
Fuzzy Itand#244; Integral Driven by a Fuzzy Brownian Motion
Directory of Open Access Journals (Sweden)
Didier Kumwimba Seya
2015-11-01
Full Text Available In this paper we take into account the fuzzy stochastic integral driven by fuzzy Brownian motion. To define the metric between two fuzzy numbers and to take into account the limit of a sequence of fuzzy numbers, we invoke the Hausdorff metric. First this fuzzy stochastic integral is constructed for fuzzy simple stochastic functions, then the construction is done for fuzzy stochastic integrable functions.
International Nuclear Information System (INIS)
Knebel, J.U.
1995-01-01
The SUCO program is a three-step series of scaled model experiments investigating the optional sump cooling concept of the EPR. This concept is entirely based on passive safety features. This report presents the basic physical phenomena and scaling criteria of decay heat removal from a large coolant pool by single-phase and two-phase natural circulation flow. The physical significance of the dimensionless similarity groups derived is evaluated. The report gives first measurement results of the 1:20 linearly scaled plane two-dimensional SUCOS-2D test facility. The real height SUCOT test facility that is in its building up phase is presented. (orig.)
Gates, Alan
2011-01-01
This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop. With Pig, you can batch-process data without having to create a full-fledged application-making it easy for you to experiment with new datasets. Programming Pig introduces new users to Pig, and provides experienced users with comprehensive coverage on key features such as the Pig Latin scripting language, the Grunt shell, and User Defined Functions (UDFs) for extending Pig. If you need to analyze terabytes of data, this book shows you how to do it efficiently
Geothermal Technologies Program Overview - Peer Review Program
Energy Technology Data Exchange (ETDEWEB)
Milliken, JoAnn [Office of Energy Efficiency and Renewable Energy (EERE), Washington, DC (United States)
2011-06-06
This Geothermal Technologies Program presentation was delivered on June 6, 2011 at a Program Peer Review meeting. It contains annual budget, Recovery Act, funding opportunities, upcoming program activities, and more.
International Nuclear Information System (INIS)
Anon.
1979-01-01
The fusion program plan is briefly reviewed and the role of the prototype experimental power reactor, thought of as The Next Step (TNS), is discussed. The required device capabilities and basic reactor concepts for a TNS fusion electric plant are given. A detailed discussion of the physics considerations for the Power Generating Fusion Reactor (PGFR), including plasma heating, MHD equilibrium and stability, burn control resulting from toroidal field ripple, fueling, and boundary effects, is presented. Engineering considerations of the major PGFR systems, as well as diagnostics, instrumentation, control, and programmatic issues are also considered in detail. It is concluded that TNS design studies have established the existence of a technical basis for constructing a long pulse, D-T burning tokamak to be operational prior to 1990
1996-01-01
Since the 1970s, NASA has been involved in the research and demonstration of telemedicine for its potential in the care of astronauts in flight and Earth-bound applications. A combination of NASA funding, expertise and off-the-shelf computer and networking systems made telemedicine possible for a medically underserved hospital in Texas. Through two-way audio/video relay, the program links pediatric oncology specialists at the University of Texas Health Science Center in San Antonio to South Texas Hospital in Harlingen, providing easier access and better care to children with cancer. Additionally, the hospital is receiving teleclinics on pediatric oncology nursing, family counseling and tuberculosis treatment. VTEL Corporation, Sprint, and the Healthcare Open Systems and Trials Consortium also contributed staff and hardware.
International Nuclear Information System (INIS)
Heywood, A.
1993-01-01
Lawrence Livermore National Laboratory (LLNL) initiated several projects with the Boreskov Institute of Catalysis to develop innovative process technologies for the treatment of mixed and hazardous wastes containing a high percentage of organic material. Each of these processes involves the use of catalysts for oxidation (or initial reduction) of the hazardous organic constituents. Because of their commitment to a national mixed waste treatment program, both the Department of Energy/Office of Environmental Management (DOE/EM) and LLNL Environmental Restoration and Waste Management/Applied Technologies (ER-WM/AT) programs have a considerable interest in innovative/alternative flowsheets for organic mixed waste treatment. Selective Catalytic Reduction (SCR) using ammonia as a reducing agent is current a preferred method of treating NO x in off-gases. The advantages of SCR over methods, such as wet scrubbing, include compact design, low maintenance, and the absence of gas cooling requirements and secondary wastes. Any further improvements in catalyst design would lower costs, improve their resistance to poisons, expand their ability to promote oxidation/reduction in mixtures such as NO x /CO, and increase their mechanical strength. An additional requirement of catalysts to be used in California is that the catalyst formulations must meet the California Land Ban disposal restrictions. A monitoring network is needed in Russia to coordinate the environmental monitoring activities of government (including military establishments and facilities) and commercial entities. The network shall incorporate existing as well as proposed monitoring stations. It will comply with all toxic substance control regulations and include analyses for all priority radiochemical and chemical substances. A database compatible with the Environmental Technologies for Remedial Actions Data Exchange (EnviroTRADE) database will ultimately be compiled
Full Text Available ... Trauma Programs Trauma Programs About Trauma Programs Violence Prevention BleedingControl.org Trauma Quality Programs National Trauma Data ... Conference Publications and Posters National Trauma System Injury Prevention and Control Quality and Safety Conference Quality and ...
Human Reliability Program Overview
Energy Technology Data Exchange (ETDEWEB)
Bodin, Michael
2012-09-25
This presentation covers the high points of the Human Reliability Program, including certification/decertification, critical positions, due process, organizational structure, program components, personnel security, an overview of the US DOE reliability program, retirees and academia, and security program integration.
Vehicle Technologies Program Overview
Energy Technology Data Exchange (ETDEWEB)
none,
2006-09-05
Overview of the Vehicle Technologies Program including external assessment and market view; internal assessment, program history and progress; program justification and federal role; program vision, mission, approach, strategic goals, outputs, and outcomes; and performance goals.
Full Text Available ... Trauma Trauma Programs Trauma Programs About Trauma Programs Violence Prevention BleedingControl.org Trauma Quality Programs National Trauma ... Benefits Current Openings Newsroom Newsroom Newsroom Press Releases Media Resources The FIRST Trial ACS Publications ACS in ...
