Optimal recombination in genetic algorithms for flowshop scheduling problems
Kovalenko, Julia
2016-10-01
The optimal recombination problem consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We prove NP-hardness of the optimal recombination for various variants of the flowshop scheduling problem with makespan criterion and criterion of maximum lateness. An algorithm for solving the optimal recombination problem for permutation flowshop problems is built, using enumeration of prefect matchings in a special bipartite graph. The algorithm is adopted for the classical flowshop scheduling problem and for the no-wait flowshop problem. It is shown that the optimal recombination problem for the permutation flowshop scheduling problem is solvable in polynomial time for almost all pairs of parent solutions as the number of jobs tends to infinity.
Flow-shop scheduling problem under uncertainties: Review and trends
Directory of Open Access Journals (Sweden)
Eliana María González-Neira
2017-03-01
Full Text Available Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.
SOLVING FLOWSHOP SCHEDULING PROBLEMS USING A DISCRETE AFRICAN WILD DOG ALGORITHM
Directory of Open Access Journals (Sweden)
M. K. Marichelvam
2013-04-01
Full Text Available The problem of m-machine permutation flowshop scheduling is considered in this paper. The objective is to minimize the makespan. The flowshop scheduling problem is a typical combinatorial optimization problem and has been proved to be strongly NP-hard. Hence, several heuristics and meta-heuristics were addressed by the researchers. In this paper, a discrete African wild dog algorithm is applied for solving the flowshop scheduling problems. Computational results using benchmark problems show that the proposed algorithm outperforms many other algorithms addressed in the literature.
A PSO-based hybrid metaheuristic for permutation flowshop scheduling problems.
Zhang, Le; Wu, Jinnan
2014-01-01
This paper investigates the permutation flowshop scheduling problem (PFSP) with the objectives of minimizing the makespan and the total flowtime and proposes a hybrid metaheuristic based on the particle swarm optimization (PSO). To enhance the exploration ability of the hybrid metaheuristic, a simulated annealing hybrid with a stochastic variable neighborhood search is incorporated. To improve the search diversification of the hybrid metaheuristic, a solution replacement strategy based on the pathrelinking is presented to replace the particles that have been trapped in local optimum. Computational results on benchmark instances show that the proposed PSO-based hybrid metaheuristic is competitive with other powerful metaheuristics in the literature.
Li, Jun-qing; Pan, Quan-ke; Mao, Kun
2014-01-01
A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm. PMID:24883414
Directory of Open Access Journals (Sweden)
Jun-qing Li
2014-01-01
Full Text Available A hybrid algorithm which combines particle swarm optimization (PSO and iterated local search (ILS is proposed for solving the hybrid flowshop scheduling (HFS problem with preventive maintenance (PM activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron’s benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.
Li, Jun-qing; Pan, Quan-ke; Mao, Kun
2014-01-01
A hybrid algorithm which combines particle swarm optimization (PSO) and iterated local search (ILS) is proposed for solving the hybrid flowshop scheduling (HFS) problem with preventive maintenance (PM) activities. In the proposed algorithm, different crossover operators and mutation operators are investigated. In addition, an efficient multiple insert mutation operator is developed for enhancing the searching ability of the algorithm. Furthermore, an ILS-based local search procedure is embedded in the algorithm to improve the exploitation ability of the proposed algorithm. The detailed experimental parameter for the canonical PSO is tuning. The proposed algorithm is tested on the variation of 77 Carlier and Néron's benchmark problems. Detailed comparisons with the present efficient algorithms, including hGA, ILS, PSO, and IG, verify the efficiency and effectiveness of the proposed algorithm.
A hybrid genetic algorithm for the distributed permutation flowshop scheduling problem
Directory of Open Access Journals (Sweden)
Jian Gao
2011-08-01
Full Text Available Distributed Permutation Flowshop Scheduling Problem (DPFSP is a newly proposed scheduling problem, which is a generalization of classical permutation flow shop scheduling problem. The DPFSP is NP-hard in general. It is in the early stages of studies on algorithms for solving this problem. In this paper, we propose a GA-based algorithm, denoted by GA_LS, for solving this problem with objective to minimize the maximum completion time. In the proposed GA_LS, crossover and mutation operators are designed to make it suitable for the representation of DPFSP solutions, where the set of partial job sequences is employed. Furthermore, GA_LS utilizes an efficient local search method to explore neighboring solutions. The local search method uses three proposed rules that move jobs within a factory or between two factories. Intensive experiments on the benchmark instances, extended from Taillard instances, are carried out. The results indicate that the proposed hybrid genetic algorithm can obtain better solutions than all the existing algorithms for the DPFSP, since it obtains better relative percentage deviation and differences of the results are also statistically significant. It is also seen that best-known solutions for most instances are updated by our algorithm. Moreover, we also show the efficiency of the GA_LS by comparing with similar genetic algorithms with the existing local search methods.
Directory of Open Access Journals (Sweden)
Mehmet Fatih Tasgetiren
2016-10-01
Full Text Available In this paper, we present a variable block insertion heuristic (VBIH algorithm to solve the blocking flowshop scheduling problem with the total flowtime criterion. In the VBIH algorithm, we define a minimum and a maximum block size. After constructing the initial sequence, the VBIH algorithm starts with a minimum block size being equal to one. It removes the block from the current sequence and inserts it into the partial sequence sequentially with a predetermined move size. The sequence, which is obtained after several block moves, goes under a variable local search (VLS, which is based on traditional insertion and swap neighborhood structures. If the new sequence obtained after the VLS local search is better than the current sequence, it replaces the current sequence. As long as it improves, it keeps the same block size. However, if it does not improve, the block size is incremented by one and a simulated annealing-type of acceptance criterion is used to accept the current sequence. This process is repeated until the block size reaches at the maximum block size. Furthermore, we present a novel constructive heuristic, which is based on the profile fitting heuristic from the literature. The proposed constructive heuristic is able to further improve the best known solutions for some larger instances in a few seconds. Parameters of the constructive heuristic and the VBIH algorithm are determined through a design of experiment approach. Extensive computational results on the Taillard’s well-known benchmark suite show that the proposed VBIH algorithm outperforms the discrete artificial bee colony algorithm, which is one of the most efficient algorithms recently in the literature. Ultimately, 52 out of the 150 best known solutions are further improved with substantial margins.
A hybrid approach for minimizing makespan in permutation flowshop scheduling
DEFF Research Database (Denmark)
Govindan, Kannan; Balasundaram, R.; Baskar, N.
2017-01-01
This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan (total completion time). To solve scheduling problems, a combination of Decision Tree (DT) and Scatter Search (SS) algorithms are used. Initially, the DT is used to generate a seed...... solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification...
Directory of Open Access Journals (Sweden)
Pongpan Nakkaew
2016-06-01
Full Text Available In manufacturing process where efficiency is crucial in order to remain competitive, flowshop is a common configuration in which machines are arranged in series and products are produced through the stages one by one. In certain production processes, the machines are frequently configured in the way that each production stage may contain multiple processing units in parallel or hybrid. Moreover, along with precedent conditions, the sequence dependent setup times may exist. Finally, in case there is no buffer, a machine is said to be blocked if the next stage to handle its output is being occupied. Such NP-Hard problem, referred as Blocking Hybrid Flowshop Scheduling Problem with Sequence Dependent Setup/Changeover Times, is usually not possible to find the best exact solution to satisfy optimization objectives such as minimization of the overall production time. Thus, it is usually solved by approximate algorithms such as metaheuristics. In this paper, we investigate comparatively the effectiveness of the two approaches: a Genetic Algorithm (GA and an Artificial Bee Colony (ABC algorithm. GA is inspired by the process of natural selection. ABC, in the same manner, resembles the way types of bees perform specific functions and work collectively to find their foods by means of division of labor. Additionally, we apply an algorithm to improve the GA and ABC algorithms so that they can take advantage of parallel processing resources of modern multiple core processors while eliminate the need for screening the optimal parameters of both algorithms in advance.
FLOWSHOP SCHEDULING USING A NETWORK APPROACH ...
African Journals Online (AJOL)
eobe
problems considered were solved using LINGO 7.0. The present technique has been shown to be very effective and efficient efficient. Keywords: Flow shop, network, linear programming, makespan, Gantt Chart, LINGO. 1. INTRODUCTION. INTRODUCTION. INTRODUCTION. The traditional flow shop scheduling problem, in.
Heuristic for Stochastic Online Flowshop Problem with Preemption Penalties
Directory of Open Access Journals (Sweden)
Mohammad Bayat
2013-01-01
Full Text Available The deterministic flowshop model is one of the most widely studied problems; whereas its stochastic equivalent has remained a challenge. Furthermore, the preemptive online stochastic flowshop problem has received much less attention, and most of the previous researches have considered a nonpreemptive version. Moreover, little attention has been devoted to the problems where a certain time penalty is incurred when preemption is allowed. This paper examines the preemptive stochastic online flowshop with the objective of minimizing the expected makespan. All the jobs arrive overtime, which means that the existence and the parameters of each job are unknown until its release date. The processing time of the jobs is stochastic and actual processing time is unknown until completion of the job. A heuristic procedure for this problem is presented, which is applicable whenever the job processing times are characterized by their means and standard deviation. The performance of the proposed heuristic method is explored using some numerical examples.
Flowshop Scheduling Using a Network Approach | Oladeinde ...
African Journals Online (AJOL)
In this paper, a network based formulation of a permutation flow shop problem is presented. Two nuances of flow shop problems with different levels of complexity are solved using different approaches to the linear programming formulation. Key flow shop parameters inclosing makespan of the flow shop problems were ...
A Method of Flow-Shop Re-Scheduling Dealing with Variation of Productive Capacity
Directory of Open Access Journals (Sweden)
Kenzo KURIHARA
2005-02-01
Full Text Available We can make optimum scheduling results using various methods that are proposed by many researchers. However, it is very difficult to process the works on time without delaying the schedule. There are two major causes that disturb the planned optimum schedules; they are (1the variation of productive capacity, and (2the variation of products' quantities themselves. In this paper, we deal with the former variation, or productive capacities, at flow-shop works. When production machines in a shop go out of order at flow-shops, we cannot continue to operate the productions and we have to stop the production line. To the contrary, we can continue to operate the shops even if some workers absent themselves. Of course, in this case, the production capacities become lower, because workers need to move from a machine to another to overcome the shortage of workers and some shops cannot be operated because of the worker shortage. We developed a new re-scheduling method based on Branch-and Bound method. We proposed an equation for calculating the lower bound for our Branch-and Bound method in a practical time. Some evaluation experiments are done using practical data of real flow-shop works. We compared our results with those of another simple scheduling method, and we confirmed the total production time of our result is shorter than that of another method by 4%.
Hsiao, Ming-Chih; Su, Ling-Huey
2018-02-01
This research addresses the problem of scheduling hybrid machine types, in which one type is a two-machine flowshop and another type is a single machine. A job is either processed on the two-machine flowshop or on the single machine. The objective is to determine a production schedule for all jobs so as to minimize the makespan. The problem is NP-hard since the two parallel machines problem was proved to be NP-hard. Simulated annealing algorithms are developed to solve the problem optimally. A mixed integer programming (MIP) is developed and used to evaluate the performance for two SAs. Computational experiments demonstrate the efficiency of the simulated annealing algorithms, the quality of the simulated annealing algorithms will also be reported.
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.
The triangle scheduling problem
Dürr, Christoph; Hanzálek, Zdeněk; Konrad, Christian; Seddik, Yasmina; Sitters, R.A.; Vásquez, Óscar C.; Woeginger, Gerhard
2017-01-01
This paper introduces a novel scheduling problem, where jobs occupy a triangular shape on the time line. This problem is motivated by scheduling jobs with different criticality levels. A measure is introduced, namely the binary tree ratio. It is shown that the Greedy algorithm solves the problem to
Literature Review on the Hybrid Flow Shop Scheduling Problem with Unrelated Parallel Machines
Directory of Open Access Journals (Sweden)
Eliana Marcela Peña Tibaduiza
2017-01-01
Full Text Available Context: The flow shop hybrid problem with unrelated parallel machines has been less studied in the academia compared to the flow shop hybrid with identical processors. For this reason, there are few reports about the kind of application of this problem in industries. Method: A literature review of the state of the art on flow-shop scheduling problem was conducted by collecting and analyzing academic papers on several scientific databases. For this aim, a search query was constructed using keywords defining the problem and checking the inclusion of unrelated parallel machines in such definition; as a result, 50 papers were finally selected for this study. Results: A classification of the problem according to the characteristics of the production system was performed, also solution methods, constraints and objective functions commonly used are presented. Conclusions: An increasing trend is observed in studies of flow shop with multiple stages, but few are based on industry case-studies.
Routing and scheduling problems
DEFF Research Database (Denmark)
Reinhardt, Line Blander
be that the objects routed have an availability time window and a delivery time window or that locations on the path have a service time window. When routing moving transportation objects such as vehicles and vessels schedules are made in connection with the routing. Such schedules represent the time for the presence......In today’s globalized society, transport contributes to our daily life in many different ways. The production of the parts for a shelf ready product may take place on several continents and our travel between home and work, vacation travel and business trips has increased in distance the last...... couple of decades. To deliver competitive service and price, transportation today needs to be cost effective. A company requiring for things to be shipped will aim at having the freight shipped as cheaply as possible while often satisfying certain time constraints. For the transportation company...
The Vessel Schedule Recovery Problem
DEFF Research Database (Denmark)
Brouer, Berit Dangaard; Plum, Christian Edinger Munk; Vaaben, Bo
Maritime transportation is the backbone of world trade and is accountable for around 3% of the worlds CO2 emissions. We present the Vessel Schedule Recovery Problem (VSRP) to evaluate a given disruption scenario and to select a recovery action balancing the trade off between increased bunker...
Constraint-based scheduling applying constraint programming to scheduling problems
Baptiste, Philippe; Nuijten, Wim
2001-01-01
Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...
Santosa, B.; Siswanto, N.; Fiqihesa
2018-04-01
This paper proposes a discrete Particle Swam Optimization (PSO) to solve limited-wait hybrid flowshop scheduing problem with multi objectives. Flow shop schedulimg represents the condition when several machines are arranged in series and each job must be processed at each machine with same sequence. The objective functions are minimizing completion time (makespan), total tardiness time, and total machine idle time. Flow shop scheduling model always grows to cope with the real production system accurately. Since flow shop scheduling is a NP-Hard problem then the most suitable method to solve is metaheuristics. One of metaheuristics algorithm is Particle Swarm Optimization (PSO), an algorithm which is based on the behavior of a swarm. Originally, PSO was intended to solve continuous optimization problems. Since flow shop scheduling is a discrete optimization problem, then, we need to modify PSO to fit the problem. The modification is done by using probability transition matrix mechanism. While to handle multi objectives problem, we use Pareto Optimal (MPSO). The results of MPSO is better than the PSO because the MPSO solution set produced higher probability to find the optimal solution. Besides the MPSO solution set is closer to the optimal solution
International Nuclear Information System (INIS)
Azadeh, A.; Maleki Shoja, B.; Ghanei, S.; Sheikhalishahi, M.
2015-01-01
This research investigates a redundancy-scheduling optimization problem for a multi-state series parallel system. The system is a flow shop manufacturing system with multi-state machines. Each manufacturing machine may have different performance rates including perfect performance, decreased performance and complete failure. Moreover, warm standby redundancy is considered for the redundancy allocation problem. Three objectives are considered for the problem: (1) minimizing system purchasing cost, (2) minimizing makespan, and (3) maximizing system reliability. Universal generating function is employed to evaluate system performance and overall reliability of the system. Since the problem is in the NP-hard class of combinatorial problems, genetic algorithm (GA) is used to find optimal/near optimal solutions. Different test problems are generated to evaluate the effectiveness and efficiency of proposed approach and compared to simulated annealing optimization method. The results show the proposed approach is capable of finding optimal/near optimal solution within a very reasonable time. - Highlights: • A redundancy-scheduling optimization problem for a multi-state series parallel system. • A flow shop with multi-state machines and warm standby redundancy. • Objectives are to optimize system purchasing cost, makespan and reliability. • Different test problems are generated and evaluated by a unique genetic algorithm. • It locates optimal/near optimal solution within a very reasonable time
Integrated network design and scheduling problems :
Energy Technology Data Exchange (ETDEWEB)
Nurre, Sarah G.; Carlson, Jeffrey J.
2014-01-01
We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.
Routing Flow-Shop with Buffers and Ready Times – Comparison of Selected Solution Algorithms
Józefczyk Jerzy; Markowski Michał; Balgabaeva Ljazat
2014-01-01
This article extends the former results concerning the routing flow-shop problem to minimize the makespan on the case with buffers, non-zero ready times and different speeds of machines. The corresponding combinatorial optimization problem is formulated. The exact as well as four heuristic solution algorithms are presented. The branch and bound approach is applied for the former one. The heuristic algorithms employ known constructive idea proposed for the former version of the problem as well...
The Home Care Crew Scheduling Problem
DEFF Research Database (Denmark)
Rasmussen, Matias Sevel; Justesen, Tor
In the Home Care Crew Scheduling Problem (HCCSP) a staff of caretakers has to be assigned a number of visits, such that the total number of assigned visits is maximised. The visits have different locations and positions in time, and travelling time and time windows must be respected. The challenge...
Multitasking Scheduling Problems with Deterioration Effect
Directory of Open Access Journals (Sweden)
Zhanguo Zhu
2017-01-01
Full Text Available Multitasking scheduling problems with a deterioration effect incurred by coexisting behavioral phenomena in human-related scheduling systems including deteriorating task processing times and deteriorating rate-modifying activity (DRMA of human operators are addressed. Under the assumption of this problem, the processing of a selected task suffers from the joint effect of available but unfinished waiting tasks, the position-dependent deterioration of task processing time, and the DRMA of human operators. Traditionally, these issues have been considered separately; herein, we address their integration. We propose optimal algorithms to solve the problems to minimize makespan and the total absolute differences in completion time, respectively. Based on the analysis, some special cases and extensions are also discussed.
Genetic Algorithms for Satellite Scheduling Problems
Directory of Open Access Journals (Sweden)
Fatos Xhafa
2012-01-01
Full Text Available Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.