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National Research Council Canada - National Science Library
Oualline, Steve
2003-01-01
... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4 6 3 2. The Basics of Program Writing Programs from Conception to Execution Creating a Real Program Getting Help in Unix Getting Help in an IDE Programming...
Lott, Steven
2015-01-01
This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.
Full Text Available ... Membership Directory 2017 Annual Meeting 2016 Annual Meeting Women's Committee Mentorship Program Outside Activities ACS Archives Contact Us Quality Programs Quality Programs Overview About Quality Programs ACS ...
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Behavioral program synthesis with genetic programming
Krawiec, Krzysztof
2016-01-01
Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subs...
An Intelligent Robot Programing
Energy Technology Data Exchange (ETDEWEB)
Hong, Seong Yong
2012-01-15
This book introduces an intelligent robot programing with background of the begging, introduction of VPL, and SPL, building of environment for robot platform, starting of robot programing, design of simulation environment, robot autonomy drive control programing, simulation graphic. Such as SPL graphic programing graphical image and graphical shapes, and graphical method application, application of procedure for robot control, robot multiprogramming, robot bumper sensor programing, robot LRF sencor programing and robot color sensor programing.
Šmit, Matej
2016-01-01
Most operating systems are written in the C programming language. Similar is with system software, for example, device drivers, compilers, debuggers, disk checkers, etc. Recently some new programming languages emerged, which are supposed to be suitable for system programming. In this thesis we present programming languages D, Go, Nim and Rust. We defined the criteria which are important for deciding whether programming language is suitable for system programming. We examine programming langua...
Purely Functional Structured Programming
Obua, Steven
2010-01-01
The idea of functional programming has played a big role in shaping today's landscape of mainstream programming languages. Another concept that dominates the current programming style is Dijkstra's structured programming. Both concepts have been successfully married, for example in the programming language Scala. This paper proposes how the same can be achieved for structured programming and PURELY functional programming via the notion of LINEAR SCOPE. One advantage of this proposal is that m...
An Intelligent Robot Programing
International Nuclear Information System (INIS)
Hong, Seong Yong
2012-01-01
This book introduces an intelligent robot programing with background of the begging, introduction of VPL, and SPL, building of environment for robot platform, starting of robot programing, design of simulation environment, robot autonomy drive control programing, simulation graphic. Such as SPL graphic programing graphical image and graphical shapes, and graphical method application, application of procedure for robot control, robot multiprogramming, robot bumper sensor programing, robot LRF sencor programing and robot color sensor programing.
Science Programs Applied Energy Programs Civilian Nuclear Energy Programs Laboratory Directed Research » Applied Energy Program Applied Energy Program Los Alamos is using its world-class scientific capabilities to enhance national energy security by developing energy sources with limited environmental impact
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Diabetes Prevention Program (DPP)
... Recruiting Patients & Families Consortia, Networks & Centers Reports & Planning Diabetes Prevention Program (DPP) The NIDDK-sponsored Diabetes Prevention ... Diabetes Prevention Program for those who are eligible. Diabetes Prevention Program (DPP) DPP Goal The DPP looked ...
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Full Text Available ... Verification, Review, and Consultation Program for Hospitals Trauma Systems Consultation Program Trauma Education Achieving Zero Preventable Deaths Conference Publications and Posters ...
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Full Text Available ... Canada) International Fellows Associate Fellows Residents Medical Students Affiliate Members ACS Insurance Programs ACS Discount Programs FACS Resources Career Connection Update ...
Full Text Available ... Validation Programs Accreditation, Verification, and Validation Programs Accredited Education Institutes ... Entering Resident Readiness Assessment Evidence-Based Decisions in ...
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A hybrid approach for biobjective optimization
DEFF Research Database (Denmark)
Stidsen, Thomas Jacob Riis; Andersen, Kim Allan
2018-01-01
to singleobjective problems is that no standard multiobjective solvers exist and specialized algorithms need to be programmed from scratch.In this article we will present a hybrid approach, which operates both in decision space and in objective space. The approach enables massive efficient parallelization and can...... be used to a wide variety of biobjective Mixed Integer Programming models. We test the approach on the biobjective extension of the classic traveling salesman problem, on the standard datasets, and determine the full set of nondominated points. This has only been done once before (Florios and Mavrotas...
A Constraint-Based Model for Fast Post-Disaster Emergency Vehicle Routing
Directory of Open Access Journals (Sweden)
Roberto Amadini
2013-12-01
Full Text Available Disasters like terrorist attacks, earthquakes, hurricanes, and volcano eruptions are usually unpredictable events that affect a high number of people. We propose an approach that could be used as a decision support tool for a post-disaster response that allows the assignment of victims to hospitals and organizes their transportation via emergency vehicles. By exploiting the synergy between Mixed Integer Programming and Constraint Programming techniques, we are able to compute the routing of the vehicles so as to rescue much more victims than both heuristic based and complete approaches in a very reasonable time.
Optimal energy management in pulp and paper mills
International Nuclear Information System (INIS)
Sarimveis, H.K.; Angelou, A.S.; Retsina, T.R.; Rutherford, S.R.; Bafas, G.V.
2003-01-01
In this paper, we examine the utilization of mathematical programming tools for optimum energy management of the power plant in pulp and paper mills. The objective is the fulfillment of the total plant requirements in energy and steam with the minimum possible cost. The proposed methodology is based on the development of a detailed model of the power plant using mass and energy balances and a mathematical formulation of the electrical purchase contract, which can be translated into a rigorous mixed integer linear programming optimization problem. The results show that the method can be a very useful tool for the reduction of production cost due to minimization of the fuel and electricity costs
Process integration: Cooling water systems design
CSIR Research Space (South Africa)
Gololo, KV
2010-10-01
Full Text Available stream_source_info Gololo2_2010.pdf.txt stream_content_type text/plain stream_size 17891 Content-Encoding UTF-8 stream_name Gololo2_2010.pdf.txt Content-Type text/plain; charset=UTF-8 The 13th Asia Pacific Confederation... results in a nonlinear program (NLP) formulation and the second case yields mixed integer nonlinear program (MINLP). In both cases the cooling towers operating capacity were debottlenecked without compromising the heat duties. The 13th Asia...