Directory of Open Access Journals (Sweden)
Huixin Tian
2016-01-01
Full Text Available Different from most researches focused on the single objective hybrid flowshop scheduling (HFS problem, this paper investigates a biobjective HFS problem with sequence dependent setup time. The two objectives are the minimization of total weighted tardiness and the total setup time. To efficiently solve this problem, a Pareto-based adaptive biobjective variable neighborhood search (PABOVNS is developed. In the proposed PABOVNS, a solution is denoted as a sequence of all jobs and a decoding procedure is presented to obtain the corresponding complete schedule. In addition, the proposed PABOVNS has three major features that can guarantee a good balance of exploration and exploitation. First, an adaptive selection strategy of neighborhoods is proposed to automatically select the most promising neighborhood instead of the sequential selection strategy of canonical VNS. Second, a two phase multiobjective local search based on neighborhood search and path relinking is designed for each selected neighborhood. Third, an external archive with diversity maintenance is adopted to store the nondominated solutions and at the same time provide initial solutions for the local search. Computational results based on randomly generated instances show that the PABOVNS is efficient and even superior to some other powerful multiobjective algorithms in the literature.
Optimal pre-scheduling of problem remappings
Nicol, David M.; Saltz, Joel H.
1987-01-01
A large class of scientific computational problems can be characterized as a sequence of steps where a significant amount of computation occurs each step, but the work performed at each step is not necessarily identical. Two good examples of this type of computation are: (1) regridding methods which change the problem discretization during the course of the computation, and (2) methods for solving sparse triangular systems of linear equations. Recent work has investigated a means of mapping such computations onto parallel processors; the method defines a family of static mappings with differing degrees of importance placed on the conflicting goals of good load balance and low communication/synchronization overhead. The performance tradeoffs are controllable by adjusting the parameters of the mapping method. To achieve good performance it may be necessary to dynamically change these parameters at run-time, but such changes can impose additional costs. If the computation's behavior can be determined prior to its execution, it can be possible to construct an optimal parameter schedule using a low-order-polynomial-time dynamic programming algorithm. Since the latter can be expensive, the performance is studied of the effect of a linear-time scheduling heuristic on one of the model problems, and it is shown to be effective and nearly optimal.
Directory of Open Access Journals (Sweden)
Sang-Oh Shim
2017-12-01
Full Text Available Scheduling problems for the sustainability of manufacturing firms in the era of the fourth industrial revolution is addressed in this research. In terms of open innovation, innovative production scheduling can be defined as scheduling using big data, cyber-physical systems, internet of things, cloud computing, mobile network, and so on. In this environment, one of the most important things is to develop an innovative scheduling algorithm for the sustainability of manufacturing firms. In this research, a flexible flowshop scheduling problem is considered with the properties of sequence-dependent setup and different process plans for jobs. In a flexible flowshop, there are serial workstations with multiple pieces of equipment that are able to process multiple lots simultaneously. Since the scheduling in this workshop is known to be extremely difficult, it is important to devise an efficient and effective scheduling algorithm. In this research, a heuristic algorithm is proposed based on a few dispatching rules and economic lot size model with the objective of minimizing total tardiness of orders. For the purposes of performance evaluation, a simulation study is conducted on randomly generated problem instances. The results imply that our proposed method outperforms the existing ones, and greatly enhances the sustainability of manufacturing firms.
Solving a chemical batch scheduling problem by local search
Brucker, P.; Hurink, Johann L.
1999-01-01
A chemical batch scheduling problem is modelled in two different ways as a discrete optimization problem. Both models are used to solve the batch scheduling problem in a two-phase tabu search procedure. The method is tested on real-world data.
The Liner Shipping Routing and Scheduling Problem Under Environmental Considerations
DEFF Research Database (Denmark)
Dithmer, Philip; Reinhardt, Line Blander; Kontovas, Christos
2017-01-01
This paper deals with the Liner Shipping Routing and Scheduling Problem (LSRSP), which consists of designing the time schedule for a vessel to visit a fixed set of ports while minimizing costs. We extend the classical problem to include the external cost of ship air emissions and we present some ...
Dynamic Scheduling for Cloud Reliability using Transportation Problem
P. Balasubramanie; S. K. Senthil Kumar
2012-01-01
Problem statement: Cloud is purely a dynamic environment and the existing task scheduling algorithms are mostly static and considered various parameters like time, cost, make span, speed, scalability, throughput, resource utilization, scheduling success rate and so on. Available scheduling algorithms are mostly heuristic in nature and more complex, time consuming and does not consider reliability and availability of the cloud computing environment. Therefore there is a need to implement a sch...
A DIFFERENTIAL EVOLUTION ALGORITHM DEVELOPED FOR A NURSE SCHEDULING PROBLEM
Directory of Open Access Journals (Sweden)
Shahnazari-Shahrezaei, P.
2012-11-01
Full Text Available Nurse scheduling is a type of manpower allocation problem that tries to satisfy hospital managers objectives and nurses preferences as much as possible by generating fair shift schedules. This paper presents a nurse scheduling problem based on a real case study, and proposes two meta-heuristics a differential evolution algorithm (DE and a greedy randomised adaptive search procedure (GRASP to solve it. To investigate the efficiency of the proposed algorithms, two problems are solved. Furthermore, some comparison metrics are applied to examine the reliability of the proposed algorithms. The computational results in this paper show that the proposed DE outperforms the GRASP.
Handling Deafness Problem of Scheduled Multi-Channel Polling MACs
Jiang, Fulong; Liu, Hao; Shi, Longxing
Combining scheduled channel polling with channel diversity is a promising way for a MAC protocol to achieve high energy efficiency and performance under both light and heavy traffic conditions. However, the deafness problem may cancel out the benefit of channel diversity. In this paper, we first investigate the deafness problem of scheduled multi-channel polling MACs with experiments. Then we propose and evaluate two schemes to handle the deafness problem. Our experiment shows that deafness is a significant reason for performance degradation in scheduled multi-channel polling MACs. A proper scheme should be chosen depending on the traffic pattern and the design objective.
Solving large scale crew scheduling problems by using iterative partitioning
E.J.W. Abbink (Erwin)
2008-01-01
textabstractThis paper deals with large-scale crew scheduling problems arising at the Dutch railway operator, Netherlands Railways (NS). NS operates about 30,000 trains a week. All these trains need a driver and a certain number of conductors. No available crew scheduling algorithm can solve such
Solving University Scheduling Problem Using Hybrid Approach
Directory of Open Access Journals (Sweden)
Aftab Ahmed Shaikh
2011-10-01
Full Text Available In universities scheduling curriculum activity is an essential job. Primarily, scheduling is a distribution of limited resources under interrelated constraints. The set of hard constraints demand the highest priority and should not to be violated at any cost, while the maximum soft constraints satisfaction mounts the quality scale of solution. In this research paper, a novel bisected approach is introduced that is comprisesd of GA (Genetic Algorithm as well as Backtracking Recursive Search. The employed technique deals with both hard and soft constraints successively. The first phase decisively is focused over elimination of all the hard constraints bounded violations and eventually produces partial solution for subsequent step. The second phase is supposed to draw the best possible solution on the search space. Promising results are obtained by implementation on the real dataset. The key points of the research approach are to get assurance of hard constraints removal from the dataset and minimizing computational time for GA by initializing pre-processed set of chromosomes.
Hybrid IP/CP Methods for Solving Sports Scheduling Problems
DEFF Research Database (Denmark)
Rasmussen, Rasmus Vinther
2006-01-01
The field of sports scheduling comprises a challenging research areawith a great variety of hard combinatorial optimization problems andchallenging practical applications. This dissertation gives acomprehensive survey of the area and a number of new contributionsare presented. First a general sol...
The application of artificial intelligence to astronomical scheduling problems
Johnston, Mark D.
1992-01-01
Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike
Analysis of Feeder Bus Network Design and Scheduling Problems
Directory of Open Access Journals (Sweden)
Mohammad Hadi Almasi
2014-01-01
Full Text Available A growing concern for public transit is its inability to shift passenger’s mode from private to public transport. In order to overcome this problem, a more developed feeder bus network and matched schedules will play important roles. The present paper aims to review some of the studies performed on Feeder Bus Network Design and Scheduling Problem (FNDSP based on three distinctive parts of the FNDSP setup, namely, problem description, problem characteristics, and solution approaches. The problems consist of different subproblems including data preparation, feeder bus network design, route generation, and feeder bus scheduling. Subsequently, descriptive analysis and classification of previous works are presented to highlight the main characteristics and solution methods. Finally, some of the issues and trends for future research are identified. This paper is targeted at dealing with the FNDSP to exhibit strategic and tactical goals and also contributes to the unification of the field which might be a useful complement to the few existing reviews.
Analysis of feeder bus network design and scheduling problems.
Almasi, Mohammad Hadi; Mirzapour Mounes, Sina; Koting, Suhana; Karim, Mohamed Rehan
2014-01-01
A growing concern for public transit is its inability to shift passenger's mode from private to public transport. In order to overcome this problem, a more developed feeder bus network and matched schedules will play important roles. The present paper aims to review some of the studies performed on Feeder Bus Network Design and Scheduling Problem (FNDSP) based on three distinctive parts of the FNDSP setup, namely, problem description, problem characteristics, and solution approaches. The problems consist of different subproblems including data preparation, feeder bus network design, route generation, and feeder bus scheduling. Subsequently, descriptive analysis and classification of previous works are presented to highlight the main characteristics and solution methods. Finally, some of the issues and trends for future research are identified. This paper is targeted at dealing with the FNDSP to exhibit strategic and tactical goals and also contributes to the unification of the field which might be a useful complement to the few existing reviews.
The Home Care Crew Scheduling Problem:
DEFF Research Database (Denmark)
Rasmussen, Matias Sevel; Justesen, Tor; Dohn, Anders
branch-and-price solution algorithm, as this method has previously given solid results for classical vehicle routing problems. Temporal dependencies are modelled as generalised precedence constraints and enforced through the branching. We introduce a novel visit clustering approach based on the soft...
The Application of Artificial Intelligence to Astronomical Scheduling Problems
Johnston, Mark D.
1993-01-01
As artificial intelligence (AI) technology has moved from the research laboratory into more and more widespread use, one of the leading applications in astronomy has been to high-profile observation scheduling. The Spike scheduling system was developed by the Space Telescope Science Institute (STScI) for the purpose of long-range scheduling of Hubble Space Telescope (HST). Spike has been in daily operational use at STScI since well before HST launch in April 1990. The system has also been adapted to schedule other missions: one of these missions (EUVE) is currently operational, while another (ASTRO-D) will be launched in February 1993. Some other future space astronomy missions (XTE, SWAS, and AXAF) are making tentative plans to use Spike. Spike has proven to be a powerful and flexible scheduling framework with applicability to a wide variety of problems.
DEFF Research Database (Denmark)
Hansen, Anders Dohn; Clausen, Jens
This paper presents the Steel Plate Storage Yard Crane Scheduling Problem. The task is to generate a schedule for two gantry cranes sharing tracks. The schedule must comply with a number of constraints and at the same time be cost efficient. We propose some ideas for a two stage planning/scheduli....../scheduling solution approach to the problem.......This paper presents the Steel Plate Storage Yard Crane Scheduling Problem. The task is to generate a schedule for two gantry cranes sharing tracks. The schedule must comply with a number of constraints and at the same time be cost efficient. We propose some ideas for a two stage planning...
Efficient mixed integer programming models for family scheduling problems
Directory of Open Access Journals (Sweden)
Meng-Ye Lin
Full Text Available This paper proposes several mixed integer programming models which incorporate optimal sequence properties into the models, to solve single machine family scheduling problems. The objectives are total weighted completion time and maximum lateness, respectively. Experiment results indicate that there are remarkable improvements in computational efficiency when optimal sequence properties are included in the models. For the total weighted completion time problems, the best model solves all of the problems up to 30-jobs within 5 s, all 50-job problems within 4 min and about 1/3 of the 75-job to 100-job problems within 1 h. For maximum lateness problems, the best model solves almost all the problems up to 30-jobs within 11 min and around half of the 50-job to 100-job problems within 1 h. Keywords: Family scheduling, Sequence independent setup, Total weighted completion time, Maximum lateness
Periodic Heterogeneous Vehicle Routing Problem With Driver Scheduling
Mardiana Panggabean, Ellis; Mawengkang, Herman; Azis, Zainal; Filia Sari, Rina
2018-01-01
The paper develops a model for the optimal management of logistic delivery of a given commodity. The company has different type of vehicles with different capacity to deliver the commodity for customers. The problem is then called Periodic Heterogeneous Vehicle Routing Problem (PHVRP). The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We propose a combined approach of heuristic algorithm and exact method to solve the problem.
The Simultaneous Vehicle Scheduling and Passenger Service Problem
DEFF Research Database (Denmark)
Petersen, Hanne Løhmann; Larsen, Allan; Madsen, Oli B.G.
Passengers using public transport systems often experience waiting times when transferring between two scheduled services. We propose a planning approach which seeks to obtain a favorable trade-off between the conflicting objectives passenger service and operating cost, by allowing some moderate...... modifications of the timetable during the vehicle scheduling phase. This planning approach is referred to as the Simultaneous Vehicle Scheduling and Passenger Service Problem (SVSPSP). The SVSPSP is solved using a large neighbourhood search metaheuristic. The proposed framework is tested on data inspired...
Optimization of the solution of the problem of scheduling theory ...
African Journals Online (AJOL)
This article describes the genetic algorithm used to solve the problem related to the scheduling theory. A large number of different methods is described in the scientific literature. The main issue that faced the problem in question is that it is necessary to search the optimal solution in a large search space for the set of ...
Directory of Open Access Journals (Sweden)
Arun Gupta
2016-07-01
Full Text Available The flow-shop scheduling problem (FSP has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed. Some of these techniques offer excellent effectiveness and efficiency at the expense of substantial implementation efforts and being extremely complicated. This paper brings out the application of a Multi-Criteria Decision Making (MCDM method known as techniques for order preference by similarity to an ideal solution (TOPSIS using different weighting schemes in flow-shop environment. The objective function is identification of a job sequence which in turn would have minimum makespan (total job completion time. The application of the proposed method to flow shop scheduling is presented and explained with a numerical example. The results of the proposed TOPSIS based technique of FSP are also compared on the basis of some benchmark problems and found compatible with the results obtained from other standard procedures.
Scheduling and order acceptance for the customised stochastic lot scheduling problem
van Foreest, Nicky D.; Wijngaard, Jacob; van der Vaart, Taco
2010-01-01
This paper develops and analyses several customer order acceptance policies to achieve high bottleneck utilisation for the customised stochastic lot scheduling problem (CSLSP) with large setups and strict order due dates. To compare the policies, simulation is used as the main tool, due to the
Classification of Ship Routing and Scheduling Problems in Liner Shipping
DEFF Research Database (Denmark)
Kjeldsen, Karina Hjortshøj
2011-01-01
This article provides a classification scheme for ship routing and scheduling problems in liner shipping in line with the current and future operational conditions of the liner shipping industry. Based on the classification, the literature is divided into groups whose main characteristics...... are described. The literature within each group is reviewed, much of it for the first time....
A stochastic approach for solving the operating room scheduling problem
Molina-Pariente, Jose M.; Hans, Elias W.; Framinan, Jose M.
2016-01-01
We address a stochastic operating room scheduling problem which consists of assigning an intervention date and operating room to surgeries on the waiting list, minimizing the under- and overtime costs of the operating rooms, and the cost of exceeding the capacity constraints of the system.
Solving Large Scale Crew Scheduling Problems in Practice
E.J.W. Abbink (Erwin); L. Albino; T.A.B. Dollevoet (Twan); D. Huisman (Dennis); J. Roussado; R.L. Saldanha
2010-01-01
textabstractThis paper deals with large-scale crew scheduling problems arising at the Dutch railway operator, Netherlands Railways (NS). NS operates about 30,000 trains a week. All these trains need a driver and a certain number of guards. Some labor rules restrict the duties of a certain crew base
The GBT Dynamic Scheduling System: Scheduling Applications of the Knapsack Problem and Sudoku
Sessoms, E.; Clark, M.; Marganian, P.; McCarty, M.; Shelton, A.
2009-09-01
We applied algorithmic approaches to both theoretical and practical aspects of scheduling the Robert C. Byrd Green Bank Telescope (GBT). When using a theoretical approach to scheduling, assigning a numerical value, or score, to a telescope period is only half of the problem. The other half consists of using the score to determine the best global arrangement of the telescope periods in order to maximize the scientific throughput of the telescope. The naive brute-force approach of trying all possible schedules is too computationally expensive. Instead we applied a well-studied approach from operations research, known as dynamic programming. Specifically, we found the so-called ``knapsack'' algorithm to be a good fit to this problem. On the other hand, we cannot actually achieve maximum theoretical efficiency due to many practical constraints on telescope scheduling. The most severe practical constraints are fixed periods that must be scheduled at a specific date and time regardless of possible score and windowed periods that must be scheduled in regular, recurring intervals. The primary difficulty in scheduling fixed and windowed sessions is that they have the potential to conflict and even to generate irresolvable conflicts (double booking). In working on this problem, we realized it shared many characteristics with the game of Sudoku. In Sudoku, there are many possible arrangements of the recurring numbers 1 through 9 (telescope sessions). Some of these are fixed (the hints) and the others must live in windows (distinct groups having one instance each of each digit). Sudoku puzzles are solved algorithmically using a heuristic-guided brute-force search. We followed a similar approach. A full brute-force search is, again, too computationally expensive, but we found ways to restrict the search enough to make it feasible. We used a number of heuristics but found the largest gains came from partitioning the problem into distinct subsets than can each be scheduled
Novel Approaches for Some Stochastic and Deterministic Scheduling Problems
Liao, Lingrui
2011-01-01
In this dissertation, we develop novel approaches to independently address two issues that are commonly encountered in machine scheduling problems: uncertainty of problem parameters (in particular, due to job processing times), and batching of jobs for processing on capacitated machines. Our approach to address the uncertainty issue regards the indeterminate parameters as random variables, and explicitly considers the resulting variability of a performance measure. To incorporate variabili...
Extended precedence preservative crossover for job shop scheduling problems
Ong, Chung Sin; Moin, Noor Hasnah; Omar, Mohd
2013-04-01
Job shop scheduling problems (JSSP) is one of difficult combinatorial scheduling problems. A wide range of genetic algorithms based on the two parents crossover have been applied to solve the problem but multi parents (more than two parents) crossover in solving the JSSP is still lacking. This paper proposes the extended precedence preservative crossover (EPPX) which uses multi parents for recombination in the genetic algorithms. EPPX is a variation of the precedence preservative crossover (PPX) which is one of the crossovers that perform well to find the solutions for the JSSP. EPPX is based on a vector to determine the gene selected in recombination for the next generation. Legalization of children (offspring) can be eliminated due to the JSSP representation encoded by using permutation with repetition that guarantees the feasibility of chromosomes. The simulations are performed on a set of benchmarks from the literatures and the results are compared to ensure the sustainability of multi parents recombination in solving the JSSP.