National Transuranic Program Charter
International Nuclear Information System (INIS)
1994-10-01
The National Transuranic Program Plan and Charter describes the functional elements of the National TRU Program, organizational relationships, programmatic responsibilities, division of work scope among the various DOE organizations that comprise the program, and program baselines against which overall progress will be measured. The charter defines the authorities and responsibilities of various organizations involved in the management of TRU waste throughout the DOE complex
International Nuclear Information System (INIS)
Nelson, E.M.
1996-01-01
Numerous computer programs are available to help accelerator physicists and engineers model and design accelerator cavities and other microwave components. This article discusses the problems these programs solve and the principles upon which these programs are based. Some examples of how these programs are used in the design of accelerator cavities are also given
DEFF Research Database (Denmark)
This book constitutes the refereed proceedings of the Second Symposium on Programs as Data Objects, PADO 2001, held in Aarhus, Denmark, in May 2001. The 14 revised full papers presented were carefully reviewed and selected from 30 submissions. Various aspects of looking at programs as data objects...... are covered from the point of view of program analysis, program transformation, computational complexity, etc....
The Cybernetic Writing Program.
Lowe, Kelly Fisher
This paper looks at the role of a Writing Program Administrator, and applies the idea of a cybernetic system to the administration of the program. In this cybernetic model, the Writing Program Administrator (WPA) works as both a problem solver and problem causer, with the responsibility of keeping the program in proper balance. A cybernetic…
Full Text Available ... Advocacy Efforts Cancer Liaison Program Cancer Programs Conference Clinical Research Program Commission on Cancer National Accreditation Program for ... and Safety Conference ACS Clinical Scholars in Residence Clinical Trials ... Health Services Research Methods Course Surgeon Specific Registry Trauma Education Trauma ...
Maintenance procedure upgrade programs
International Nuclear Information System (INIS)
Campbell, J.J.; Zimmerman, C.M.
1988-01-01
This paper describes a systematic approach to upgrading nuclear power plant maintenance procedures. The approach consists of four phases: diagnosis, program planning, program implementation, and program evaluation. Each phase is explained as a series of steps to ensure that all factors in a procedure upgrade program are considered
Levine, Hermine Zagat
1985-01-01
The author reports company responses to a questionnaire concerning employee assistance programs (EAP). Answers concern EAP structure, staff training, use of outside consultant, services provided by EAPs, program administration, employee confidence in EAPs, advertising the program, program philosophy, problems encountered by EAP users, coverage and…
Environmental conditions analysis program
International Nuclear Information System (INIS)
Holten, J.
1991-01-01
The PC-based program discussed in this paper has the capability of determining the steady state temperatures of environmental zones (rooms). A program overview will be provided along with examples of formula use. Required input and output from the program will also be discussed. Specific application of plant monitored temperatures and utilization of this program will be offered. The presentation will show how the program can project individual room temperature profiles without continual temperature monitoring of equipment. A discussion will also be provided for the application of the program generated data. Evaluations of anticipated or planned plant modifications and the use of the subject program will also be covered
Shaykhian, Gholam Ali
2007-01-01
C++ Programming Language: The C++ seminar covers the fundamentals of C++ programming language. The C++ fundamentals are grouped into three parts where each part includes both concept and programming examples aimed at for hands-on practice. The first part covers the functional aspect of C++ programming language with emphasis on function parameters and efficient memory utilization. The second part covers the essential framework of C++ programming language, the object-oriented aspects. Information necessary to evaluate various features of object-oriented programming; including encapsulation, polymorphism and inheritance will be discussed. The last part of the seminar covers template and generic programming. Examples include both user defined and standard templates.
Federal Wind Energy Program. Program summary. [USA
Energy Technology Data Exchange (ETDEWEB)
None
1978-01-01
The objective of the Federal Wind Energy Program is to accelerate the development of reliable and economically viable wind energy systems and enable the earliest possible commercialization of wind power. To achieve this objective for small and large wind systems requires advancing the technology, developing a sound industrial technology base, and addressing the non-technological issues which could deter the use of wind energy. This summary report outlines the projects being supported by the program through FY 1977 toward the achievement of these goals. It also outlines the program's general organization and specific program elements.
An Analysis of Programming Beginners' Source Programs
Matsuyama, Chieko; Nakashima, Toyoshiro; Ishii, Naohiro
The production of animations was made the subject of a university programming course in order to make students understand the process of program creation, and so that students could tackle programming with interest. In this paper, the formats and composition of the programs which students produced were investigated. As a result, it was found that there were a lot of problems related to such matters as how to use indent, how to apply comments and functions etc. for the format and the composition of the source codes.
Introduction to parallel programming
Brawer, Steven
1989-01-01
Introduction to Parallel Programming focuses on the techniques, processes, methodologies, and approaches involved in parallel programming. The book first offers information on Fortran, hardware and operating system models, and processes, shared memory, and simple parallel programs. Discussions focus on processes and processors, joining processes, shared memory, time-sharing with multiple processors, hardware, loops, passing arguments in function/subroutine calls, program structure, and arithmetic expressions. The text then elaborates on basic parallel programming techniques, barriers and race
Banič, Nejc
2014-01-01
In this thesis, we implemented a way of programming by means of gaming accessories. The main reason is that to show a diferent way of developing programs, because vast majority of programers are using two input / output devices: keyboard and mouse. These two devices have become standard and will definitely remain so in the future. For our implementation, we used high-level programming language Java and NetBeans integrated development environment. The program is actually a ...
Multiobjective programming and planning
Cohon, Jared L
2004-01-01
This text takes a broad view of multiobjective programming, emphasizing the methods most useful for continuous problems. It reviews multiobjective programming methods in the context of public decision-making problems, developing each problem within a context that addresses practical aspects of planning issues. Topics include a review of linear programming, the formulation of the general multiobjective programming problem, classification of multiobjective programming methods, techniques for generating noninferior solutions, multiple-decision-making methods, multiobjective analysis of water reso
Technology Commercialization Program 1991
Energy Technology Data Exchange (ETDEWEB)
1991-11-01
This reference compilation describes the Technology Commercialization Program of the Department of Energy, Defense Programs. The compilation consists of two sections. Section 1, Plans and Procedures, describes the plans and procedures of the Defense Programs Technology Commercialization Program. The second section, Legislation and Policy, identifies legislation and policy related to the Program. The procedures for implementing statutory and regulatory requirements are evolving with time. This document will be periodically updated to reflect changes and new material.
Stochastic integer programming by dynamic programming
Lageweg, B.J.; Lenstra, J.K.; Rinnooy Kan, A.H.G.; Stougie, L.; Ermoliev, Yu.; Wets, R.J.B.
1988-01-01
Stochastic integer programming is a suitable tool for modeling hierarchical decision situations with combinatorial features. In continuation of our work on the design and analysis of heuristics for such problems, we now try to find optimal solutions. Dynamic programming techniques can be used to
Analyzing Array Manipulating Programs by Program Transformation
Cornish, J. Robert M.; Gange, Graeme; Navas, Jorge A.; Schachte, Peter; Sondergaard, Harald; Stuckey, Peter J.
2014-01-01
We explore a transformational approach to the problem of verifying simple array-manipulating programs. Traditionally, verification of such programs requires intricate analysis machinery to reason with universally quantified statements about symbolic array segments, such as "every data item stored in the segment A[i] to A[j] is equal to the corresponding item stored in the segment B[i] to B[j]." We define a simple abstract machine which allows for set-valued variables and we show how to translate programs with array operations to array-free code for this machine. For the purpose of program analysis, the translated program remains faithful to the semantics of array manipulation. Based on our implementation in LLVM, we evaluate the approach with respect to its ability to extract useful invariants and the cost in terms of code size.
Program reference schedule baseline
International Nuclear Information System (INIS)
1986-07-01
This Program Reference Schedule Baseline (PRSB) provides the baseline Program-level milestones and associated schedules for the Civilian Radioactive Waste Management Program. It integrates all Program-level schedule-related activities. This schedule baseline will be used by the Director, Office of Civilian Radioactive Waste Management (OCRWM), and his staff to monitor compliance with Program objectives. Chapter 1 includes brief discussions concerning the relationship of the PRSB to the Program Reference Cost Baseline (PRCB), the Mission Plan, the Project Decision Schedule, the Total System Life Cycle Cost report, the Program Management Information System report, the Program Milestone Review, annual budget preparation, and system element plans. Chapter 2 includes the identification of all Level 0, or Program-level, milestones, while Chapter 3 presents and discusses the critical path schedules that correspond to those Level 0 milestones
Energy Technology Data Exchange (ETDEWEB)
Shipman, Galen M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-06-13
These are the slides for a presentation on programming models in HPC, at the Los Alamos National Laboratory's Parallel Computing Summer School. The following topics are covered: Flynn's Taxonomy of computer architectures; single instruction single data; single instruction multiple data; multiple instruction multiple data; address space organization; definition of Trinity (Intel Xeon-Phi is a MIMD architecture); single program multiple data; multiple program multiple data; ExMatEx workflow overview; definition of a programming model, programming languages, runtime systems; programming model and environments; MPI (Message Passing Interface); OpenMP; Kokkos (Performance Portable Thread-Parallel Programming Model); Kokkos abstractions, patterns, policies, and spaces; RAJA, a systematic approach to node-level portability and tuning; overview of the Legion Programming Model; mapping tasks and data to hardware resources; interoperability: supporting task-level models; Legion S3D execution and performance details; workflow, integration of external resources into the programming model.
Revealing the programming process
DEFF Research Database (Denmark)
Bennedsen, Jens; Caspersen, Michael Edelgaard
2005-01-01
One of the most important goals of an introductory programming course is that the students learn a systematic approach to the development of computer programs. Revealing the programming process is an important part of this; however, textbooks do not address the issue -- probably because...... the textbook medium is static and therefore ill-suited to expose the process of programming. We have found that process recordings in the form of captured narrated programming sessions are a simple, cheap, and efficient way of providing the revelation.We identify seven different elements of the programming...
International Nuclear Information System (INIS)
Vaturi, Sylvain
1969-01-01
Computerized edition is essential for data processing exploitation. When a more or less complex edition program is required for each task, then the need for a general edition program become obvious. The aim of this study is to create a general edition program. Universal programs are capable to execute numerous and varied tasks. For a more precise processing, the execution of which is frequently required, the use of a specialized program is preferable because, contradictory to the universal program, it goes straight to the point [fr
International Nuclear Information System (INIS)
Bornapour, Mosayeb; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin; Parastegari, Moein
2017-01-01
Highlights: • Stochastic model is proposed for coordinated scheduling of renewable energy sources. • The effect of combined heat and power is considered. • Uncertainties of wind speed, solar radiation and electricity market price are considered. • Profit maximization, emission and AENS minimization are considered as objective functions. • Modified firefly algorithm is employed to solve the problem. - Abstract: Nowadays the operation of renewable energy sources and combined heat and power (CHP) units is increased in micro grids; therefore, to reach optimal performance, optimal scheduling of these units is required. In this regard, in this paper a micro grid consisting of proton exchange membrane fuel cell-combined heat and power (PEMFC-CHP), wind turbines (WT) and photovoltaic (PV) units, is modeled to determine the optimal scheduling state of these units by considering uncertain behavior of renewable energy resources. For this purpose, a scenario-based method is used for modeling the uncertainties of electrical market price, the wind speed, and solar irradiance. It should be noted that the hydrogen storage strategy is also applied in this study for PEMFC-CHP units. Market profit, total emission production, and average energy not supplied (AENS) are the objective functions considered in this paper simultaneously. Consideration of the above-mentioned objective functions converts the proposed problem to a mixed integer nonlinear programming. To solve this problem, a multi-objective firefly algorithm is used. The uncertainties of parameters convert the mixed integer nonlinear programming problem to a stochastic mixed integer nonlinear programming problem. Moreover, optimal coordinated scheduling of renewable energy resources and thermal units in micro-grids improve the value of the objective functions. Simulation results obtained from a modified 33-bus distributed network as a micro grid illustrates the effectiveness of the proposed method.