Solving a manpower scheduling problem for airline catering using metaheuristics
DEFF Research Database (Denmark)
Ho, Sin C.; Leung, Janny M. Y.
2010-01-01
We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take-off. Jobs (flights) must...... be serviced within a given time-window by a team consisting of a driver and loader. Each driver/loader has the skills to service some, but not all, of the airline/aircraft/ configuration of the jobs. Given the jobs to be serviced and the roster of workers for each shift, the problem is to form teams...
GENETIC ALGORITHM APPLICATION FOR MULTI-CRITERIA SCHEDULING PROBLEM
Directory of Open Access Journals (Sweden)
I. V. Arkhipov
2015-05-01
Full Text Available The paper describes mathematical model and method of task solution for defining an enterprise work performance schedule. Two-stage feedstock processing is supposed to exist at the enterprise. At the first stage the sawing process into semimanufactured products is done. The second stage (finished products manufacturing stage includes durable processing of obtained semimanufactured products at one of the interchangeable work centers. The sawing process into semimanufactured products is carried out according to a plan, developed in advance and in compliance with technological charts. Scheduling consists of separate cutting calculation and planning of all feedstock cutting with the aim of the most effective specification task performance based on available reserves. Following the cutting plan, an enterprise work performance schedule is created. This schedule consists of the cutting sequence with volume, start and end time, and plan for loading of after-treatment. The solution to this problem becomes more involved due to the necessity of taking into account all features, limitations and parameters of process equipment, as well as of raw material and production orders. Special method based on genetic algorithm has been proposed for handling the problem. The algorithm has been tested on several different realproduction plans. Its efficiency estimation is given. The software systemimplemented on the proposed algorithm has been tested on real operating data of several sawmills. Reduction of machine idle time and incomplete production decrease has been confirmed by the enterprise specialists.
The Simultaneous Vehicle Scheduling and Passenger Service Problem
DEFF Research Database (Denmark)
Petersen, Hanne Løhmann; Larsen, Allan; Madsen, Oli B.G.
2013-01-01
Passengers using public transport systems often experience waiting times when transferring between two scheduled services. In this paper we propose a planning approach that seeks to obtain a favourable trade-off between the two contrasting objectives, passenger service and operating cost, by modi...... by the express-bus network in the Greater Copenhagen area. The results are encouraging and indicate a potential decrease of passenger transfer waiting times in the network of up to 20%, with the vehicle scheduling costs remaining mostly unaffected.......Passengers using public transport systems often experience waiting times when transferring between two scheduled services. In this paper we propose a planning approach that seeks to obtain a favourable trade-off between the two contrasting objectives, passenger service and operating cost......, by modifying the timetable. The planning approach is referred to as the simultaneous vehicle scheduling and passenger service problem (SVSPSP). The SVSPSP is modelled as an integer programming problem and solved using a large neighborhood search metaheuristic. The proposed framework is tested on data inspired...
Global Optimization of Nonlinear Blend-Scheduling Problems
Directory of Open Access Journals (Sweden)
Pedro A. Castillo Castillo
2017-04-01
Full Text Available The scheduling of gasoline-blending operations is an important problem in the oil refining industry. This problem not only exhibits the combinatorial nature that is intrinsic to scheduling problems, but also non-convex nonlinear behavior, due to the blending of various materials with different quality properties. In this work, a global optimization algorithm is proposed to solve a previously published continuous-time mixed-integer nonlinear scheduling model for gasoline blending. The model includes blend recipe optimization, the distribution problem, and several important operational features and constraints. The algorithm employs piecewise McCormick relaxation (PMCR and normalized multiparametric disaggregation technique (NMDT to compute estimates of the global optimum. These techniques partition the domain of one of the variables in a bilinear term and generate convex relaxations for each partition. By increasing the number of partitions and reducing the domain of the variables, the algorithm is able to refine the estimates of the global solution. The algorithm is compared to two commercial global solvers and two heuristic methods by solving four examples from the literature. Results show that the proposed global optimization algorithm performs on par with commercial solvers but is not as fast as heuristic approaches.
The operational flight and multi-crew scheduling problem
Directory of Open Access Journals (Sweden)
Stojković Mirela
2005-01-01
Full Text Available This paper introduces a new kind of operational multi-crew scheduling problem which consists in simultaneously modifying, as necessary, the existing flight departure times and planned individual work days (duties for the set of crew members, while respecting predefined aircraft itineraries. The splitting of a planned crew is allowed during a day of operations, where it is more important to cover a flight than to keep planned crew members together. The objective is to cover a maximum number of flights from a day of operations while minimizing changes in both the flight schedule and the next-day planned duties for the considered crew members. A new type of the same flight departure time constraints is introduced. They ensure that a flight which belongs to several personalized duties, where the number of duties is equal to the number of crew members assigned to the flight, will have the same departure time in each of these duties. Two variants of the problem are considered. The first variant allows covering of flights by less than the planned number of crew members, while the second one requires covering of flights by a complete crew. The problem is mathematically formulated as an integer nonlinear multi-commodity network flow model with time windows and supplementary constraints. The optimal solution approach is based on Dantzig-Wolfe decomposition/column generation embedded into a branch-and-bound scheme. The resulting computational times on commercial-size problems are very good. Our new simultaneous approach produces solutions whose quality is far better than that of the traditional sequential approach where the flight schedule has been changed first and then input as a fixed data to the crew scheduling problem.
Artificial immune algorithm for multi-depot vehicle scheduling problems
Wu, Zhongyi; Wang, Donggen; Xia, Linyuan; Chen, Xiaoling
2008-10-01
In the fast-developing logistics and supply chain management fields, one of the key problems in the decision support system is that how to arrange, for a lot of customers and suppliers, the supplier-to-customer assignment and produce a detailed supply schedule under a set of constraints. Solutions to the multi-depot vehicle scheduling problems (MDVRP) help in solving this problem in case of transportation applications. The objective of the MDVSP is to minimize the total distance covered by all vehicles, which can be considered as delivery costs or time consumption. The MDVSP is one of nondeterministic polynomial-time hard (NP-hard) problem which cannot be solved to optimality within polynomial bounded computational time. Many different approaches have been developed to tackle MDVSP, such as exact algorithm (EA), one-stage approach (OSA), two-phase heuristic method (TPHM), tabu search algorithm (TSA), genetic algorithm (GA) and hierarchical multiplex structure (HIMS). Most of the methods mentioned above are time consuming and have high risk to result in local optimum. In this paper, a new search algorithm is proposed to solve MDVSP based on Artificial Immune Systems (AIS), which are inspirited by vertebrate immune systems. The proposed AIS algorithm is tested with 30 customers and 6 vehicles located in 3 depots. Experimental results show that the artificial immune system algorithm is an effective and efficient method for solving MDVSP problems.
Flexible ship loading problem with transfer vehicle assignment and scheduling
DEFF Research Database (Denmark)
Iris, Çağatay; Christensen, Jonas; Pacino, Dario
2018-01-01
This paper presents the flexible containership loading problem for seaport container terminals. The integrated management of loading operations, planning of the transport vehicles to use and their scheduling is what we define as the Flexible Ship Loading Problem (FSLP). The flexibility comes from...... a cooperative agreement between the terminal operator and the liner shipping company, specifying that the terminal has the right to decide which specific container to load for each slot obeying the class-based stowage plan received from the liner. We formulate a mathematical model for the problem. Then we...... present various modelling enhancements and a mathematical model to obtain strong lower bounds. We also propose a heuristic algorithm to solve the problem. It is shown that enhancements improve the performance of formulation significantly, and the heuristic efficiently generates high-quality solutions...
Diversity Controlling Genetic Algorithm for Order Acceptance and Scheduling Problem
Directory of Open Access Journals (Sweden)
Cheng Chen
2014-01-01
Full Text Available Selection and scheduling are an important topic in production systems. To tackle the order acceptance and scheduling problem on a single machine with release dates, tardiness penalty, and sequence-dependent setup times, in this paper a diversity controlling genetic algorithm (DCGA is proposed, in which a diversified population is maintained during the whole search process through survival selection considering both the fitness and the diversity of individuals. To measure the similarity between individuals, a modified Hamming distance without considering the unaccepted orders in the chromosome is adopted. The proposed DCGA was validated on 1500 benchmark instances with up to 100 orders. Compared with the state-of-the-art algorithms, the experimental results show that DCGA improves the solution quality obtained significantly, in terms of the deviation from upper bound.
Heuristic Method for Decision-Making in Common Scheduling Problems
Directory of Open Access Journals (Sweden)
Edyta Kucharska
2017-10-01
Full Text Available The aim of the paper is to present a heuristic method for decision-making regarding an NP-hard scheduling problem with limitations related to tasks and the resources dependent on the current state of the process. The presented approach is based on the algebraic-logical meta-model (ALMM, which enables making collective decisions in successive process stages, not separately for individual objects or executors. Moreover, taking into account the limitations of the problem, it involves constructing only an acceptable solution and significantly reduces the amount of calculations. A general algorithm based on the presented method is composed of the following elements: preliminary analysis of the problem, techniques for the choice of decision at a given state, the pruning non-perspective trajectory, selection technique of the initial state for the trajectory final part, and the trajectory generation parameters modification. The paper includes applications of the presented approach to scheduling problems on unrelated parallel machines with a deadline and machine setup time dependent on the process state, where the relationship between tasks is defined by the graph. The article also presents the results of computational experiments.
On the Integrated Job Scheduling and Constrained Network Routing Problem
DEFF Research Database (Denmark)
Gamst, Mette
This paper examines the NP-hard problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job demands a number of resources, which must be sent to the executing machine via constrained paths. Furthermore, two resource demand...... transmissions cannot use the same edge in the same time period. An exact solution approach based on Dantzig-Wolfe decomposition is proposed along with several heuristics. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results...
Directory of Open Access Journals (Sweden)
I Gede Agus Widyadana
2002-01-01
Full Text Available The research is focused on comparing Genetics algorithm and Simulated Annealing in the term of performa and processing time. The main purpose is to find out performance both of the algorithm to solve minimizing makespan and total flowtime in a particular flowshop system. Performances of the algorithms are found by simulating problems with variation of jobs and machines combination. The result show the Simulated Annealing is much better than the Genetics up to 90%. The Genetics, however, only had score in processing time, but the trend that plotted suggest that in problems with lots of jobs and lots of machines, the Simulated Annealing will run much faster than the Genetics. Abstract in Bahasa Indonesia : Penelitian ini difokuskan pada pembandingan algoritma Genetika dan Simulated Annealing ditinjau dari aspek performa dan waktu proses. Tujuannya adalah untuk melihat kemampuan dua algoritma tersebut untuk menyelesaikan problem-problem penjadwalan flow shop dengan kriteria minimasi makespan dan total flowtime. Kemampuan kedua algoritma tersebut dilihat dengan melakukan simulasi yang dilakukan pada kombinasi-kombinasi job dan mesin yang berbeda-beda. Hasil simulasi menunjukan algoritma Simulated Annealing lebih unggul dari algoritma Genetika hingga 90%, algoritma Genetika hanya unggul pada waktu proses saja, namun dengan tren waktu proses yang terbentuk, diyakini pada problem dengan kombinasi job dan mesin yang banyak, algoritma Simulated Annealing dapat lebih cepat daripada algoritma Genetika. Kata kunci: Algoritma Genetika, Simulated Annealing, flow shop, makespan, total flowtime.
JIT single machine scheduling problem with periodic preventive maintenance
Shahriari, Mohammadreza; Shoja, Naghi; Zade, Amir Ebrahimi; Barak, Sasan; Sharifi, Mani
2016-09-01
This article investigates a JIT single machine scheduling problem with a periodic preventive maintenance. Also to maintain the quality of the products, there is a limitation on the maximum number of allowable jobs in each period. The proposed bi-objective mixed integer model minimizes total earliness-tardiness and makespan simultaneously. Due to the computational complexity of the problem, multi-objective particle swarm optimization (MOPSO) algorithm is implemented. Also, as well as MOPSO, two other optimization algorithms are used for comparing the results. Eventually, Taguchi method with metrics analysis is presented to tune the algorithms' parameters and a multiple criterion decision making technique based on the technique for order of preference by similarity to ideal solution is applied to choose the best algorithm. Comparison results confirmed the supremacy of MOPSO to the other algorithms.
Routing Flow-Shop with Buffers and Ready Times – Comparison of Selected Solution Algorithms
Directory of Open Access Journals (Sweden)
Józefczyk Jerzy
2014-12-01
Full Text Available This article extends the former results concerning the routing flow-shop problem to minimize the makespan on the case with buffers, non-zero ready times and different speeds of machines. The corresponding combinatorial optimization problem is formulated. The exact as well as four heuristic solution algorithms are presented. The branch and bound approach is applied for the former one. The heuristic algorithms employ known constructive idea proposed for the former version of the problem as well as the Tabu Search metaheuristics. Moreover, the improvement procedure is proposed to enhance the quality of both heuristic algorithms. The conducted simulation experiments allow evaluating all algorithms. Firstly, the heuristic algorithms are compared with the exact one for small instances of the problem in terms of the criterion and execution times. Then, for larger instances, the heuristic algorithms are mutually compared. The case study regarding the maintenance of software products, given in the final part of the paper, illustrates the possibility to apply the results for real-world manufacturing systems.
A Fast Estimator of Performance with Respect to the Design Parameters of Self Re-Entrant Flowshops
Waqas, U.; Geilen, M.; Stuijk, S.; Pinxten, J.V.; Basten, T.; Somers, L.; Corporaal, H.
2016-01-01
Self re-entrant flowshops consist of machines which process jobs several times. They are found in applications like TFT-LCD assembly, LED manufacturing and industrial printing. The structure of a self re-entrant flowshop influences its performance. To get better performance while reducing costs a
Intelligent discrete particle swarm optimization for multiprocessor task scheduling problem
Directory of Open Access Journals (Sweden)
S Sarathambekai
2017-03-01
Full Text Available Discrete particle swarm optimization is one of the most recently developed population-based meta-heuristic optimization algorithm in swarm intelligence that can be used in any discrete optimization problems. This article presents a discrete particle swarm optimization algorithm to efficiently schedule the tasks in the heterogeneous multiprocessor systems. All the optimization algorithms share a common algorithmic step, namely population initialization. It plays a significant role because it can affect the convergence speed and also the quality of the final solution. The random initialization is the most commonly used method in majority of the evolutionary algorithms to generate solutions in the initial population. The initial good quality solutions can facilitate the algorithm to locate the optimal solution or else it may prevent the algorithm from finding the optimal solution. Intelligence should be incorporated to generate the initial population in order to avoid the premature convergence. This article presents a discrete particle swarm optimization algorithm, which incorporates opposition-based technique to generate initial population and greedy algorithm to balance the load of the processors. Make span, flow time, and reliability cost are three different measures used to evaluate the efficiency of the proposed discrete particle swarm optimization algorithm for scheduling independent tasks in distributed systems. Computational simulations are done based on a set of benchmark instances to assess the performance of the proposed algorithm.
Genetic algorithm to solve the problems of lectures and practicums scheduling
Syahputra, M. F.; Apriani, R.; Sawaluddin; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.
2018-02-01
Generally, the scheduling process is done manually. However, this method has a low accuracy level, along with possibilities that a scheduled process collides with another scheduled process. When doing theory class and practicum timetable scheduling process, there are numerous problems, such as lecturer teaching schedule collision, schedule collision with another schedule, practicum lesson schedules that collides with theory class, and the number of classrooms available. In this research, genetic algorithm is implemented to perform theory class and practicum timetable scheduling process. The algorithm will be used to process the data containing lists of lecturers, courses, and class rooms, obtained from information technology department at University of Sumatera Utara. The result of scheduling process using genetic algorithm is the most optimal timetable that conforms to available time slots, class rooms, courses, and lecturer schedules.
The school bus routing and scheduling problem with transfers.
Bögl, Michael; Doerner, Karl F; Parragh, Sophie N
2015-03-01
In this article, we study the school bus routing and scheduling problem with transfers arising in the field of nonperiodic public transportation systems. It deals with the transportation of pupils from home to their school in the morning taking the possibility that pupils may change buses into account. Allowing transfers has several consequences. On the one hand, it allows more flexibility in the bus network structure and can, therefore, help to reduce operating costs. On the other hand, transfers have an impact on the service level: the perceived service quality is lower due to the existence of transfers; however, at the same time, user ride times may be reduced and, thus, transfers may also have a positive impact on service quality. The main objective is the minimization of the total operating costs. We develop a heuristic solution framework to solve this problem and compare it with two solution concepts that do not consider transfers. The impact of transfers on the service level in terms of time loss (or user ride time) and the number of transfers is analyzed. Our results show that allowing transfers reduces total operating costs significantly while average and maximum user ride times are comparable to solutions without transfers. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 65(2), 180-203 2015.
Stochastic Optimization for Network-Constrained Power System Scheduling Problem
Directory of Open Access Journals (Sweden)
D. F. Teshome
2015-01-01
Full Text Available The stochastic nature of demand and wind generation has a considerable effect on solving the scheduling problem of a modern power system. Network constraints such as power flow equations and transmission capacities also need to be considered for a comprehensive approach to model renewable energy integration and analyze generation system flexibility. Firstly, this paper accounts for the stochastic inputs in such a way that the uncertainties are modeled as normally distributed forecast errors. The forecast errors are then superimposed on the outputs of load and wind forecasting tools. Secondly, it efficiently models the network constraints and tests an iterative algorithm and a piecewise linear approximation for representing transmission losses in mixed integer linear programming (MILP. It also integrates load shedding according to priority factors set by the system operator. Moreover, the different interactions among stochastic programming, network constraints, and prioritized load shedding are thoroughly investigated in the paper. The stochastic model is tested on a power system adopted from Jeju Island, South Korea. Results demonstrate the impact of wind speed variability and network constraints on the flexibility of the generation system. Further analysis shows the effect of loss modeling approaches on total cost, accuracy, computational time, and memory requirement.
Solving the job-shop scheduling problem optimally by dynamic programming
Gromicho Dos Santos, J.A.; van Hoorn, J.J.; Saldanha da Gama, F.; Timmer, G.T.
2012-01-01
Scheduling problems received substantial attention during the last decennia. The job-shop problem is a very important scheduling problem, which is NP-hard in the strong sense and with well-known benchmark instances of relatively small size which attest the practical difficulty in solving it. The
Research on remanufacturing scheduling problem based on critical chain management
Cui, Y.; Guan, Z.; He, C.; Yue, L.