Cyclic delivery scheduling to customers with different priorities
Directory of Open Access Journals (Sweden)
Katarzyna Zofia Gdowska
2013-12-01
Full Text Available Background: In this paper a cyclic delivery scheduling problem for customers with different priorities is presented. Shops, which are provided with deliveries, are occasionally located in places which are crucial for the proper flow of traffic. In such places coordination of deliveries is crucial; therefore it allows to completely eliminate the phenomenon of the simultaneous arrivals of suppliers. Methods: In this paper the cyclic delivery scheduling problem for customers with different priorities was presented. To this theoretical problem a mix integer programming model was developed. Specific approach to the cyclic delivery scheduling problem is inspired by timetabling problem for urban public transport. Results: Mixed integer programming model was employed for solving four cases of cyclic delivery scheduling problem for customers with different priorities. When the value of the synchronization priority assigned to a single customer raised then the total number of synchronizations in the whole network decreased. In order to compare solutions a synchronization rate was utilized. A simple factor was utilized - the proportion of number of synchronizations of deliveries to a given customer to the total number of synchronizations obtained for the whole network. When the value of synchronization priority raised then the value of synchronization rate of this customer improved significantly. Conclusions: The mixed integer programming model for the cyclic delivery scheduling problem for customers with different priorities presented in this paper can be utilized for generating schedules of serving customers located in places where only one delivery can be received and unloaded at one go and where there is no space for other suppliers to wait in a queue. Such a schedule can be very useful for organizing deliveries to small shops united in a franchising network, since they operate in a way that is very similar to the network presented in this paper
Employee assistance programs: history and program description.
Gilbert, B
1994-10-01
1. The history and development of Employee Assistance Programs (EAPs) can be traced back to the 1800s. There are currently over 10,000 EAPs in the United States. 2. Standards for program accreditation and counselor certification have been established for EAPs. The "core technology of Employee Assistance Programs" includes identification of behavioural problems based on job performance issues, expert consultation with supervisors, appropriate use of constructive confrontation, microlinkages with treatment providers and resources, macrolinkages between providers, resources, and work organizations, focus on substance abuse, and evaluation of employee success based on job performance. 3. Some EAPs take a broad brush approach, and incorporate health promotion and managed care functions.
Department of Housing and Urban Development — Income limits used to determine the income eligibility of applicants for assistance under three programs authorized by the National Housing Act. These programs are...
International Nuclear Information System (INIS)
Briggs, R.J.; Hester, R.E.; Porter, G.D.; Sherwood, W.A.; Spoerlein, R.; Stallard, B.W.; Taska, J.; Weiss, P.B.
1975-01-01
This report describes important experimental results obtained in the last two years of the Astron Program, an LLL controlled nuclear fusion program which terminated in 1973. Little theoretical work is included, but an extensive bibliography is given
Full Text Available ... Quality Standard Optimal Resources for Surgical Quality and Safety Inspiring Quality Initiative Resources Continuous Quality Improvement ACS Clinical Scholars in Residence AHRQ Safety Program for ISCR AHRQ Safety Program for ISCR ...
Full Text Available ... Member Fellows International Fellows Associate Fellows Residents Medical Students Affiliate Members Fees and Dues Realize the Potential ... and Canada) International Fellows Associate Fellows Residents Medical Students Affiliate Members ACS Insurance Programs ACS Discount Programs ...
LSPC is the Loading Simulation Program in C++, a watershed modeling system that includes streamlined Hydrologic Simulation Program Fortran (HSPF) algorithms for simulating hydrology, sediment, and general water quality
Full Text Available ... Program Trauma Education Achieving Zero Preventable Deaths Conference Publications and Posters National Trauma System Injury Prevention and ... Division of Education ACS Education and Training Courses Publications Resources Education Program Videos Contact Us Clinical Congress ...
... NTP? NTP develops and applies tools of modern toxicology and molecular biology to identify substances in the ... depend on for decisions that matter. The National Toxicology Program provides the scientific basis for programs, activities, ...
Department of Veterans Affairs — If you are already enrolled in VA health care, the Choice Program allows you to receive health care within your community. Using this program does NOT impact your...
French plutonium management program
International Nuclear Information System (INIS)
Greneche, D.
2002-01-01
The French plutonium management program is summarized in this paper. The program considers nuclear generation as a major component of national electric power supply and includes the reprocessing of the spent fuel. (author)
U.S. Department of Health & Human Services — The Entrez Programming Utilities (E-utilities) are a set of eight server-side programs that provide a stable interface into the Entrez query and database system at...
U.S. Environmental Protection Agency — LSPC is the Loading Simulation Program in C++, a watershed modeling system that includes streamlined Hydrologic Simulation Program Fortran (HSPF) algorithms for...
Coalbed Methane Outreach Program
Coalbed Methane Outreach Program, voluntary program seeking to reduce methane emissions from coal mining activities. CMOP promotes profitable recovery/use of coal mine methane (CMM), addressing barriers to using CMM instead of emitting it to atmosphere.
Full Text Available ... JACS Jobs Events Find a Surgeon Patients and Family Contact My Profile Shop ( 0 ) Cart Donate American College of Surgeons Education Patients and Family Skills Programs Ostomy Home Skills Program Ostomy Home ...
Full Text Available ... SESAP Sampler SRGS Resources in Surgical Education ACS Fundamentals of Surgery Curriculum Mastery in General Surgery Program ... Communications to the Profession Advocacy Advocacy Overview Quality Payment Program QPP Resource Center QPP Resource Center 2018 ...
Full Text Available ... Profession Member Benefits About Member Benefits About Member Benefits Fellows (US and Canada) International Fellows Associate Fellows Residents Medical Students Affiliate Members ACS Insurance Programs ACS Discount Programs ...
& Development (LDRD) National Security Education Center (NSEC) Office of Science Programs Richard P Databases National Security Education Center (NSEC) Center for Nonlinear Studies Engineering Institute Scholarships STEM Education Programs Teachers (K-12) Students (K-12) Higher Education Regional Education
Full Text Available ... Program State Legislation Tracked by the College Maintenance of Certification Quality Quality Quality Electronic Health Records (EHR) Incentive Program Physician Quality Reporting System Value-Based Payment Modifier Quality and Resource Use ...
Full Text Available ... About Quality Programs ACS Leadership in Quality ACS Leadership in Quality Setting the Quality Standard Optimal Resources for Surgical Quality and Safety Inspiring Quality Initiative Resources Continuous Quality Improvement ACS Clinical Scholars in Residence AHRQ Safety Program ...
Full Text Available ... My OR EHR Incentive Program Global Codes and Data Collection Patient Opioid Use New Medicare Card Project Medicare ... self-care checklist Evaluation (Complete the Ostomy Patient Survey . We need your opinion!) Program outcomes The ACS ...