2017-06-01
Remanufacturing is the recycling process of waste products as “as good as new products”, compared with materials recycling, remanufacturing represents a higher form of recycling. The typical structure of remanufacturing system consists of three parts: disassembly workshop, remanufacturing workshop and assembly workshop. However, the management of production planning and control activities can differ greatly from management activities in traditional manufacturing. Scheduling in a remanufacturing environment is more complex and the scheduler must deal with more uncertainty than in a traditional manufacturing environment. In order to properly schedule in a remanufacturing environment the schedule must be able to cope with several complicating factors which increase variability. This paper introduced and discussed seven complicating characteristics that require significant changes in production planning and control activities, in order to provide a new method for remanufacturing production scheduling system.
Performance comparison of some evolutionary algorithms on job shop scheduling problems
Mishra, S. K.; Rao, C. S. P.
2016-09-01
Job Shop Scheduling as a state space search problem belonging to NP-hard category due to its complexity and combinational explosion of states. Several naturally inspire evolutionary methods have been developed to solve Job Shop Scheduling Problems. In this paper the evolutionary methods namely Particles Swarm Optimization, Artificial Intelligence, Invasive Weed Optimization, Bacterial Foraging Optimization, Music Based Harmony Search Algorithms are applied and find tuned to model and solve Job Shop Scheduling Problems. To compare about 250 Bench Mark instances have been used to evaluate the performance of these algorithms. The capabilities of each these algorithms in solving Job Shop Scheduling Problems are outlined.
A New Lagrangian Relaxation Method Considering Previous Hour Scheduling for Unit Commitment Problem
Khorasani, H.; Rashidinejad, M.; Purakbari-Kasmaie, M.; Abdollahi, A.
2009-08-01
Generation scheduling is a crucial challenge in power systems especially under new environment of liberalization of electricity industry. A new Lagrangian relaxation method for unit commitment (UC) has been presented for solving generation scheduling problem. This paper focuses on the economical aspect of UC problem, while the previous hour scheduling as a very important issue is studied. In this paper generation scheduling of present hour has been conducted by considering the previous hour scheduling. The impacts of hot/cold start-up cost have been taken in to account in this paper. Case studies and numerical analysis presents significant outcomes while it demonstrates the effectiveness of the proposed method.
Advancing Air Force Scheduling through Modeling Problem Topologies
2006-08-03
much better starting point for their negotiations. 4 We received seven days of actual AFSCN data circa 1993 from Dr. James Moore of AFIT and five days...Conference on Automated Planning and Scheduling, Whistler , British Columbia, June. • J.P. Watson, A.E. Howe and L.D. Whitley. 2003. “An Analysis of...Scheduling, Whistler , CA, June 4, 2004. A. Howe, “Leap Before You Look: An Effective Strategy for Oversubscribed Scheduling” at Nineteenth National
Directory of Open Access Journals (Sweden)
S. Khavvaji
2011-01-01
Full Text Available Background and aims Shiftwork that affects diverse aspects of human life is arranged in various schedules, each has its own advantages and disadvantages. This study was carried out with the objectives of determination of common 12-hour shift schedules in petrochemical plants, comparison of shift work health-related problems among employees working in different shift schedules and recommendation of appropriate shift schedule for decrement of related health problems. methodsThis cross-sectional study was conducted at 8 petrochemical plants in Asalooyeh region related to National Petrochemical Industries in which 12-hour shift schedules were applied. Study population consisted of 549 shift workers with age mean of 29.83±5.75 years. Data on personal details, shift schedule and adverse health effects of shiftwork (i.e. gastrointestinal, cardiovascular, musculoskeletal, psychological, sleep etc. disorders were collected by anonymous questionnaire. Results Among 549 studied shift employees, 39.6% worked in 4N-7D-3N-7Res (4night-7day-3night-7rest, 29.1% in 7N-7D-7Res and 31.3% in 7D-7N-7Res schedules. Statistical comparison showed that the prevalence of h ealth problems such as gastrointestinal, cardiovascular and musculoskeletal disorders among 7D-7N-7Res schedule shiftworkers were significantly higher than that of other schedules (p0.05. Conclusion Prevalence of gastrointestinal, cardiovascular and musculoskeletal disorders in all schedules were high, but odds ratios of all problems among 7D-7N-7Res schedule shiftworkers were significantly more than those of the shiftworkers of the other schedules. This schedule should, therefore, be changed to decrease related-health problems. Fixed 14D/14N schedule may be an appropriate substitution.
Comparison of heuristic approaches for the multiple depot vehicle scheduling problem
A.S. Pepin; G. Desaulniers (Guy); A. Hertz (Alain); D. Huisman (Dennis)
2006-01-01
textabstractGiven a set of timetabled tasks, the multi-depot vehicle scheduling problem is a well-known problem that consists of determining least-cost schedules for vehicles assigned to several depots such that each task is accomplished exactly once by a vehicle. In this paper, we propose to
A branch-and-price algorithm for a hierarchical crew scheduling problem
Faneyte, Diego B.C.; Spieksma, Frits C.R.; Woeginger, Gerhard
2002-01-01
We describe a real-life problem arising at a crane rental company. This problem is a generalization of the basic crew scheduling problem given in Mingozzi et al. [18] and Beasley and Cao [6]. We formulate the problem as an integer programming problem and establish ties with the integer
Electric power scheduling - A distributed problem-solving approach
Mellor, Pamela A.; Dolce, James L.; Krupp, Joseph C.
1990-01-01
Space Station Freedom's power system, along with the spacecraft's other subsystems, needs to carefully conserve its resources and yet strive to maximize overall Station productivity. Due to Freedom's distributed design, each subsystem must work cooperatively within the Station community. There is a need for a scheduling tool which will preserve this distributed structure, allow each subsystem the latitude to satisfy its own constraints, and preserve individual value systems while maintaining Station-wide integrity.
Programación de operaciones en dos etapas para un flowshop multiperíodo no tradicional
Directory of Open Access Journals (Sweden)
Juan Pablo Orejuela-Cabrera
2014-01-01
Full Text Available En el presente documento se desarrolla una metodología de dos etapas para programar las operaciones en un flowshop multiperíodo, en éste se tienen trabajos que aunque que se deben terminar en la misma ventana de tiempo, unos son de entrega inmediata y deben programarse en el momento más temprano de la ventana, y otros en el momento más tardío, de tal modo que se minimice su tiempo de permanencia en el sistema. Se plantea una estrategia de descomposición temporal para el problema multiperíodo, en la que se combina la programación estructurada con la programación lineal, de tal modo que para cada periodo se corren dos fases compuestas de dos modelos matemáticos que programan los trabajos según su prioridad. La metodología planteada se valida en un problema de programación de trabajos en la industria de alimentos concentrados, obteniéndose como resultado un scheduling para cada periodo que satisface los requerimientos de los productos de entrega inmediata y los de entrega en el momento más tardío. Del tal modo que se minimiza para los primeros el inventario de producto en proceso y para los segundos el tiempo de no permanencia en el sistema.
The Green Ship Routing and Scheduling Problem (GSRSP): A conceptual approach
DEFF Research Database (Denmark)
Kontovas, Christos A.
2014-01-01
to 'green' routing and scheduling and outlines some possible ways to incorporate the air emissions dimension into maritime transportation OR. The main contribution of this note vis-a-vis the state of the art is that it conceptualizes the formulation of the 'Green Ship Routing and Scheduling Problem' (GSRSP...
Electric power scheduling: A distributed problem-solving approach
Mellor, Pamela A.; Dolce, James L.; Krupp, Joseph C.
1990-01-01
Space Station Freedom's power system, along with the spacecraft's other subsystems, needs to carefully conserve its resources and yet strive to maximize overall Station productivity. Due to Freedom's distributed design, each subsystem must work cooperatively within the Station community. There is a need for a scheduling tool which will preserve this distributed structure, allow each subsystem the latitude to satisfy its own constraints, and preserve individual value systems while maintaining Station-wide integrity. The value-driven free-market economic model is such a tool.
Solving scheduling tournament problems using a new version of CLONALG
Pérez-Cáceres, Leslie; Riff, María Cristina
2015-01-01
The travelling tournament problem (TTP) is an important and well-known problem within the collective sports research community. The problem is NP-hard which makes difficult finding quality solution in short amount of time. Recently a new kind of TTP has been proposed 'The Relaxed Travelling Tournament Problem'. This version of the problem allows teams to have some days off during the tournament. In this paper, we propose an immune algorithm that is able to solve both problem versions. The algorithm uses moves which are based on the team home/away patterns. One of these moves has been specially designed for the relaxed travel tournament instances. We have tested the algorithm using well-known problem benchmarks and the results obtained are very encouraging.
National Research Council Canada - National Science Library
Crino, John
2002-01-01
.... This dissertation applies and extends some of Colletti's (1999) seminal work in group theory and metaheuristics in order to solve the theater distribution vehicle routing and scheduling problem (TDVRSP...
A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan
Rameshkumar, K.; Rajendran, C.
2018-02-01
In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.
Optimising the Slab Yard Planning and Crane Scheduling Problem using a two-stage heuristic
DEFF Research Database (Denmark)
Hansen, Anders Dohn; Clausen, Jens
2010-01-01
In this paper, we present the Slab Yard Planning and Crane Scheduling Problem. The problem has its origin in steel production facilities with a large throughput. A slab yard is used as a buffer for slabs that are needed in the upcoming production. Slabs are transported by cranes and the problem...
A Column Generation Approach for Solving the Patient Admission Scheduling Problem
DEFF Research Database (Denmark)
Range, Troels Martin; Lusby, Richard Martin; Larsen, Jesper
This paper addresses the Patient Admission Scheduling (PAS) problem. The PAS problem deals with assigning elective patients to beds, satisfying a number of soft and hard constraints. The problem can be seen as part of the functions of hospital management at an operational level. There exists...
Directory of Open Access Journals (Sweden)
Behnam Barzegar
2012-01-01
Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.
DEFF Research Database (Denmark)
Gamst, M.
2014-01-01
an optical network. The problem is formulated as an IP problem and is shown to be NP-hard. An exact solution approach based on Dantzig-Wolfe decomposition is proposed. Also, several heuristic methods are developed by combining heuristics for the job scheduling problem and for the constrained network routing...... problem. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results show that solving the integrated job scheduling and constrained network routing problem to optimality is very difficult. The exact solution approach performs......This paper examines the problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job has a certain demand, which must be sent to the executing machine via constrained paths. A job cannot start before all its demands have...
Optimal infrastructure maintenance scheduling problem under budget uncertainty.
2010-05-01
This research addresses a general class of infrastructure asset management problems. Infrastructure : agencies usually face budget uncertainties that will eventually lead to suboptimal planning if : maintenance decisions are made without taking the u...
a genetic algorithm in a schedule problem with special constraints
Directory of Open Access Journals (Sweden)
Carlos Pérez de la Cruz
2011-07-01
Full Text Available Ramírez (2001 introduced the generalized robust coloring problem (GRCP, this problem lets solve timetabling problems which considers constraints such as: two events can not be assigned at the same time and there must be at least d days between two events.The GRCP deals with a robust coloring for a given graph with a fixed number of colors, not necessarily the chromatic number and considers the distance between colors as the penalization of complementary edges. It was shown that the problem is NP-complete, so it is necessary to use approximate methods to find good solutions in a reasonable time. This paper presents a hybrid of a genetic algorithm with a local search for cases of 30-120 hours per week; it is shown that for some cases the found solution is optimal and in other cases the solutions are very promising.
Elkhyari, Abdallah; Guéret, Christelle; Jussien, Narendra
2003-01-01
Timetabling problems have been studied a lot over the last decade. Due to the complexity and the variety of such problems, most work concern static problems in which activities to schedule and resources are known in advance, and constraints are fixed. However, every timetabling problem is subject to unexpected events (consider for example, for university timetabling problems, a missing teacher, or a slide projector breakdoawn). In such a situation, one has to quickly build a new solution whic...
Directory of Open Access Journals (Sweden)
Yongyi Shou
2014-01-01
Full Text Available A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.
Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs
Directory of Open Access Journals (Sweden)
Wenming Cheng
2012-01-01
Full Text Available In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.
A branch-and-price algorithm for the long-term home care scheduling problem
DEFF Research Database (Denmark)
Gamst, Mette; Jensen, Thomas Sejr
2012-01-01
In several countries, home care is provided for certain citizens living at home. The long-term home care scheduling problem is to generate work plans such that a high quality of service is maintained, the work hours of the employees are respected, and the overall cost is kept as low as possible. We...... propose a branchand-price algorithm for the long-term home care scheduling problem. The pricing problem generates a one-day plan for an employee, and the master problem merges the plans with respect to regularity constraints. The method is capable of generating plans with up to 44 visits during one week....
Ship Block Transportation Scheduling Problem Based on Greedy Algorithm
Directory of Open Access Journals (Sweden)
Chong Wang
2016-05-01
Full Text Available Ship block transportation problems are crucial issues to address in reducing the construction cost and improving the productivity of shipyards. Shipyards aim to maximize the workload balance of transporters with time constraint such that all blocks should be transported during the planning horizon. This process leads to three types of penalty time: empty transporter travel time, delay time, and tardy time. This study aims to minimize the sum of the penalty time. First, this study presents the problem of ship block transportation with the generalization of the block transportation restriction on the multi-type transporter. Second, the problem is transformed into the classical traveling salesman problem and assignment problem through a reasonable model simplification and by adding a virtual node to the proposed directed graph. Then, a heuristic algorithm based on greedy algorithm is proposed to assign blocks to available transporters and sequencing blocks for each transporter simultaneously. Finally, the numerical experiment method is used to validate the model, and its result shows that the proposed algorithm is effective in realizing the efficient use of the transporters in shipyards. Numerical simulation results demonstrate the promising application of the proposed method to efficiently improve the utilization of transporters and to reduce the cost of ship block logistics for shipyards.
A review on application of neural networks and fuzzy logic to solve hydrothermal scheduling problem
International Nuclear Information System (INIS)
Haroon, S.; Malik, T.N.; Zafar, S.
2014-01-01
Electrical power system is highly complicated having hydro and thermal mix with large number of machines. To reduce power production cost, hydro and thermal resources are mixed. Hydrothermal scheduling is the optimal coordination of hydro and thermal plants to meet the system load demand at minimum possible operational cost while satisfying the system constraints. Hydrothermal scheduling is dynamic, large scale, non-linear and non-convex optimization problem. The classical techniques have failed in solving such problem. Artificial Intelligence Tools based techniques are used now a day to solve this complex optimization problem because of their no requirements on the nature of the problem. The aim of this research paper is to provide a comprehensive survey of literature related to both Artificial Neural Network (ANN) and Fuzzy Logic (FL) as effective optimization algorithms for the hydrothermal scheduling problem. The outcomes along with the merits and demerits of individual techniques are also discussed. (author)
Wang, Zhaocai; Ji, Zuwen; Wang, Xiaoming; Wu, Tunhua; Huang, Wei
2017-12-01
As a promising approach to solve the computationally intractable problem, the method based on DNA computing is an emerging research area including mathematics, computer science and molecular biology. The task scheduling problem, as a well-known NP-complete problem, arranges n jobs to m individuals and finds the minimum execution time of last finished individual. In this paper, we use a biologically inspired computational model and describe a new parallel algorithm to solve the task scheduling problem by basic DNA molecular operations. In turn, we skillfully design flexible length DNA strands to represent elements of the allocation matrix, take appropriate biological experiment operations and get solutions of the task scheduling problem in proper length range with less than O(n 2 ) time complexity. Copyright © 2017. Published by Elsevier B.V.
Scheduling Internal Audit Activities: A Stochastic Combinatorial Optimization Problem
Rossi, R.; Tarim, S.A.; Hnich, B.; Prestwich, S.; Karacaer, S.
2010-01-01
The problem of finding the optimal timing of audit activities within an organisation has been addressed by many researchers. We propose a stochastic programming formulation with Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) certainty-equivalent models. In experiments
Cyclic flow shop scheduling problem with two-machine cells
Directory of Open Access Journals (Sweden)
Bożejko Wojciech
2017-06-01
Full Text Available In the paper a variant of cyclic production with setups and two-machine cell is considered. One of the stages of the problem solving consists of assigning each operation to the machine on which it will be carried out. The total number of such assignments is exponential. We propose a polynomial time algorithm finding the optimal operations to machines assignment.
Exact methods for time constrained routing and related scheduling problems
DEFF Research Database (Denmark)
Kohl, Niklas
1995-01-01
, Desrosiers and Solomon (1992) who were able to solve 50 of the problems, and Halse (1992) who solved 33. The main reason for the success of the algorithm is the exploitation of valid inequalities. The increase in speed of computers since 1992 play only a minor role. In the last part of the dissertation...... application of valid inequalities on the VRPTW. The algorithm developed represents a major step forward in terms of computational ability to solve the VRPTW. Solutions to a large number of previously unsolved problems are reported....... can be improved further by incorporation of valid inequalities . We show how this can be done computationally and we introduce a number of valid inequalities for the VRPTW. Finally we present a number of strategies, primarily branch-and-bound, to obtain integer solutions. In the computational part...
An Improved Genetic Algorithm for Single-Machine Inverse Scheduling Problem
Directory of Open Access Journals (Sweden)
Jianhui Mou
2014-01-01
Full Text Available The goal of the scheduling is to arrange operations on suitable machines with optimal sequence for corresponding objectives. In order to meet market requirements, scheduling systems must own enough flexibility against uncertain events. These events can change production status or processing parameters, even causing the original schedule to no longer be optimal or even to be infeasible. Traditional scheduling strategies, however, cannot cope with these cases. Therefore, a new idea of scheduling called inverse scheduling has been proposed. In this paper, the inverse scheduling with weighted completion time (SMISP is considered in a single-machine shop environment. In this paper, an improved genetic algorithm (IGA with a local searching strategy is proposed. To improve the performance of IGA, efficient encoding scheme, fitness evaluation mechanism, feasible initialization methods, and a local search procedure have been employed in the paper. Because of the local improving method, the proposed IGA can balance its exploration ability and exploitation ability. We adopt 27 instances to verify the effectiveness of the proposed algorithm. The experimental results illustrated that the proposed algorithm can generate satisfactory solutions. This approach also has been applied to solve the scheduling problem in the real Chinese shipyard and can bring some benefits.
Discrete Optimization Model for Vehicle Routing Problem with Scheduling Side Cosntraints
Juliandri, Dedy; Mawengkang, Herman; Bu'ulolo, F.
2018-01-01
Vehicle Routing Problem (VRP) is an important element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a hard combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve the demands a set of customers It is required that these vehicles return to the depot after serving customers’ demand. The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the overall costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model.
A column generation approach for solving the patient admission scheduling problem
DEFF Research Database (Denmark)
Range, Troels Martin; Lusby, Richard Martin; Larsen, Jesper
2014-01-01
This paper addresses the Patient Admission Scheduling (PAS) problem. The PAS problem entails assigning elective patients to beds, while satisfying a number of hard constraints and as many soft constraints as is possible, and arises at all planning levels for hospital management. There exist a few...