Full Text Available ... Careers at ACS Careers at ACS About ACS Career Types Working at ACS ... American College of Surgeons Education Patients and Family Skills Programs Ostomy Home Skills Program Ostomy Home Skills ...
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Understanding Participation in Programs.
Hanson, Alan L.
1991-01-01
Adherence to program planning principles does not guarantee participation. Attention must be paid to characteristics that make a program responsive: target audience, promotion and marketing, competition, and logistics. (SK)
International Nuclear Information System (INIS)
1977-01-01
A compilation and index of the ERDA materials sciences program is presented. This compilation is intended for use by administrators, managers, and scientists to help coordinate research and as an aid in selecting new programs
National Research Council Canada - National Science Library
Stryjewski, John
1998-01-01
The BMDO Innovative Science and Technology Experimentation Facility (BMDO/ISTEF) laser radar program is engaged in an ongoing program to develop and demonstrate advanced laser radar concepts for Ballistic Missile Defense (BMD...
Programming Language Paradigms
Felician ALECU
2013-01-01
This paper's goal is to briefly explain the basic theory behind programming languages and their history while taking a close look at different programming paradigms that are used today as well as describing their differences, benefits, and drawbacks
ICASE Computer Science Program
1985-01-01
The Institute for Computer Applications in Science and Engineering computer science program is discussed in outline form. Information is given on such topics as problem decomposition, algorithm development, programming languages, and parallel architectures.
International Nuclear Information System (INIS)
Burgess, R.L.
1978-01-01
Progress is reported on the following research programs: analysis and modeling of ecosystems; EDFB/IBP data center; biome analysis studies; land/water interaction studies; and computer programs for development of models
Bogdanchikov, A.; Zhaparov, M.; Suliyev, R.
2013-04-01
Today we have a lot of programming languages that can realize our needs, but the most important question is how to teach programming to beginner students. In this paper we suggest using Python for this purpose, because it is a programming language that has neatly organized syntax and powerful tools to solve any task. Moreover it is very close to simple math thinking. Python is chosen as a primary programming language for freshmen in most of leading universities. Writing code in python is easy. In this paper we give some examples of program codes written in Java, C++ and Python language, and we make a comparison between them. Firstly, this paper proposes advantages of Python language in relation to C++ and JAVA. Then it shows the results of a comparison of short program codes written in three different languages, followed by a discussion on how students understand programming. Finally experimental results of students' success in programming courses are shown.
Full Text Available ... Meetings and Events Scholarships, Competitions, Awards, and Project Work Top 10 Reasons to Participate Grand Rounds Webinar ... Accreditation Program for Breast Centers About NAPBC Accreditation Education NAPBC Standards Cancer Programs News Quality in Geriatric ...
Modeling EERE deployment programs
Energy Technology Data Exchange (ETDEWEB)
Cort, K. A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hostick, D. J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Belzer, D. B. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Livingston, O. V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2007-11-01
The purpose of the project was to identify and characterize the modeling of deployment programs within the EERE Technology Development (TD) programs, address possible improvements to the modeling process, and note gaps in knowledge for future research.
Full Text Available ... About ACS NSQIP Join ACS NSQIP Now Collaboratives Hospital Compare Quality and Safety Conference Participant Use Data ... Life Support Verification, Review, and Consultation Program for Hospitals Trauma Systems Consultation Program Trauma Education Achieving Zero ...
Full Text Available ... Centers National Cancer Database National Accreditation Program for Rectal Cancer Oncology Medical Home Accreditation Program Stereotactic Breast ... collaboration with the American Society of Colon and Rectal Surgeons (ASCRS), American Urological Association (AUA), Certified Enterostomal ...
Youth Suicide Prevention Programs
Kalafat, John
2006-01-01
Youth suicide prevention programs are described that promote the identification and referral of at-risk youth, address risk factors, and promote protective factors. Emphasis is on programs that are both effective and sustainable in applied settings.
Crab Rationalization Permit Program
National Oceanic and Atmospheric Administration, Department of Commerce — The Crab Rationalization Program (Program) allocates BSAI crab resources among harvesters, processors, and coastal communities. The North Pacific Fishery Management...
Dental Assisting Program Standards.
Georgia Univ., Athens. Dept. of Vocational Education.
This publication contains statewide standards for the dental assisting program in Georgia. The standards are divided into 12 categories: foundations (philosophy, purpose, goals, program objectives, availability, evaluation); admissions (admission requirements, provisional admission requirements, recruitment, evaluation and planning); program…
International Nuclear Information System (INIS)
Shearer, J.W.
1975-01-01
A summary is given of the history and rationale of the USSR program to implode metallic liners for the fusion program. The explosive driven, magnetic drive, and compressed gas driven research is reviewed. (MOW)
Full Text Available ... Associate Fellows Residents Medical Students Affiliate Members ACS Insurance Programs ACS Discount Programs FACS Resources Career Connection ... and Awards Overview Scholarships, Fellowships, and Awards Overview Health Policy Scholarships Scholarships for International Surgeons Research Scholarships ...
Full Text Available ... Class Clinical Congress 2018 Events at Clinical Congress Child Care at Clinical Congress Info for International Attendees ... Accreditation Program for Breast Centers About NAPBC Accreditation Education NAPBC Standards Cancer Programs News Quality in Geriatric ...
Full Text Available ... You Want to Be a Surgeon Resident Resources Teaching Resources Online Guide to Choosing a Surgical Residency ... Research Findings Quality Program Initiatives Communications to the Profession Advocacy Advocacy Overview Quality Payment Program QPP Resource ...
CERN. Geneva
2017-01-01
Reactive Programming in gaining a lot of excitement. Many libraries, tools, and frameworks are beginning to make use of reactive libraries. Besides, applications dealing with big data or high frequency data can benefit from this programming paradigm. Come to this presentation to learn about what reactive programming is, what kind of problems it solves, how it solves them. We will take an example oriented approach to learning the programming model and the abstraction.