A duty-period-based formulation of the airline crew scheduling problem
Energy Technology Data Exchange (ETDEWEB)
Hoffman, K.
1994-12-31
We present a new formulation of the airline crew scheduling problem that explicitly considers the duty periods. We suggest an algorithm for solving the formulation by a column generation approach with branch-and-bound. Computational results are reported for a number of test problems.
Heuristics methods for the flow shop scheduling problem with separated setup times
Directory of Open Access Journals (Sweden)
Marcelo Seido Nagano
2012-06-01
Full Text Available This paper deals with the permutation flow shop scheduling problem with separated machine setup times. As a result of an investigation on the problem characteristics, four heuristics methods are proposed with procedures of the construction sequencing solution by an analogy with the asymmetric traveling salesman problem with the objective of minimizing makespan. Experimental results show that one of the new heuristics methods proposed provide high quality solutions in comparisons with the evaluated methods considered in the literature.
Directory of Open Access Journals (Sweden)
Yahong Zheng
2014-05-01
Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.
A new genetic algorithm for flexible job-shop scheduling problems
International Nuclear Information System (INIS)
Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia
2015-01-01
Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.
A new genetic algorithm for flexible job-shop scheduling problems
Energy Technology Data Exchange (ETDEWEB)
Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia [University of Batna, Batna (Algeria)
2015-03-15
Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.
A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems
Thammano, Arit; Teekeng, Wannaporn
2015-05-01
The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.
Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems
Directory of Open Access Journals (Sweden)
Muhammad Kamal Amjad
2018-01-01
Full Text Available Flexible Job Shop Scheduling Problem (FJSSP is an extension of the classical Job Shop Scheduling Problem (JSSP. The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA have gained the most popularity. Keeping in view this aspect, this article presents a comprehensive literature review of the FJSSPs solved using the GA. The survey is further extended by the inclusion of the hybrid GA (hGA techniques used in the solution of the problem. This review will give readers an insight into use of certain parameters in their future research along with future research directions.
Resource-constrained project scheduling problem: review of past and recent developments
Directory of Open Access Journals (Sweden)
Farhad Habibi
2018-01-01
Full Text Available The project scheduling problem is both practically and theoretically of paramount importance. From the practical perspective, improvement of project scheduling as a critical part of project management process can lead to successful project completion and significantly decrease of the relevant costs. From the theoretical perspective, project scheduling is regarded as one of the in-teresting optimization issues, which has attracted the attention of many researchers in the area of operations research. Therefore, the project scheduling issue has been significantly evaluated over time and has been developed from various aspects. In this research, the topics related to Re-source-Constrained Project Scheduling Problem (RCPSP are reviewed, recent developments in this field are evaluated, and the results are presented for future studies. In this regard, first, the standard problem of RCPSP is expressed and related developments are presented from four as-pects of resources, characteristics of activities, type of objective functions, and availability level of information. Following that, details about 216 articles conducted on RCPSP during 1980-2017 are expressed. At the end, in line with the statistics obtained from the evaluation of previ-ous articles, suggestions are made for the future studies in order to help the development of new issues in this area.
Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm
Piroozfard, Hamed; Wong, Kuan Yew
2015-05-01
The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.
Cyclic delivery-scheduling problem with synchronization of vehicles\\' arrivals at logistic centers
Directory of Open Access Journals (Sweden)
Katarzyna Zofia Gdowska
2015-12-01
Full Text Available Background: In this paper a cyclic delivery-scheduling problem with vehicles serving fixed routes is presented. Each vehicle is assigned to one route to which some manufacturers' warehouses and logistics centers belong. A vehicle is to be loaded at a manufacturer's warehouse, then to deliver goods to a logistics center and may be also loaded there with other goods and to transport them to the next node along the route. One logistic center belongs to several routes, so the goods delivered by one vehicle may continue their journey by another truck. For every route the frequency of the vehicle is fixed and known. The objective here is to obtain such synchronization of vehicles arrivals in logistics centers, so that it is possible to organize their arrivals in repeatable blocks. Methods: In the paper the cyclic delivery-scheduling problem with vehicles serving fixed routes is formulated as a MIP model. Due to the fixed routes and desirable synchronization of vehicles arrivals in shared points this problem seems to be similar to the public transit network timetabling problem. Because of that the model presented here was based on a model dedicated to the public transit network timetabling problem, where optimization criterion was to maximize synchronization of vehicles' arrivals at the shared nodes. Results: Mixed integer programming model was employed for solving several cases of cyclic delivery-scheduling problem with vehicles serving fixed routes. Computational experiments are reported and obtained results are presented. Conclusions: The mixed integer programming model for the cyclic delivery-scheduling problem with synchronization of vehicles arrivals at logistic centers presented in this paper can be utilized for generating schedules for a group of vehicles serving fixed long routes. It may result in reducing total operational cost related to this group of vehicles as well as in reducing the goods travel time from the place of origin to their
Comparison of heuristics for an economic lot scheduling problem with deliberated coproduction
Directory of Open Access Journals (Sweden)
Pilar I. Vidal-Carreras
2009-12-01
Full Text Available We built on the Economic Lot Scheduling Problem Scheduling (ELSP literature by making some modifications in order to introduce new constraints which had not been thoroughly studied with a view to simulating specific real situations. Specifically, our aim is to propose and simulate different scheduling policies for a new ELSP variant: Deliberated Coproduction. This problem comprises a product system in an ELSP environment in which we may choose if more than one product can be produced on the machine at a given time. We expressly consider the option of coproducing two products whose demand is not substitutable. In order to draw conclusions, a simulation model and its results were developed in the article by employing modified Bomberger data which include two items that could be produced simultaneously.
Energy-Efficient Scheduling Problem Using an Effective Hybrid Multi-Objective Evolutionary Algorithm
Directory of Open Access Journals (Sweden)
Lvjiang Yin
2016-12-01
Full Text Available Nowadays, manufacturing enterprises face the challenge of just-in-time (JIT production and energy saving. Therefore, study of JIT production and energy consumption is necessary and important in manufacturing sectors. Moreover, energy saving can be attained by the operational method and turn off/on idle machine method, which also increases the complexity of problem solving. Thus, most researchers still focus on small scale problems with one objective: a single machine environment. However, the scheduling problem is a multi-objective optimization problem in real applications. In this paper, a single machine scheduling model with controllable processing and sequence dependence setup times is developed for minimizing the total earliness/tardiness (E/T, cost, and energy consumption simultaneously. An effective multi-objective evolutionary algorithm called local multi-objective evolutionary algorithm (LMOEA is presented to tackle this multi-objective scheduling problem. To accommodate the characteristic of the problem, a new solution representation is proposed, which can convert discrete combinational problems into continuous problems. Additionally, a multiple local search strategy with self-adaptive mechanism is introduced into the proposed algorithm to enhance the exploitation ability. The performance of the proposed algorithm is evaluated by instances with comparison to other multi-objective meta-heuristics such as Nondominated Sorting Genetic Algorithm II (NSGA-II, Strength Pareto Evolutionary Algorithm 2 (SPEA2, Multiobjective Particle Swarm Optimization (OMOPSO, and Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D. Experimental results demonstrate that the proposed LMOEA algorithm outperforms its counterparts for this kind of scheduling problems.
A basic period approach to the economic lot scheduling problem with shelf life considerations
Soman, C.A.; van Donk, D.P.; Gaalman, G.J.C.
2004-01-01
Almost all the research on the economic lot scheduling problem (ELSP) considering limited shelf life of products has assumed a common cycle approach and an unrealistic assumption of possibility of deliberately reducing the production rate. In many cases, like in food processing industry where
Solving scheduling problems by untimed model checking. The clinical chemical analyser case study
Margaria, T.; Wijs, Anton J.; Massink, M.; van de Pol, Jan Cornelis; Bortnik, Elena M.
2009-01-01
In this article, we show how scheduling problems can be modelled in untimed process algebra, by using special tick actions. A minimal-cost trace leading to a particular action, is one that minimises the number of tick steps. As a result, we can use any (timed or untimed) model checking tool to find
Directory of Open Access Journals (Sweden)
Rogério M. Branco
2016-07-01
Full Text Available This paper discusses the application of heuristic-based evolutionary technique in search for solutions concerning the dynamic job-shop scheduling problems with dependent setup times and alternate routes. With a combinatorial nature, these problems belong to an NP-hard class, with an aggravated condition when in realistic, dynamic and therefore, more complex cases than the traditional static ones. The proposed genetic algorithm executes two important functions: choose the routes using dispatching rules when forming each individual from a defined set of available machines and, also make the scheduling for each of these individuals created. The chromosome codifies a route, or the selected machines, and also an order to process the operations. In essence , each individual needs to be decoded by the scheduler to evaluate its time of completion, so the fitness function of the genetic algorithm, applying the modified Giffler and Thomson’s algorithm, obtains a scheduling of the selected routes in a given planning horizon. The scheduler considers the preparation time between operations on the machines and can manage operations exchange respecting the route and the order given by the chromosome. The best results in the evolutionary process are individuals with routes and processing orders optimized for this type of problema.
An Algorithm for the Weighted Earliness-Tardiness Unconstrained Project Scheduling Problem
Afshar Nadjafi, Behrouz; Shadrokh, Shahram
This research considers a project scheduling problem with the object of minimizing weighted earliness-tardiness penalty costs, taking into account a deadline for the project and precedence relations among the activities. An exact recursive method has been proposed for solving the basic form of this problem. We present a new depth-first branch and bound algorithm for extended form of the problem, which time value of money is taken into account by discounting the cash flows. The algorithm is extended with two bounding rules in order to reduce the size of the branch and bound tree. Finally, some test problems are solved and computational results are reported.
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem.
Chen, Xiaopan; Kong, Yunfeng; Dang, Lanxue; Hou, Yane; Ye, Xinyue
2015-01-01
As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP) and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods.
Exact and Metaheuristic Approaches for a Bi-Objective School Bus Scheduling Problem.
Directory of Open Access Journals (Sweden)
Xiaopan Chen
Full Text Available As a class of hard combinatorial optimization problems, the school bus routing problem has received considerable attention in the last decades. For a multi-school system, given the bus trips for each school, the school bus scheduling problem aims at optimizing bus schedules to serve all the trips within the school time windows. In this paper, we propose two approaches for solving the bi-objective school bus scheduling problem: an exact method of mixed integer programming (MIP and a metaheuristic method which combines simulated annealing with local search. We develop MIP formulations for homogenous and heterogeneous fleet problems respectively and solve the models by MIP solver CPLEX. The bus type-based formulation for heterogeneous fleet problem reduces the model complexity in terms of the number of decision variables and constraints. The metaheuristic method is a two-stage framework for minimizing the number of buses to be used as well as the total travel distance of buses. We evaluate the proposed MIP and the metaheuristic method on two benchmark datasets, showing that on both instances, our metaheuristic method significantly outperforms the respective state-of-the-art methods.
Multi-objective Mobile Robot Scheduling Problem with Dynamic Time Windows
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa; Steger-Jensen, Kenn
2012-01-01
This paper deals with the problem of scheduling feeding tasks of a single mobile robot which has capability of supplying parts to feeders on pro-duction lines. The performance criterion is to minimize the total traveling time of the robot and the total tardiness of the feeding tasks being scheduled......, simul-taneously. In operation, the feeders have to be replenished a number of times so as to maintain the manufacture of products during a planning horizon. A meth-od based on predefined characteristics of the feeders is presented to generate dynamic time windows of the feeding tasks which are dependent...
The TensorFlow Partitioning and Scheduling Problem: It's the Critical Path!
Mayer, Ruben; Mayer, Christian; Laich, Larissa
2017-01-01
State-of-the-art data flow systems such as TensorFlow impose iterative calculations on large graphs that need to be partitioned on heterogeneous devices such as CPUs, GPUs, and TPUs. However, partitioning can not be viewed in isolation. Each device has to select the next graph vertex to be executed, i.e., perform local scheduling decisions. Both problems, partitioning and scheduling, are NP-complete by themselves but have to be solved in combination in order to minimize overall execution time...
Minimizing the total tardiness for the tool change scheduling problem on parallel machines
Directory of Open Access Journals (Sweden)
Antonio Costa
2016-04-01
Full Text Available This paper deals with the total tardiness minimization problem in a parallel machines manufacturing environment where tool change operations have to be scheduled along with jobs. The mentioned issue belongs to the family of scheduling problems under deterministic machine availability restrictions. A new model that considers the effects of the tool wear on the quality characteristics of the worked product is proposed. Since no mathematical programming-based approach has been developed by literature so far, two distinct mixed integer linear programming models, able to schedule jobs as well as tool change activities along the provided production horizon, have been devised. The former is an adaptation of a well-known model presented by the relevant literature for the single machine scheduling problem with tool changes. The latter has been specifically developed for the issue at hand. After a theoretical analysis aimed at revealing the differences between the proposed mathematical models in terms of computational complexity, an extensive experimental campaign has been fulfilled to assess performances of the proposed methods under the CPU time viewpoint. Obtained results have been statistically analyzed through a properly arranged ANOVA analysis.
Chang, Yung-Chia; Li, Vincent C.; Chiang, Chia-Ju
2014-04-01
Make-to-order or direct-order business models that require close interaction between production and distribution activities have been adopted by many enterprises in order to be competitive in demanding markets. This article considers an integrated production and distribution scheduling problem in which jobs are first processed by one of the unrelated parallel machines and then distributed to corresponding customers by capacitated vehicles without intermediate inventory. The objective is to find a joint production and distribution schedule so that the weighted sum of total weighted job delivery time and the total distribution cost is minimized. This article presents a mathematical model for describing the problem and designs an algorithm using ant colony optimization. Computational experiments illustrate that the algorithm developed is capable of generating near-optimal solutions. The computational results also demonstrate the value of integrating production and distribution in the model for the studied problem.
The Simultaneous Vehicle Scheduling and Passenger Service Problem with Flexible Dwell Times
DEFF Research Database (Denmark)
Fonseca, Joao Filipe Paiva; Larsen, Allan; van der Hurk, Evelien
In this talk, we deal with a generalization of the well-known Vehicle Scheduling Problem(VSP) that we call Simultaneous Vehicle Scheduling and Passenger Service Problem with Flexible Dwell Times (SVSPSP-FDT). The SVSPSP-FDT generalizes the VSP because the original timetables of the trips can...... be changed (i.e., shifted and stretched) in order to minimize a new objective function that aims at minimizing the operational costs plus the waiting times of the passengers at transfer points. Contrary to most generalizations of the VSP, the SVSPSP-FDT establishes the possibility of changing trips' dwell...... times at important transfer points based on expected passenger ows. We introduce a compact mixed integer linear formulation of the SVSPSP-FDT able to address small instances. We also present a meta-heuristic approach to solve medium/large instances of the problem. The e ectiveness of the proposed...
MULTICRITERIA HYBRID FLOW SHOP SCHEDULING PROBLEM: LITERATURE REVIEW, ANALYSIS, AND FUTURE RESEARCH
Directory of Open Access Journals (Sweden)
Marcia de Fatima Morais
2014-12-01
Full Text Available This research focuses on the Hybrid Flow Shop production scheduling problem, which is one of the most difficult problems to solve. The literature points to several studies that focus the Hybrid Flow Shop scheduling problem with monocriteria functions. Despite of the fact that, many real world problems involve several objective functions, they can often compete and conflict, leading researchers to concentrate direct their efforts on the development of methods that take consider this variant into consideration. The goal of the study is to review and analyze the methods in order to solve the Hybrid Flow Shop production scheduling problem with multicriteria functions in the literature. The analyses were performed using several papers that have been published over the years, also the parallel machines types, the approach used to develop solution methods, the type of method develop, the objective function, the performance criterion adopted, and the additional constraints considered. The results of the reviewing and analysis of 46 papers showed opportunities for future research on this topic, including the following: (i use uniform and dedicated parallel machines, (ii use exact and metaheuristics approaches, (iv develop lower and uppers bounds, relations of dominance and different search strategies to improve the computational time of the exact methods, (v develop other types of metaheuristic, (vi work with anticipatory setups, and (vii add constraints faced by the production systems itself.
A 0-1 Integer Programming Model for the Course Scheduling Problem and A Case Study
Directory of Open Access Journals (Sweden)
Hakan ALTUNAY
2016-01-01
Full Text Available The course scheduling problem is one of the most common timetabling problems which are frequently encountered in all educational institutions, especially universities. This problem which is getting harder to solve day by day, means the assignment of the lessons and lecturers into the most suitable timeslots and classrooms, provided that various constraints are taken into account. These constraints peculiar to the problem are consisted due to various factors such as the characteristics and the rules of the educational institutions, preferences of lecturers, students’ requests and suggestions. In this study, a novel 0-1 integer programming model that considers preferences of lecturers is proposed for the course scheduling problem. The proposed mathematical model is also tested with a case study from Uludag University. Thus, the performance of the mathematical model can be tested and the results can be analyzed. The results of the carried out application show efficient results in preparing a course schedule that meets the preferences of the lecturers and complies with the rules of the institutions.
A hybrid algorithm for flexible job-shop scheduling problem with setup times
Directory of Open Access Journals (Sweden)
Ameni Azzouz
2017-01-01
Full Text Available Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP is a generalization of the above-mentioned problem, where each operation can be processed by a set of resources and has a processing time depending on the resource used. The FJSP problems cover two difficulties, namely, machine assignment problem and operation sequencing problem. This paper addresses the flexible job-shop scheduling problem with sequence-dependent setup times to minimize two kinds of objectives function: makespan and bi-criteria objective function. For that, we propose a hybrid algorithm based on genetic algorithm (GA and variable neighbourhood search (VNS to solve this problem. To evaluate the performance of our algorithm, we compare our results with other methods existing in literature. All the results show the superiority of our algorithm against the available ones in terms of solution quality.
Amallynda, I.; Santosa, B.
2017-11-01
This paper proposes a new generalization of the distributed parallel machine and assembly scheduling problem (DPMASP) with eligibility constraints referred to as the modified distributed parallel machine and assembly scheduling problem (MDPMASP) with eligibility constraints. Within this generalization, we assume that there are a set non-identical factories or production lines, each one with a set unrelated parallel machine with different speeds in processing them disposed to a single assembly machine in series. A set of different products that are manufactured through an assembly program of a set of components (jobs) according to the requested demand. Each product requires several kinds of jobs with different sizes. Beside that we also consider to the multi-objective problem (MOP) of minimizing mean flow time and the number of tardy products simultaneously. This is known to be NP-Hard problem, is important to practice, as the former criterions to reflect the customer's demand and manufacturer's perspective. This is a realistic and complex problem with wide range of possible solutions, we propose four simple heuristics and two metaheuristics to solve it. Various parameters of the proposed metaheuristic algorithms are discussed and calibrated by means of Taguchi technique. All proposed algorithms are tested by Matlab software. Our computational experiments indicate that the proposed problem and fourth proposed algorithms are able to be implemented and can be used to solve moderately-sized instances, and giving efficient solutions, which are close to optimum in most cases.
Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search
DEFF Research Database (Denmark)
Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan
2007-01-01
This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...
Solving a manpower scheduling problem for airline catering using tabu search
DEFF Research Database (Denmark)
Ho, Sin C.; Leung, Janny M. Y.
We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take off. Jobs (flights) must...... be serviced within a given time-window by a team consisting of a driver and a loader. Each driver/loader has the skills to service some, but not all, of the airline/aircraft/configuration of the jobs. Given the jobs to be serviced and the roster of workers for each shift, the problem is to form teams...
Buddala, Raviteja; Mahapatra, Siba Sankar
2017-11-01
Flexible flow shop (or a hybrid flow shop) scheduling problem is an extension of classical flow shop scheduling problem. In a simple flow shop configuration, a job having `g' operations is performed on `g' operation centres (stages) with each stage having only one machine. If any stage contains more than one machine for providing alternate processing facility, then the problem becomes a flexible flow shop problem (FFSP). FFSP which contains all the complexities involved in a simple flow shop and parallel machine scheduling problems is a well-known NP-hard (Non-deterministic polynomial time) problem. Owing to high computational complexity involved in solving these problems, it is not always possible to obtain an optimal solution in a reasonable computation time. To obtain near-optimal solutions in a reasonable computation time, a large variety of meta-heuristics have been proposed in the past. However, tuning algorithm-specific parameters for solving FFSP is rather tricky and time consuming. To address this limitation, teaching-learning-based optimization (TLBO) and JAYA algorithm are chosen for the study because these are not only recent meta-heuristics but they do not require tuning of algorithm-specific parameters. Although these algorithms seem to be elegant, they lose solution diversity after few iterations and get trapped at the local optima. To alleviate such drawback, a new local search procedure is proposed in this paper to improve the solution quality. Further, mutation strategy (inspired from genetic algorithm) is incorporated in the basic algorithm to maintain solution diversity in the population. Computational experiments have been conducted on standard benchmark problems to calculate makespan and computational time. It is found that the rate of convergence of TLBO is superior to JAYA. From the results, it is found that TLBO and JAYA outperform many algorithms reported in the literature and can be treated as efficient methods for solving the FFSP.
Waters, Melissa B.; Lerman, Dorothea C.; Hovanetz, Alyson N.
2009-01-01
The separate and combined effects of visual schedules and extinction plus differential reinforcement of other behavior (DRO) were evaluated to decrease transition-related problem behavior of 2 children diagnosed with autism. Visual schedules alone were ineffective in reducing problem behavior when transitioning from preferred to nonpreferred…
modeling, optimisation and analysis of re-entrant flowshop job
African Journals Online (AJOL)
HOD
constrained by number of jobs and resources availability with traditional scheduling policies of First Come First Serve. (FCFS) and the ... traditional GA schemes and operators were used together with roulette wheel algorithm without elitism in the selection process ..... [16] Tsujimura, Y., Park, S. H., Chang, I. S., & Gen, M. “An.
An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times
Directory of Open Access Journals (Sweden)
Rui Zhang
2011-09-01
Full Text Available Due to the influence of unpredictable random events, the processing time of each operation should be treated as random variables if we aim at a robust production schedule. However, compared with the extensive research on the deterministic model, the stochastic job shop scheduling problem (SJSSP has not received sufficient attention. In this paper, we propose an artificial bee colony (ABC algorithm for SJSSP with the objective of minimizing the maximum lateness (which is an index of service quality. First, we propose a performance estimate for preliminary screening of the candidate solutions. Then, the K-armed bandit model is utilized for reducing the computational burden in the exact evaluation (through Monte Carlo simulation process. Finally, the computational results on different-scale test problems validate the effectiveness and efficiency of the proposed approach.
A Model for Bus Crew Scheduling Problem with Multiple Duty Types
Directory of Open Access Journals (Sweden)
Mingming Chen
2012-01-01
Full Text Available This paper presents an approach for solving the bus crew scheduling problem which considers early, day, and late duty modes with time shift and work intensity constraints. Furthermore, the constraint with the least crew number of a certain duty (e.g., day duty has also been considered. An optimization model is formulated as a 0-1 integer programming problem to improve the efficiency of crew scheduling at the minimum expense of total idle time of crew for a circle bus line. Correspondingly, a heuristic algorithm utilizing the tabu search algorithm has been proposed to solve the model. Finally, the proposed model and algorithm are successfully tested by a case study.
Greedy and metaheuristics for the offline scheduling problem in grid computing
DEFF Research Database (Denmark)
Gamst, Mette
In grid computing a number of geographically distributed resources connected through a wide area network, are utilized as one computations unit. The NP-hard offline scheduling problem in grid computing consists of assigning jobs to resources in advance. In this paper, five greedy heuristics and two....... All heuristics solve instances with up to 2000 jobs and 1000 resources, thus the results are useful both with respect to running times and to solution values....
A Novel Joint Problem of Routing, Scheduling, and Variable-Width Channel Allocation in WMNs
Directory of Open Access Journals (Sweden)
Chun-Cheng Lin
2014-01-01
Full Text Available This paper investigates a novel joint problem of routing, scheduling, and channel allocation for single-radio multichannel wireless mesh networks in which multiple channel widths can be adjusted dynamically through a new software technology so that more concurrent transmissions and suppressed overlapping channel interference can be achieved. Although the previous works have studied this joint problem, their linear programming models for the problem were not incorporated with some delicate constraints. As a result, this paper first constructs a linear programming model with more practical concerns and then proposes a simulated annealing approach with a novel encoding mechanism, in which the configurations of multiple time slots are devised to characterize the dynamic transmission process. Experimental results show that our approach can find the same or similar solutions as the optimal solutions for smaller-scale problems and can efficiently find good-quality solutions for a variety of larger-scale problems.
Hybrid Metaheuristics for Solving a Fuzzy Single Batch-Processing Machine Scheduling Problem
Molla-Alizadeh-Zavardehi, S.; Tavakkoli-Moghaddam, R.; Lotfi, F. Hosseinzadeh
2014-01-01
This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the advantages of genetic algorithm (GA), variable neighborhood search (VNS), and simulated annealing (SA) frameworks. Besides, we propose three fuzzy earliest due date heuristics to solve the given problem. Through computational experiments with several random test problems, a robust calibration is applied on the parameters. Finally, computational results on different-scale test problems are presented to compare the proposed algorithms. PMID:24883359
Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem
Directory of Open Access Journals (Sweden)
Mohammed Al-Salem
2016-01-01
Full Text Available The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD for a set of jobs when their weights equal 1 (unweighted problem. This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithm is proposed to find approximate solutions. Through computational experiments, the heuristic algorithms’ performance is evaluated with problems up to 500 jobs.
Robust Proactive Project Scheduling Model for the Stochastic Discrete Time/Cost Trade-Off Problem
Directory of Open Access Journals (Sweden)
Hongbo Li
2015-01-01
Full Text Available We study the project budget version of the stochastic discrete time/cost trade-off problem (SDTCTP-B from the viewpoint of the robustness in the scheduling. Given the project budget and a set of activity execution modes, each with uncertain activity time and cost, the objective of the SDTCTP-B is to minimize the expected project makespan by determining each activity’s mode and starting time. By modeling the activity time and cost using interval numbers, we propose a proactive project scheduling model for the SDTCTP-B based on robust optimization theory. Our model can generate robust baseline schedules that enable a freely adjustable level of robustness. We convert our model into its robust counterpart using a form of the mixed-integer programming model. Extensive experiments are performed on a large number of randomly generated networks to validate our model. Moreover, simulation is used to investigate the trade-off between the advantages and the disadvantages of our robust proactive project scheduling model.
Directory of Open Access Journals (Sweden)
Xiuli Wu
2018-03-01
Full Text Available Renewable energy is an alternative to non-renewable energy to reduce the carbon footprint of manufacturing systems. Finding out how to make an alternative energy-efficient scheduling solution when renewable and non-renewable energy drives production is of great importance. In this paper, a multi-objective flexible flow shop scheduling problem that considers variable processing time due to renewable energy (MFFSP-VPTRE is studied. First, the optimization model of the MFFSP-VPTRE is formulated considering the periodicity of renewable energy and the limitations of energy storage capacity. Then, a hybrid non-dominated sorting genetic algorithm with variable local search (HNSGA-II is proposed to solve the MFFSP-VPTRE. An operation and machine-based encoding method is employed. A low-carbon scheduling algorithm is presented. Besides the crossover and mutation, a variable local search is used to improve the offspring’s Pareto set. The offspring and the parents are combined and those that dominate more are selected to continue evolving. Finally, two groups of experiments are carried out. The results show that the low-carbon scheduling algorithm can effectively reduce the carbon footprint under the premise of makespan optimization and the HNSGA-II outperforms the traditional NSGA-II and can solve the MFFSP-VPTRE effectively and efficiently.
A novel modeling approach for job shop scheduling problem under uncertainty
Directory of Open Access Journals (Sweden)
Behnam Beheshti Pur
2013-11-01
Full Text Available When aiming on improving efficiency and reducing cost in manufacturing environments, production scheduling can play an important role. Although a common workshop is full of uncertainties, when using mathematical programs researchers have mainly focused on deterministic problems. After briefly reviewing and discussing popular modeling approaches in the field of stochastic programming, this paper proposes a new approach based on utility theory for a certain range of problems and under some practical assumptions. Expected utility programming, as the proposed approach, will be compared with the other well-known methods and its meaningfulness and usefulness will be illustrated via a numerical examples and a real case.
Directory of Open Access Journals (Sweden)
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.
SCHEDULING PROBLEMS OF STATIONARY OBJECTS WITH THE PROCESSOR IN ONE-DIMENSIONAL ZONE
Directory of Open Access Journals (Sweden)
N. A. Dunichkina
2015-01-01
Full Text Available We consider the mathematical model in which an operating processor serves the set of the stationary objects positioned in a one-dimensional working zone. The processor performs two voyages between the uttermost points of the zone: the forward or direct one, where certain objects are served, and the return one, where remaining objects are served. Servicing of the object cannot start earlier than its ready date. The individual penalty function is assigned to every object, the function depending on the servicing completion time. Minimized criteria of schedule quality are assumed to be total service duration and total penalty. We formulate and study optimization problems with one and two criteria. Proposed algorithms are based on dynamic programming and Pareto principle, the implementations of these algorithms are demonstrated on numerical examples. We show that the algorithm for the problem of processing time minimization is polynomial, and that the problem of total penalty minimization is NP-hard. Correspondingly, the bicriteria problem with the mentioned evaluation criteria is fundamentally intractable, computational complexity of the schedule structure algorithm is exponential. The model describes the fuel supply processes to the diesel-electrical dredgers which extract non-metallic building materials (sand, gravel in large-scale areas of inland waterways. Similar models and optimization problems are important, for example, in applications like the control of satellite group refueling and regular civil aircraft refueling.The article is published in the author’s wording.
DEVELOPMENT OF A HYBRID FUZZY GENETIC ALGORITHM MODEL FOR SOLVING TRANSPORTATION SCHEDULING PROBLEM
Directory of Open Access Journals (Sweden)
H.C.W. Lau
2015-12-01
Full Text Available There has been an increasing public demand for passenger rail service in the recent times leading to a strong focus on the need for effective and efficient use of resources and managing the increasing passenger requirements, service reliability and variability by the railway management. Whilst shortening the passengers’ waiting and travelling time is important for commuter satisfaction, lowering operational costs is equally important for railway management. Hence, effective and cost optimised train scheduling based on the dynamic passenger demand is one of the main issues for passenger railway management. Although the passenger railway scheduling problem has received attention in operations research in recent years, there is limited literature investigating the adoption of practical approaches that capitalize on the merits of mathematical modeling and search algorithms for effective cost optimization. This paper develops a hybrid fuzzy logic based genetic algorithm model to solve the multi-objective passenger railway scheduling problem aiming to optimize total operational costs at a satisfactory level of customer service. This hybrid approach integrates genetic algorithm with the fuzzy logic approach which uses the fuzzy controller to determine the crossover rate and mutation rate in genetic algorithm approach in the optimization process. The numerical study demonstrates the improvement of the proposed hybrid approach, and the fuzzy genetic algorithm has demonstrated its effectiveness to generate better results than standard genetic algorithm and other traditional heuristic approaches, such as simulated annealing.
DEFF Research Database (Denmark)
Wen, Min; Krapper, Emil; Larsen, Jesper
2011-01-01
The world's second largest producer of pork, Danish Crown, also provides a fresh meat supply logistics system within Denmark. This is used by the majority of supermarkets in Denmark. This article addresses an integrated vehicle routing and driver scheduling problem arising at Danish Crown...... in their fresh meat supply logistics system. The problem consists of a 1‐week planning horizon, heterogeneous vehicles, and drivers with predefined work regulations. These regulations include, among other things, predefined workdays, fixed starting time, maximum weekly working duration, and a break rule....... The objective is to minimize the total delivery cost that is a weighted sum of two kinds of delivery costs. A multilevel variable neighborhood search heuristic is proposed for the problem. In a preprocessing step, the problem size is reduced through an aggregation procedure. Thereafter, the aggregated weekly...
The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem
Directory of Open Access Journals (Sweden)
Denis Pinha
2016-11-01
Full Text Available This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.
Directory of Open Access Journals (Sweden)
Sunxin Wang
2014-01-01
Full Text Available This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP. Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.
Guo, Peng; Cheng, Wenming; Wang, Yi
2014-10-01
The quay crane scheduling problem (QCSP) determines the handling sequence of tasks at ship bays by a set of cranes assigned to a container vessel such that the vessel's service time is minimized. A number of heuristics or meta-heuristics have been proposed to obtain the near-optimal solutions to overcome the NP-hardness of the problem. In this article, the idea of generalized extremal optimization (GEO) is adapted to solve the QCSP with respect to various interference constraints. The resulting GEO is termed the modified GEO. A randomized searching method for neighbouring task-to-QC assignments to an incumbent task-to-QC assignment is developed in executing the modified GEO. In addition, a unidirectional search decoding scheme is employed to transform a task-to-QC assignment to an active quay crane schedule. The effectiveness of the developed GEO is tested on a suite of benchmark problems introduced by K.H. Kim and Y.M. Park in 2004 (European Journal of Operational Research, Vol. 156, No. 3). Compared with other well-known existing approaches, the experiment results show that the proposed modified GEO is capable of obtaining the optimal or near-optimal solution in a reasonable time, especially for large-sized problems.
Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time
Directory of Open Access Journals (Sweden)
Hongtao Hu
2016-01-01
Full Text Available A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.
Solving a Production Scheduling Problem by Means of Two Biobjective Metaheuristic Procedures
Toncovich, Adrián; Oliveros Colay, María José; Moreno, José María; Corral, Jiménez; Corral, Rafael
2009-11-01
Production planning and scheduling problems emphasize the need for the availability of management tools that can help to assure proper service levels to customers, maintaining, at the same time, the production costs at acceptable levels and maximizing the utilization of the production facilities. In this case, a production scheduling problem that arises in the context of the activities of a company dedicated to the manufacturing of furniture for children and teenagers is addressed. Two bicriteria metaheuristic procedures are proposed to solve the sequencing problem in a production equipment that constitutes the bottleneck of the production process of the company. The production scheduling problem can be characterized as a general flow shop with sequence dependant setup times and additional inventory constraints. Two objectives are simultaneously taken into account when the quality of the candidate solutions is evaluated: the minimization of completion time of all jobs, or makespan, and the minimization of the total flow time of all jobs. Both procedures are based on a local search strategy that responds to the structure of the simulated annealing metaheuristic. In this case, both metaheuristic approaches generate a set of solutions that provides an approximation to the optimal Pareto front. In order to evaluate the performance of the proposed techniques a series of experiments was conducted. After analyzing the results, it can be said that the solutions provided by both approaches are adequate from the viewpoint of the quality as well as the computational effort involved in their generation. Nevertheless, a further refinement of the proposed procedures should be implemented with the aim of facilitating a quasi-automatic definition of the solution parameters.
Directory of Open Access Journals (Sweden)
JW Joubert
2005-06-01
Full Text Available Regardless of the success that linear programming and integer linear programming has had in applications in engineering, business and economics, one has to challenge the assumed reality that these optimization models represent. In this paper the certainty assumptions of an integer linear program application is challenged in an attempt to improve the solution robustness in an uncertain environment. The authors resort to a two-stage, fixed recourse program to introduce random variables with a uniform distribution instead of deterministic expected values in a workforce sizing and scheduling problem. Although the solution to the problem comprises a significantly larger fulltime staff complement than that determined via the problem without the introduction of random variables, the expected workforce requirements preempt and consider the costly expense of casual workers.
Directory of Open Access Journals (Sweden)
Yi Han
2013-01-01
Full Text Available This paper presents a shuffled frog leaping algorithm (SFLA for the single-mode resource-constrained project scheduling problem where activities can be divided into equant units and interrupted during processing. Each activity consumes 0–3 types of resources which are renewable and temporarily not available due to resource vacations in each period. The presence of scarce resources and precedence relations between activities makes project scheduling a difficult and important task in project management. A recent popular metaheuristic shuffled frog leaping algorithm, which is enlightened by the predatory habit of frog group in a small pond, is adopted to investigate the project makespan improvement on Patterson benchmark sets which is composed of different small and medium size projects. Computational results demonstrate the effectiveness and efficiency of SFLA in reducing project makespan and minimizing activity splitting number within an average CPU runtime, 0.521 second. This paper exposes all the scheduling sequences for each project and shows that of the 23 best known solutions have been improved.
Research on earth observing satellite segmenting and scheduling problem for area targets
He, Renjie; Ruan, Qiming
2005-10-01
The mission of an Earth Observing Satellite (EOS) is to acquire images of specified areas on the Earth surface, in response to observation requests from customers for strategic, environmental, commercial, agricultural, and civil analysis and research. A target imaged can have one out of two shapes: a spot and a large polygonal area. A spot can be covered by a single scene of satellite sensor, while a polygonal area may require cutting-up into several contiguous strips to be completely imaged. Because of the orbit restriction, satellite can only view target during specific windows of opportunity when flying over the target. Furthermore, the satellite can only be tasked during such access time windows. Hence a scheduling method of satellite observing tasks has to be taken into account for utilizing satellite sensor efficiently. This paper intends to solve a specific segmenting and scheduling problem for area targets, which concerned with an optical observing satellite equipped with line array CCD sensor. In the paper, based on the analysis of characters of satellite sensor and observed area target, a new method of segmenting area target is given. And on the basis of segmenting results of area target, a scheduling model for multi area targets is proposed. In the paper end, experimental results and analysis are also presented.