Photovoltaic systems. Program summary
Energy Technology Data Exchange (ETDEWEB)
None
1978-12-01
Each of the Department of Energy's Photovoltaic Systems Program projects funded and/or in existence during fiscal year 1978 (October 1, 1977 through September 30, 1978) are described. The project sheets list the contractor, principal investigator, and contract number and funding and summarize the programs and status. The program is divided into various elements: program assessment and integration, research and advanced development, technology development, system definition and development, system application experiments, and standards and performance criteria. (WHK)
Full Text Available ... State Requirements Contact Online Education Accreditation, Verification, and Validation Accreditation, Verification, and Validation Programs Accreditation, Verification, and ...
Black, Susan
1993-01-01
Like British morning programs of recent decades, upstate New York program encourages parents and community residents to get involved in children's education. Parents and community residents--watercolor artists, auto mechanics, doll collectors, and others--are welcomed and valued in schools. Program's purpose is learning, not entertainment. Topics…
1982-01-01
Use of computer program STRCMACS has enabled Illinois Bell Telephone, a subsidiary of American Telephone and Telegraph to cut software development costs about 10 percent by reducing program maintenance and by allowing the department to bring other software into operation more quickly. It has also been useful in company training of programming staff.
Maine's Employability Skills Program
McMahon, John M.; Wolffe, Karen E.; Wolfe, Judy; Brooker, Carrie
2013-01-01
This Practice Report describes the development and implementation of the "Maine Employability Skills Program," a model employment program developed by the Maine Division for the Blind and Visually Impaired (DBVI). The program was designed to support the efforts of the chronically unemployed or underemployed. These consumers were either…
An Interdistrict Transfer Program
Gross, Norman
1975-01-01
This testimony, before the May 1974 public hearings of the New York City Commission on Human Rights by the Administrator, Urban-Suburban Transfer Program and Inter district Transfer Program, West Irondequoit School District, New York, reviews a program which began with 25 minority group youngsters from one racially-imbalanced Rochester school…
Trefney, Charles J.
1999-01-01
This paper presents the "Three Pillars of Success" for the Trailblazer Program. The topics include: 1) The "Rocket Equation" for SSTO (Single Stage To Orbit); 2) The Rocket I* Barrier; 3) Rocket-Based Combined-Cycle Engine; 4) Potential for Reusability; 5) Factors Mitigating RBCC Performance; 6) The "Trailblazer" Program; 7) Trailblazer Performance Goals; 8) Trailblazer Reference Vehicle; and 9) Trailblazer Program Architecture.
Full Text Available ... Trauma Programs About Trauma Programs Violence Prevention BleedingControl.org Trauma Quality Programs National Trauma Data Bank Trauma ... 5000 (F) 312-202-5001 (E) postmaster@facs.org Copyright © 1996-2018 by the American College of ...
Full Text Available ... Ostomy Home Skills Program Ostomy Home Skills Program Adult Ostomy Pediatric Ostomy Programa de Destrezas para manejo Doméstico de Ostomía Ostomy Home Skills Program Adult Ostomy Pediatric Ostomy Programa de Destrezas para manejo ...
International Nuclear Information System (INIS)
Perez, P.B.
1993-01-01
The Nuclear Reactor Program at North Carolina State University provides the PULSTAR Research Reactor and associated facilities to eligible institutions with support, in part, from the Department of Energy Reactor Sharing Program. Participation in the NCSU Reactor Sharing Program continues to increase steadily with visitors ranging from advance high school physics and chemistry students to Ph.D. level research from neighboring universities
Programs, interfaces and components
Bergstra, J.A.; Loots, M.E.
The jump instruction is considered essential for an adequate theoretical understanding of imperative sequential programming. Using atomic actions and tests as a basis we outline an algebra of programs, denoted PGA, which captures the crux of sequential programming. PGA provides an ontology for
Trends in Multicultural Programming.
Mylopoulos, Chryss
1985-01-01
Outlines basic principles and philosophy behind library multicultural programs and provides brief overview of development of such programs in Canadian libraries. Programing themes (cultural identity, contribution of ethnocultural groups to Canadian society, interpretation of multiculturalism as social policy) and suggestions for integrating…
US Department of Agriculture, 2009
2009-01-01
The Special Milk Program provides milk to children in schools, child care institutions and eligible camps that do not participate in other Federal child nutrition meal service programs. The program reimburses schools and institutions for the milk they serve. In 2008, 4,676 schools and residential child care institutions participated, along with…
California State Dept. of Education, Sacramento. Div. of School Facilities Planning.
This report examines single- and multi-track educational programs as found in California's public school system, explores the pros and cons of using year-round education (YRE) programs, and how to implement these programs. Each year-round tracking system is detailed using each of their calendars in a side-by-side comparison along with the…
Feldman, G. H.; Johnson, J. A.
1980-01-01
Structural-programming language is especially-tailored for producing assembly language programs for MODCOMP II and IV mini-computes. Modern programming language consists of set of simple and powerful control structures that include sequencing alternative selection, looping, sub-module linking, comment insertion, statement continuation, and compilation termination capabilities.
Ferguson, John D; Macari, Louie; Williams, Peter H
1983-01-01
Programming the BBC Micro is a 12-chapter book that begins with a description of the BBC microcomputer, its peripheral, and faults. Subsequent chapters focus on practice in programming, program development, graphics, words, numbers, sound, bits, bytes, and assembly language. The interfacing, file handling, and detailed description of BBC microcomputer are also shown.
Weatherization and Intergovernmental Program - Weatherization Assistance Program
Energy Technology Data Exchange (ETDEWEB)
None
2010-06-01
The U.S. Department of Energy’s (DOE) Weatherization Assistance Program reduces energy costs for low-income households by increasing the energy efficiency of their homes, while ensuring their health and safety.
Equipment qualification research program: program plan
International Nuclear Information System (INIS)
Dong, R.G.; Smith, P.D.
1982-01-01
The Lawrence Livermore National Laboratory (LLNL) under the sponsorship of the US Nuclear Regulatory Commission (NRC) has developed this program plan for research in equipment qualification (EQA). In this report the research program which will be executed in accordance with this plan will be referred to as the Equipment Qualification Research Program (EQRP). Covered are electrical and mechanical equipment under the conditions described in the OBJECTIVE section of this report. The EQRP has two phases; Phase I is primarily to produce early results and to develop information for Phase II. Phase I will last 18 months and consists of six projects. The first project is program management. The second project is responsible for in-depth evaluation and review of EQ issues and EQ processes. The third project is responsible for detailed planning to initiate Phase II. The remaining three projects address specific equipment; i.e., valves, electrical equipment, and a pump
Scallop License Limitation Program (SLLP) Permit Program
National Oceanic and Atmospheric Administration, Department of Commerce — A federal Scallop License Limitation Program (SLLP) license is required onboard any vessel deployed in scallop fisheries in Federal waters off Alaska (except for...