Directory of Open Access Journals (Sweden)
Huiling Fu
2013-01-01
Full Text Available One key decision basis to the train stop scheduling process is the passenger flow assignment, that is, the estimated passengers’ travel path choices from origins to destinations. Many existing assignment approaches are stochastic in nature, which causes unbalanced problems such as low efficiency in train capacity occupancy or an irrational distribution of transfer passengers among stations. The purpose of this paper is to propose a train stop scheduling approach. It combines a passenger flow assignment procedure that routes passenger travel paths freely within a train network and is particularly capable of incorporating additional restrictions on generating travel paths that better resemble the rail planner’s purpose of utilizing capacity resources by introducing four criteria to define the feasibility of travel path used by a traveler. Our approach also aims at ensuring connectivity and rapidity, the two essential characteristics of train service increasingly required by modern high-speed rails. The effectiveness of our approach is tested using the Chinese high-speed rail network as a real-world example. It works well in finding a train stop schedule of good quality whose operational indicators dominate those of an existing stochastic approach. The paper concludes with a comprehensive operational impact analysis, further demonstrating the value of our proposed approach.
A matheuristic approach for solving the Integrated Timetabling and Vehicle Scheduling Problem
DEFF Research Database (Denmark)
Fonseca, Joao Filipe Paiva; Larsen, Allan; van der Hurk, Evelien
that considers both operational costs and passenger transfer costs. Starting from a base timetable, the allowed modifications include shifting the departure time from the first station of each trip and also the extension of dwell times at important stops where large flows of passengers are expected to transfer...... between different trips. We consider transfers between bus trips scheduled by the model, but also transfers to other fixed lines that intersect the lines considered in the IT-VSP. We present a MIP formulation of the IT-VSP able to solve small instances of the problem, and a matheuristic approach that uses...
A Genetic Algorithm-based Heuristic for Part-Feeding Mobile Robot Scheduling Problem
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa; Bocewicz, Grzegorz
2012-01-01
This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell producing...... products without any shortage of parts. A method based on the characteristics of feeders and inspired by the (s, Q) inventory system, is thus applied to define time windows for feeding tasks of the robot. The performance criterion is to minimize total traveling time of the robot in a given planning horizon...
Skipping Strategy (SS) for Initial Population of Job-Shop Scheduling Problem
Abdolrazzagh-Nezhad, M.; Nababan, E. B.; Sarim, H. M.
2018-03-01
Initial population in job-shop scheduling problem (JSSP) is an essential step to obtain near optimal solution. Techniques used to solve JSSP are computationally demanding. Skipping strategy (SS) is employed to acquire initial population after sequence of job on machine and sequence of operations (expressed in Plates-jobs and mPlates-jobs) are determined. The proposed technique is applied to benchmark datasets and the results are compared to that of other initialization techniques. It is shown that the initial population obtained from the SS approach could generate optimal solution.
The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping
DEFF Research Database (Denmark)
Brouer, Berit Dangaard; Dirksen, Jakob; Pisinger, David
2013-01-01
or even omitting one. We present the Vessel Schedule Recovery Problem (VSRP) to evaluate a given disruption scenario and to select a recovery action balancing the trade off between increased bunker consumption and the impact on cargo in the remaining network and the customer service level. It is proven......Containerized transport by liner shipping companies is a multi billion dollar industry carrying a major part of the world trade between suppliers and customers. The liner shipping industry has come under stress in the last few years due to the economic crisis, increasing fuel costs, and capacity...
Directory of Open Access Journals (Sweden)
Wallace Agyei
2015-03-01
Full Text Available Abstract The problem of scheduling nurses at the Out-Patient Department OPD at Tafo Government Hospital Kumasi Ghana is presented. Currently the schedules are prepared by head nurse who performs this difficult and time consuming task by hand. Due to the existence of many constraints the resulting schedule usually does not guarantee the fairness of distribution of work. The problem was formulated as 0-1goal programming model with the of objective of evenly balancing the workload among nurses and satisfying their preferences as much as possible while complying with the legal and working regulations.. The developed model was then solved using LINGO14.0 software. The resulting schedules based on 0-1goal programming model balanced the workload in terms of the distribution of shift duties fairness in terms of the number of consecutive night duties and satisfied the preferences of the nurses. This is an improvement over the schedules done manually.
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...... practical constraints, such as temporal dependencies between crew schedules, the splitting of tasks across multiple days, crew competency requirements and several other managerial constraints. We propose a novel hybrid framework using Constraint Programming (CP) to generate initial feasible solutions...
Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem
Luo, Yabo; Waden, Yongo P.
2017-06-01
Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.
Sadik, A.R.; Urban, B.
2017-01-01
This research combines between two different manufacturing concepts. On the one hand, flow shop scheduling is a well-known problem in production systems. The problem appears when a group of jobs shares the same processing sequence on two or more machines sequentially. Flow shop scheduling tries to find the appropriate solution to optimize the sequence order of this group of jobs over the existing machines. The goal of flow shop scheduling is to obtain the continuity of the flow of the jobs ov...
Scheduling stochastic two-machine flow shop problems to minimize expected makespan
Directory of Open Access Journals (Sweden)
Mehdi Heydari
2013-07-01
Full Text Available During the past few years, despite tremendous contribution on deterministic flow shop problem, there are only limited number of works dedicated on stochastic cases. This paper examines stochastic scheduling problems in two-machine flow shop environment for expected makespan minimization where processing times of jobs are normally distributed. Since jobs have stochastic processing times, to minimize the expected makespan, the expected sum of the second machine’s free times is minimized. In other words, by minimization waiting times for the second machine, it is possible to reach the minimum of the objective function. A mathematical method is proposed which utilizes the properties of the normal distributions. Furthermore, this method can be used as a heuristic method for other distributions, as long as the means and variances are available. The performance of the proposed method is explored using some numerical examples.
A Column Generation Based Hyper-Heuristic to the Bus Driver Scheduling Problem
Directory of Open Access Journals (Sweden)
Hong Li
2015-01-01
Full Text Available Public transit providers are facing continuous pressure to improve service quality and reduce operating costs. Bus driver scheduling is among the most studied problems in this area. Based on this, flexible and powerful optimization algorithms have thus been developed and used for many years to help them with this challenge. Particularly, real-life large and complex problem instances often need new approaches to overcome the computational difficulties in solving them. Thus, we propose a column generation based hyper-heuristic for finding near-optimal solutions. Our approach takes advantages of the benefits offered by heuristic method since the column selection mode is driven by a hyper-heuristic using various strategies for the column generation subproblem. The performance of the proposed algorithm is compared with the approaches in the literature. Computational results on real-life instances are presented and discussed.
A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems
Directory of Open Access Journals (Sweden)
Jian Xiong
2012-01-01
Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.
Wang, Chun; Ji, Zhicheng; Wang, Yan
2017-07-01
In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) was studied with the objects to minimize makespan, total workload and critical workload. A variable neighborhood evolutionary algorithm (VNEA) was proposed to obtain a set of Pareto optimal solutions. First, two novel crowded operators in terms of the decision space and object space were proposed, and they were respectively used in mating selection and environmental selection. Then, two well-designed neighborhood structures were used in local search, which consider the problem characteristics and can hold fast convergence. Finally, extensive comparison was carried out with the state-of-the-art methods specially presented for solving MOFJSP on well-known benchmark instances. The results show that the proposed VNEA is more effective than other algorithms in solving MOFJSP.
Directory of Open Access Journals (Sweden)
Ming Zeng
2017-01-01
Full Text Available The gantry crane scheduling and storage space allocation problem in the main containers yard of railway container terminal is studied. A mixed integer programming model which comprehensively considers the handling procedures, noncrossing constraints, the safety margin and traveling time of gantry cranes, and the storage modes in the main area is formulated. A metaheuristic named backtracking search algorithm (BSA is then improved to solve this intractable problem. A series of computational experiments are carried out to evaluate the performance of the proposed algorithm under some randomly generated cases based on the practical operation conditions. The results show that the proposed algorithm can gain the near-optimal solutions within a reasonable computation time.
Xu, Zhenzhen; Zou, Yongxing; Kong, Xiangjie
2015-01-01
To our knowledge, this paper investigates the first application of meta-heuristic algorithms to tackle the parallel machines scheduling problem with weighted late work criterion and common due date ([Formula: see text]). Late work criterion is one of the performance measures of scheduling problems which considers the length of late parts of particular jobs when evaluating the quality of scheduling. Since this problem is known to be NP-hard, three meta-heuristic algorithms, namely ant colony system, genetic algorithm, and simulated annealing are designed and implemented, respectively. We also propose a novel algorithm named LDF (largest density first) which is improved from LPT (longest processing time first). The computational experiments compared these meta-heuristic algorithms with LDF, LPT and LS (list scheduling), and the experimental results show that SA performs the best in most cases. However, LDF is better than SA in some conditions, moreover, the running time of LDF is much shorter than SA.
Directory of Open Access Journals (Sweden)
Amir Abbas Najafi
2009-01-01
Full Text Available Resource investment problem with discounted cash flows (RIPDCFs is a class of project scheduling problem. In RIPDCF, the availability levels of the resources are considered decision variables, and the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, we consider a new RIPDCF in which tardiness of project is permitted with defined penalty. We mathematically formulated the problem and developed a heuristic method to solve it. The results of the performance analysis of the proposed method show an effective solution approach to the problem.
Directory of Open Access Journals (Sweden)
Sandu Siyoto
2015-10-01
Full Text Available Introduction: Autism is a pervasive developmental disorder in children that is characterized by the disruption and delays in cognitive, language, behavior, communication and social interaction. One of the ways for children with autism is the visual schedule. Visual schedule is a learning method in the form of information in a visual form that communicates a series of activities. This study aimed to determine the effects of a visual schedule to decrease problem behaviors when feeding activity and defecation in children with autism in the Foundation Board of Christian Education Wetan Jawi (YBPK Kediri. Method: Research design was One Group Pre Post Test Design, with a population of 30 respondents, used the purposive sampling technique obtained a sample of 16 respondents. When the reseachon April 16 Until Mei 17, 2014. Results: The results showed obtained Asymp significant p = 0.011 <0.05 with Wilcoxon statistical test, which means that HO was rejected and H1 accepted schedule. It means there were visual effects on reducing behavioral problems in feeding activity and defecation in children with autism in the Foundation Board of Christian Education Wetan Jawi (YBPK Kediri in 2014. Discussion: The Visual schedules can be applied in the treatment of autistic children who have behavior problems, because these techniques can provide influence on autistic children to be able to decrease behavior problems. Keywords: Visual Schedule, decline in behavior problems, children with autism
A HYBRID HEURISTIC ALGORITHM FOR SOLVING THE RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM (RCPSP
Directory of Open Access Journals (Sweden)
Juan Carlos Rivera
Full Text Available The Resource Constrained Project Scheduling Problem (RCPSP is a problem of great interest for the scientific community because it belongs to the class of NP-Hard problems and no methods are known that can solve it accurately in polynomial processing times. For this reason heuristic methods are used to solve it in an efficient way though there is no guarantee that an optimal solution can be obtained. This research presents a hybrid heuristic search algorithm to solve the RCPSP efficiently, combining elements of the heuristic Greedy Randomized Adaptive Search Procedure (GRASP, Scatter Search and Justification. The efficiency obtained is measured taking into account the presence of the new elements added to the GRASP algorithm taken as base: Justification and Scatter Search. The algorithms are evaluated using three data bases of instances of the problem: 480 instances of 30 activities, 480 of 60, and 600 of 120 activities respectively, taken from the library PSPLIB available online. The solutions obtained by the developed algorithm for the instances of 30, 60 and 120 are compared with results obtained by other researchers at international level, where a prominent place is obtained, according to Chen (2011.
Using Improved Ant Colony Algorithm to Investigate EMU Circulation Scheduling Problem
Directory of Open Access Journals (Sweden)
Yu Zhou
2014-01-01
Full Text Available High-speed railway is one of the most important ways to solve the long-standing travel difficulty problem in China. However, due to the high acquisition and maintenance cost, it is impossible for decision-making departments to purchase enough EMUs to satisfy the explosive travel demand. Therefore, there is an urgent need to study how to utilize EMU more efficiently and reduce costs in the case of completing a given task in train diagram. In this paper, an EMU circulation scheduling model is built based on train diagram constraints, maintenance constraints, and so forth; in the model solving process, an improved ACA algorithm has been designed. A case study is conducted to verify the feasibility of the model. Moreover, contrast tests have been carried out to compare the efficiency between the improved ACA and the traditional approaches. The results reveal that improved ACA method can solve the model with less time and the quality of each representative index is much better, which means that efficiency of the improved ACA method is higher and better scheduling scheme can be obtained.
A branch and cut approach to the multiproduct pipeline scheduling problem
Energy Technology Data Exchange (ETDEWEB)
Souza Filho, Erito Marques de; Bahiense, Laura; Ferreira Filho, Virgilio Jose Martins [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil)
2009-07-01
Pipelines are known as the most reliable and economical mode of transportation for petroleum and its derivatives, especially when large amounts of products have to be pumped for large distances. We address the short-term schedule of a pipeline system comprising the distribution of several petroleum derivatives from a single oil refinery to several depots, connected to local consumer markets, through a single multi-product pipeline. The major difficulties faced in these operations are related to the satisfaction of product demands by the various consumer markets, and operational constraints such as the maximum sizes of contiguous pumping packs, and the immiscible products. Several researchers have developed models and techniques for this short-term pipeline scheduling problem. Two different methodologies have been proposed in the literature: heuristic search techniques and exact methods. In this paper, we use a branch-and cut algorithm, performed in Xpress-MP{sup T}M, and compare the solutions obtained with that ones obtained before using the Variable Neighborhood Search metaheuristic. The computational results showed a significant improvement of performance in relation to previous algorithm. (author)
A Mixed Integer Linear Program for Solving a Multiple Route Taxi Scheduling Problem
Montoya, Justin Vincent; Wood, Zachary Paul; Rathinam, Sivakumar; Malik, Waqar Ahmad
2010-01-01
Aircraft movements on taxiways at busy airports often create bottlenecks. This paper introduces a mixed integer linear program to solve a Multiple Route Aircraft Taxi Scheduling Problem. The outputs of the model are in the form of optimal taxi schedules, which include routing decisions for taxiing aircraft. The model extends an existing single route formulation to include routing decisions. An efficient comparison framework compares the multi-route formulation and the single route formulation. The multi-route model is exercised for east side airport surface traffic at Dallas/Fort Worth International Airport to determine if any arrival taxi time savings can be achieved by allowing arrivals to have two taxi routes: a route that crosses an active departure runway and a perimeter route that avoids the crossing. Results indicate that the multi-route formulation yields reduced arrival taxi times over the single route formulation only when a perimeter taxiway is used. In conditions where the departure aircraft are given an optimal and fixed takeoff sequence, accumulative arrival taxi time savings in the multi-route formulation can be as high as 3.6 hours more than the single route formulation. If the departure sequence is not optimal, the multi-route formulation results in less taxi time savings made over the single route formulation, but the average arrival taxi time is significantly decreased.
An imperialist competitive algorithm for solving the production scheduling problem in open pit mine
Directory of Open Access Journals (Sweden)
Mojtaba Mokhtarian Asl
2016-06-01
Full Text Available Production scheduling (planning of an open-pit mine is the procedure during which the rock blocks are assigned to different production periods in a way that the highest net present value of the project achieved subject to operational constraints. The paper introduces a new and computationally less expensive meta-heuristic technique known as imperialist competitive algorithm (ICA for long-term production planning of open pit mines. The proposed algorithm modifies the original rules of the assimilation process. The ICA performance for different levels of the control factors has been studied and the results are presented. The result showed that ICA could be efficiently applied on mine production planning problem.
Energy Technology Data Exchange (ETDEWEB)
Souza Filho, Erito M.; Bahiense, Laura; Ferreira Filho, Virgilio J.M. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia (COPPE); Lima, Leonardo [Centro Federal de Educacao Tecnologica Celso Sukow da Fonseca (CEFET-RJ), Rio de Janeiro, RJ (Brazil)
2008-07-01
Pipeline are known as the most reliable and economical mode of transportation for petroleum and its derivatives, especially when large amounts of products have to be pumped for large distances. In this work we address the short-term schedule of a pipeline system comprising the distribution of several petroleum derivatives from a single oil refinery to several depots, connected to local consumer markets, through a single multi-product pipeline. We propose an integer linear programming formulation and a variable neighborhood search meta-heuristic in order to compare the performances of the exact and heuristic approaches to the problem. Computational tests in C language and MOSEL/XPRESS-MP language are performed over a real Brazilian pipeline system. (author)
Improved Genetic Algorithm with Gene Recombination for Bus Crew-Scheduling Problem
Directory of Open Access Journals (Sweden)
Cuiying Song
2015-01-01
Full Text Available This paper presents an improved genetic algorithm (GA with gene recombination for bus crew-scheduling problem in bus company. Unlike existing methods that rely on designing a fixed potential shift set by software, our new method does not need such a potential shift set information. In our method, satisfied shifts are generated through gene recombination in genetic algorithm. We conduct extensive studies based on real-life instances from Beijing Bus Group. Compared with results generated by the current manual method, ant colony algorithm, and CPLEX, computational results show that our algorithms demonstrated very good computational performances. In our tests, the number of the maximum reducing shifts can be beyond 30, especially when trip number is very large. The high relative percentage deviation demonstrated the effectiveness of the algorithm proposed.
Yang, Xin; Zeng, Zhenxiang; Wang, Ruidong; Sun, Xueshan
2016-01-01
This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems.
Minimizing makespan for a no-wait flowshop using genetic algorithm
Indian Academy of Sciences (India)
697. Pan et al (2008a) proposed a hybrid discrete particle swarm optimization algorithm to solve the no-wait flow shop scheduling problems with minimization of makespan as the objective function. Pan et al (2008b) presented a discrete particle swarm optimization algorithm to solve. NW-FSSP with both makespan and total ...
Directory of Open Access Journals (Sweden)
Jianfei Ye
2015-01-01
Full Text Available In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.