Clean Coal Technology Programs: Program Update 2009
Energy Technology Data Exchange (ETDEWEB)
None
2009-10-01
The purpose of the Clean Coal Technology Programs: Program Update 2009 is to provide an updated status of the U.S. Department of Energy (DOE) commercial-scale demonstrations of clean coal technologies (CCT). These demonstrations have been performed under the Clean Coal Technology Demonstration Program (CCTDP), the Power Plant Improvement Initiative (PPII), and the Clean Coal Power Initiative (CCPI). Program Update 2009 provides: (1) a discussion of the role of clean coal technology demonstrations in improving the nation’s energy security and reliability, while protecting the environment using the nation’s most abundant energy resource—coal; (2) a summary of the funding and costs of the demonstrations; and (3) an overview of the technologies being demonstrated, along with fact sheets for projects that are active, recently completed, or recently discontinued.
The Optimization dispatching of Micro Grid Considering Load Control
Zhang, Pengfei; Xie, Jiqiang; Yang, Xiu; He, Hongli
2018-01-01
This paper proposes an optimization control of micro-grid system economy operation model. It coordinates the new energy and storage operation with diesel generator output, so as to achieve the economic operation purpose of micro-grid. In this paper, the micro-grid network economic operation model is transformed into mixed integer programming problem, which is solved by the mature commercial software, and the new model is proved to be economical, and the load control strategy can reduce the charge and discharge times of energy storage devices, and extend the service life of the energy storage device to a certain extent.
A service flow model for the liner shipping network design problem
DEFF Research Database (Denmark)
Plum, Christian Edinger Munk; Pisinger, David; Sigurd, Mikkel M.
2014-01-01
. The formulation alleviates issues faced by arc flow formulations with regards to handling multiple calls to the same port. A problem which has not been fully dealt with earlier by LSNDP formulations. Multiple calls are handled by introducing service nodes, together with port nodes in a graph representation...... of the network and a penalty for not flowed cargo. The model can be used to design liner shipping networks to utilize a container carrier’s assets efficiently and to investigate possible scenarios of changed market conditions. The model is solved as a Mixed Integer Program. Results are presented for the two...
Optimal set of selected uranium enrichments that minimizes blending consequences
International Nuclear Information System (INIS)
Nachlas, J.A.; Kurstedt, H.A. Jr.; Lobber, J.S. Jr.
1977-01-01
Identities, quantities, and costs associated with producing a set of selected enrichments and blending them to provide fuel for existing reactors are investigated using an optimization model constructed with appropriate constraints. Selected enrichments are required for either nuclear reactor fuel standardization or potential uranium enrichment alternatives such as the gas centrifuge. Using a mixed-integer linear program, the model minimizes present worth costs for a 39-product-enrichment reference case. For four ingredients, the marginal blending cost is only 0.18% of the total direct production cost. Natural uranium is not an optimal blending ingredient. Optimal values reappear in most sets of ingredient enrichments
Lagrangian duality applied to the vehicle routing problem with time windows
DEFF Research Database (Denmark)
Kallehauge, Brian; Larsen, Jesper; Madsen, Oli B.G.
2006-01-01
This paper considers the vehicle routing problem with time windows, where the service of each customer must start within a specified time interval. We consider the Lagrangian relaxation of the constraint set requiring that each customer must be served by exactly one vehicle yielding a constrained...... respectively, which to date are the largest problems ever solved to optimality. We have implemented the LBCP algorithm using the ABACUS open-source framework for solving mixed-integer linear-programs by branch, cut, and price....
The dynamic multi-period vehicle routing problem
DEFF Research Database (Denmark)
Wen, Min; Cordeau, Jean-Francois; Laporte, Gilbert
2010-01-01
are to minimize total travel costs and customer waiting, and to balance the daily workload over the planning horizon. This problem originates from a large distributor operating in Sweden. It is modeled as a mixed integer linear program, and solved by means of a three-phase heuristic that works over a rolling...... planning horizon. The multi-objective aspect of the problem is handled through a scalar technique approach. Computational results show that the proposed approach can yield high quality solutions within reasonable running times....
Integrated sizing and scheduling of wind/PV/diesel/battery isolated systems
Malheiro, André
2015-05-22
In this paper we address the optimal sizing and scheduling of isolated hybrid systems using an optimization framework. The hybrid system features wind and photovoltaic conversion systems, batteries and diesel backup generators to supply electricity demand. A Mixed-Integer Linear Programming formulation is used to model system behavior over a time horizon of one year, considering hourly changes in both the availability of renewable resources and energy demand. The optimal solution is achieved with respect to the minimization of the levelized cost of energy (LCOE) over a lifetime of 20 years. Results for a case study show that the most economical solution features all four postulated subsystems. © 2015 Elsevier Ltd.
Exact Methods for Solving the Train Departure Matching Problem
DEFF Research Database (Denmark)
Haahr, Jørgen Thorlund; Bull, Simon Henry
In this paper we consider the train departure matching problem which is an important subproblem of the Rolling Stock Unit Management on Railway Sites problem introduced in the ROADEF/EURO Challenge 2014. The subproblem entails matching arriving train units to scheduled departing trains at a railway...... site while respecting multiple physical and operational constraints. In this paper we formally define that subproblem, prove its NP- hardness, and present two exact method approaches for solving the problem. First, we present a compact Mixed Integer Program formulation which we solve using a MIP solver...
Optimizing wind farm cable routing considering power losses
DEFF Research Database (Denmark)
Fischetti, Martina; Pisinger, David
2017-01-01
that must be spent immediately in cable and installation costs, and the future reduced revenues due to power losses. The latter goal has not been addressed in previous work. We present a Mixed-Integer Linear Programming approach to optimize the routing using both exact and math-heuristic methods....... In the power losses computation, wind scenarios are handled eciently as part of the preprocessing, resulting in a MIP model of only slightly larger size. A library of real-life instances is introduced and made publicly available for benchmarking. Computational results on this testbed show the viability of our...