Directory of Open Access Journals (Sweden)
Hui Lu
2014-01-01
Full Text Available Test task scheduling problem (TTSP is a complex optimization problem and has many local optima. In this paper, a hybrid chaotic multiobjective evolutionary algorithm based on decomposition (CMOEA/D is presented to avoid becoming trapped in local optima and to obtain high quality solutions. First, we propose an improving integrated encoding scheme (IES to increase the efficiency. Then ten chaotic maps are applied into the multiobjective evolutionary algorithm based on decomposition (MOEA/D in three phases, that is, initial population and crossover and mutation operators. To identify a good approach for hybrid MOEA/D and chaos and indicate the effectiveness of the improving IES several experiments are performed. The Pareto front and the statistical results demonstrate that different chaotic maps in different phases have different effects for solving the TTSP especially the circle map and ICMIC map. The similarity degree of distribution between chaotic maps and the problem is a very essential factor for the application of chaotic maps. In addition, the experiments of comparisons of CMOEA/D and variable neighborhood MOEA/D (VNM indicate that our algorithm has the best performance in solving the TTSP.
Disruption Management for the Real-Time Home Caregiver Scheduling and Routing Problem
Directory of Open Access Journals (Sweden)
Biao Yuan
2017-11-01
Full Text Available The aggravating trend of the aging population, the miniaturization of the family structure, and the increase of families with empty nesters greatly affect the sustainable development of the national economy and social old-age security system of China. The emergence of home health care or home care (HHC/HC service mode provides an alternative for elderly care. How to develop and apply this new mobile service mode is crucial for the government. Therefore, the pertinent optimization problems regarding HHC/HC have constantly attracted the attention of researchers. Unexpected events, such as new requests of customers, cancellations of customers’ services, and changes of customers’ time windows, may occur during the process of executing an a priori visiting plan. These events may sometimes make the original plan non-optimal or even infeasible. To cope with this situation, we introduce disruption management to the real-time home caregiver scheduling and routing problem. The deviation measurements on customers, caregivers, and companies are first defined. A mathematical model that minimizes the weighted sum of deviation measurements is then constructed. Next, a tabu search (TS heuristic is developed to efficiently solve the problem, and a cost recorded mechanism is used to strengthen the performance. Finally, by performing computational experiments on three real-life instances, the effectiveness of the TS heuristic is tested, and the advantages of disruption management are analyzed.
Modeling and solving the dynamic patient admission scheduling problem under uncertainty.
Ceschia, Sara; Schaerf, Andrea
2012-11-01
Our goal is to propose and solve a new formulation of the recently-formalized patient admission scheduling problem, extending it by including several real-world features, such as the presence of emergency patients, uncertainty in the length of stay, and the possibility of delayed admissions. We devised a metaheuristic approach that solves both the static (predictive) and the dynamic (daily) versions of this new problem, which is based on simulated annealing and a complex neighborhood structure. The quality of our metaheuristic approach is compared with an exact method based on integer linear programming. The main outcome is that our method is able to solve large cases (up to 4000 patients) in a reasonable time, whereas the exact method can solve only small/medium-size instances (up to 250 patients). For such datasets, the two methods obtain results at the same level of quality. In addition, the gap between our (dynamic) solver and the static one, which has all information available in advance, is only 4-5%. Finally, we propose (and publish on the web) a large set of new instances, and we discuss the impact of their features in the solution process. The metaheuristic approach proved to be a valid search method to solve dynamic problems in the healthcare domain. Copyright © 2012 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Diego Novoa
2016-09-01
Full Text Available This paper tackles an extension to the Multi-activity Combined Timetabling and Crew Scheduling Problem (MCTCSP. The goal of the original problem is to schedule the minimum number of homogenous workers required, in order to visit a set of customers characterized by services needed against schedule availability. However, since in home services it is common to have specialized workers, a mathematical model considering a heterogeneous workforce is proposed. As a solution, a GRASP-based algorithm is designed. In order to test the metaheuristic performance, 110 instances from the literature are adapted to include categorical skills. In addition, another 10 instances are randomly generated to consider large problems. The results show that the proposed GRASP finds optimal solutions in 46% of the cases and saves 40–96% computational time.
Li, Shanlin; Li, Maoqin
2015-01-01
We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL) provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1) the total weight of late orders and (2) the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time.
Directory of Open Access Journals (Sweden)
Chun Wang
2017-01-01
Full Text Available A novel multiobjective memetic algorithm based on decomposition (MOMAD is proposed to solve multiobjective flexible job shop scheduling problem (MOFJSP, which simultaneously minimizes makespan, total workload, and critical workload. Firstly, a population is initialized by employing an integration of different machine assignment and operation sequencing strategies. Secondly, multiobjective memetic algorithm based on decomposition is presented by introducing a local search to MOEA/D. The Tchebycheff approach of MOEA/D converts the three-objective optimization problem to several single-objective optimization subproblems, and the weight vectors are grouped by K-means clustering. Some good individuals corresponding to different weight vectors are selected by the tournament mechanism of a local search. In the experiments, the influence of three different aggregation functions is first studied. Moreover, the effect of the proposed local search is investigated. Finally, MOMAD is compared with eight state-of-the-art algorithms on a series of well-known benchmark instances and the experimental results show that the proposed algorithm outperforms or at least has comparative performance to the other algorithms.
Directory of Open Access Journals (Sweden)
Mohammad Hossein Sadeghi
2013-08-01
Full Text Available In this paper, two different sub-problems are considered to solve a resource constrained project scheduling problem (RCPSP, namely i assignment of modes to tasks and ii scheduling of these tasks in order to minimize the makespan of the project. The modified electromagnetism-like algorithm deals with the first problem to create an assignment of modes to activities. This list is used to generate a project schedule. When a new assignment is made, it is necessary to fix all mode dependent requirements of the project activities and to generate a random schedule with the serial SGS method. A local search will optimize the sequence of the activities. Also in this paper, a new penalty function has been proposed for solutions which are infeasible with respect to non-renewable resources. Performance of the proposed algorithm has been compared with the best algorithms published so far on the basis of CPU time and number of generated schedules stopping criteria. Reported results indicate excellent performance of the algorithm.
Directory of Open Access Journals (Sweden)
Yingni Zhai
2014-10-01
Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the
Joint optimization of green vehicle scheduling and routing problem with time-varying speeds
Zhang, Dezhi; Wang, Xin; Ni, Nan; Zhang, Zhuo
2018-01-01
Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions. PMID:29466370
Directory of Open Access Journals (Sweden)
Spruyt K
2012-02-01
Full Text Available Karen Spruyt1, Danielle L Raubuck2, Katie Grogan2, David Gozal1, Mark A Stein21Department of Pediatrics and Comer Children’s Hospital, Pritzker School of Medicine, University of Chicago, Chicago, IL; 2Institute for Juvenile Research, Hyperactivity and Learning Problems Clinic, University of Illinois at Chicago, Chicago, ILBackground: Night-to-night variability in sleep of children with attention deficit hyperactivity disorder (ADHD may be a mediator of behavioral phenotype. We examined the potential association between alertness, sleep, and eating behaviors in children with ADHD and comorbid problems.Methods: Sleep was monitored by actigraphy for 7 days. Questionnaires were used to assess sleep complaints, habits and food patterns by parental report, and sleep complaints and sleepiness by child report.Results: The group comprised 18 children, including 15 boys, aged 9.4 ± 1.7 years, 88.9% Caucasian, who took one or multiple medications. Children slept on average for 6 hours and 58 minutes with a variability of 1 hour 3 minutes relative to the mean, and their sleepiness scores were highly variable from day to day. Most children had a normal body mass index (BMI. Sleepiness and BMI were associated with sleep schedules and food patterns, such that they accounted for 76% of variance, predominantly by the association of BMI with mean wake after sleep onset and by bedtime sleepiness, with wake after sleep onset variability. Similarly, 97% of variance was shared with eating behaviors, such as desserts and snacks, and fast food meals were associated with morning sleepiness.Conclusion: Disrupted sleep and sleepiness appears to favor unhealthy food patterns and may place children with ADHD at increased risk for obesity.Keywords: sleep, child, attention deficit hyperactivity disorder, actigraphy
Constraint optimization model of a scheduling problem for a robotic arm in automatic systems
DEFF Research Database (Denmark)
Kristiansen, Ewa; Smith, Stephen F.; Kristiansen, Morten
2014-01-01
. The scheduling model is implemented as a stand-alone module using constraint programming, and integrated with a larger automatic system. The results of a number of simulation experiments with simple parts are reported, both to characterize the functionality of the scheduler and to illustrate the operation...
A hierarchical scheduling problem with a well-solvable second stage
Stougie, L.; Frenk, J.B.G.; Rinnooy Kan, A.H.G.
1984-01-01
In the hierarchical scheduling model to be considered, the decision at the aggregate level to acquire a number of identical machines has to be based on probabilistic information about the jobs that have to be scheduled on these machines at the detailed level. The objective is to minimize the sum of
Directory of Open Access Journals (Sweden)
F. Redaelli
2009-01-01
the optimal schedule length in 60% of the considered cases. Our extended analysis demonstrated that HW/SW codesign can indeed lead to significantly better results. Our experiments show that by using our proposed HW/SW codesign method, the schedule length of applications can be reduced by a factor of 2 in the best case.
A column generation approach to solve the crew re-scheduling problem
D. Huisman (Dennis)
2005-01-01
textabstractWhen tracks are out of service for maintenance during a certain period, trains cannot be operated on those tracks. This leads to a modified timetable, and results in infeasible rolling stock and crew schedules. Therefore, these schedules need to be repaired. The topic of this paper is
Directory of Open Access Journals (Sweden)
Hamed Piroozfard
2016-01-01
Full Text Available Scheduling is considered as an important topic in production management and combinatorial optimization in which it ubiquitously exists in most of the real-world applications. The attempts of finding optimal or near optimal solutions for the job shop scheduling problems are deemed important, because they are characterized as highly complex and NP-hard problems. This paper describes the development of a hybrid genetic algorithm for solving the nonpreemptive job shop scheduling problems with the objective of minimizing makespan. In order to solve the presented problem more effectively, an operation-based representation was used to enable the construction of feasible schedules. In addition, a new knowledge-based operator was designed based on the problem’s characteristics in order to use machines’ idle times to improve the solution quality, and it was developed in the context of function evaluation. A machine based precedence preserving order-based crossover was proposed to generate the offspring. Furthermore, a simulated annealing based neighborhood search technique was used to improve the local exploitation ability of the algorithm and to increase its population diversity. In order to prove the efficiency and effectiveness of the proposed algorithm, numerous benchmarked instances were collected from the Operations Research Library. Computational results of the proposed hybrid genetic algorithm demonstrate its effectiveness.
Directory of Open Access Journals (Sweden)
Julien Maheut
2013-07-01
Full Text Available Purpose: The purpose of this paper is to present an algorithm that solves the supply network configuration and operations scheduling problem in a mass customization company that faces alternative operations for one specific tool machine order in a multiplant context. Design/methodology/approach: To achieve this objective, the supply chain network configuration and operations scheduling problem is presented. A model based on stroke graphs allows the design of an algorithm that enumerates all the feasible solutions. The algorithm considers the arrival of a new customized order proposal which has to be inserted into a scheduled program. A selection function is then used to choose the solutions to be simulated in a specific simulation tool implemented in a Decision Support System. Findings and Originality/value: The algorithm itself proves efficient to find all feasible solutions when alternative operations must be considered. The stroke structure is successfully used to schedule operations when considering more than one manufacturing and supply option in each step. Research limitations/implications: This paper includes only the algorithm structure for a one-by-one, sequenced introduction of new products into the list of units to be manufactured. Therefore, the lotsizing process is done on a lot-per-lot basis. Moreover, the validation analysis is done through a case study and no generalization can be done without risk. Practical implications: The result of this research would help stakeholders to determine all the feasible and practical solutions for their problem. It would also allow to assessing the total costs and delivery times of each solution. Moreover, the Decision Support System proves useful to assess alternative solutions. Originality/value: This research offers a simple algorithm that helps solve the supply network configuration problem and, simultaneously, the scheduling problem by considering alternative operations. The proposed system
National Research Council Canada - National Science Library
Anderson, Bradley
2002-01-01
... delivery is an important scheduling objective in the just-in-time (JIT) environment. Items produced too early incur holding costs, while items produced too late incur costs in the form of dissatisfied customers...
An Integer Linear Programming Model for the Radiotherapy Treatment Scheduling Problem
Burke, Edmund K.; Leite-Rocha, Pedro; Petrovic, Sanja
2011-01-01
Radiotherapy represents an important phase of treatment for a large number of cancer patients. It is essential that resources used to deliver this treatment are employed effectively. This paper presents a new integer linear programming model for real-world radiotherapy treatment scheduling and analyses the effectiveness of using this model on a daily basis in a hospital. Experiments are conducted varying the days on which schedules can be created. Results obtained using real-world data from t...
Directory of Open Access Journals (Sweden)
Jamal Abdul Nasir
2018-01-01
Full Text Available Development of an efficient and effective home health care (HHC service system is a quite recent and challenging task for the HHC firms. This paper aims to develop an HHC service system in the perspective of long-term economic sustainability as well as operational efficiency. A more flexible mixed-integer linear programming (MILP model is formulated by incorporating the dynamic arrival and departure of patients along with the selection of new patients and nursing staff. An integrated model is proposed that jointly addresses: (i patient selection; (ii nurse hiring; (iii nurse to patient assignment; and (iv scheduling and routing decisions in a daily HHC planning problem. The proposed model extends the HHC problem from conventional scheduling and routing issues to demand and capacity management aspects. It enables an HHC firm to solve the daily scheduling and routing problem considering existing patients and nursing staff in combination with the simultaneous selection of new patients and nurses, and optimizing the existing routes by including new patients and nurses. The model considers planning issues related to compatibility, time restrictions, contract durations, idle time and workload balance. Two heuristic methods are proposed to solve the model by exploiting the variable neighborhood search (VNS approach. Results obtained from the heuristic methods are compared with a CPLEX based solution. Numerical experiments performed on different data sets, show the efficiency and effectiveness of the solution methods to handle the considered problem.
Directory of Open Access Journals (Sweden)
Shanlin Li
2015-01-01
Full Text Available We consider an integrated production and distribution scheduling problem faced by a typical make-to-order manufacturer which relies on a third-party logistics (3PL provider for finished product delivery to customers. In the beginning of a planning horizon, the manufacturer has received a set of orders to be processed on a single production line. Completed orders are delivered to customers by a finite number of vehicles provided by the 3PL company which follows a fixed daily or weekly shipping schedule such that the vehicles have fixed departure dates which are not part of the decisions. The problem is to find a feasible schedule that minimizes one of the following objective functions when processing times and weights are oppositely ordered: (1 the total weight of late orders and (2 the number of vehicles used subject to the condition that the total weight of late orders is minimum. We show that both problems are solvable in polynomial time.
Flow shop scheduling algorithm to optimize warehouse activities
Directory of Open Access Journals (Sweden)
P. Centobelli
2016-01-01
Full Text Available Successful flow-shop scheduling outlines a more rapid and efficient process of order fulfilment in warehouse activities. Indeed the way and the speed of order processing and, in particular, the operations concerning materials handling between the upper stocking area and a lower forward picking one must be optimized. The two activities, drops and pickings, have considerable impact on important performance parameters for Supply Chain wholesaler companies. In this paper, a new flow shop scheduling algorithm is formulated in order to process a greater number of orders by replacing the FIFO logic for the drops activities of a wholesaler company on a daily basis. The System Dynamics modelling and simulation have been used to simulate the actual scenario and the output solutions. Finally, a t-Student test validates the modelled algorithm, granting that it can be used for all wholesalers based on drop and picking activities.
Evolutionary based system for production scheduling in foundry
Directory of Open Access Journals (Sweden)
A. Stawowy
2008-10-01
Full Text Available This work presents a development of a capable-to-promise system for companies that operate under the hybrid make-to-order and maketo-stock strategy in a lot-sizing and flowshop environment. Proposed system simultaneously considers planning and scheduling processesin order to achieve the optimality. Optimisation engine is based on an advanced evolutionary algorithm. Information available in ERPsystem from different production units and stages, the optimization module, and customer requests are integrated via Internet using XMLlanguage as a data exchange standard.The details on key elements of the system and a software architecture are given. Practical application of the system is illustrated on the example of production scheduling for an iron castings foundry.
Directory of Open Access Journals (Sweden)
Rui Zhang
2013-01-01
Full Text Available We consider a parallel machine scheduling problem with random processing/setup times and adjustable production rates. The objective functions to be minimized consist of two parts; the first part is related with the due date performance (i.e., the tardiness of the jobs, while the second part is related with the setting of machine speeds. Therefore, the decision variables include both the production schedule (sequences of jobs and the production rate of each machine. The optimization process, however, is significantly complicated by the stochastic factors in the manufacturing system. To address the difficulty, a simulation-based three-stage optimization framework is presented in this paper for high-quality robust solutions to the integrated scheduling problem. The first stage (crude optimization is featured by the ordinal optimization theory, the second stage (finer optimization is implemented with a metaheuristic called differential evolution, and the third stage (fine-tuning is characterized by a perturbation-based local search. Finally, computational experiments are conducted to verify the effectiveness of the proposed approach. Sensitivity analysis and practical implications are also discussed.
Voinescu, Bogdan I
2018-03-19
A wide range of health problems was investigated, aiming to identify the presence and severity of a set of self-reported and common sleep, psychiatric, and somatic health problems among working professionals in four different shift schedules (morning, evening, rotating, and day) in several cities in Romania. A heterogeneous sample of 488 workers of different professions completed online a battery of tests, namely the Basic Nordic Sleep Questionnaire, the Parasomnia Questionnaire, the Epworth Sleepiness Scale, and the Patient Health Questionnaire, designed to identity symptoms of insomnia, sleepiness, snoring, parasomnia, as well as of depression, anxiety, eating, somatoform, and alcohol use disorders, respectively. The timing and the duration of the sleep, along with the presence of high blood pressure and type 2 diabetes mellitus were also inquired. The prevalence of the different health problems in relation to the type of shift schedule was evaluated with the Pearson Chi-square test. ANOVA was used to calculate the significance of the difference between the means, while associations with different health problems were estimated by binary logistic regression. The most common mental health problems were depression (26%), insomnia (20%), alcohol misuse (18%), and anxiety (17%). No significant differences based on the type of shift in terms of health problems were found, except for high blood pressure and symptoms of panic disorder that were more frequently reported by the workers in early morning shifts. Together with the workers in rotating shifts, they also reported increased sleepiness, poorer sleep quality, and shorter sleep duration. In contrast, the workers in evening shifts reported less severe health problems and longer sleep duration. Working in early morning shifts was found to be associated with poorer health outcomes, while working in rotating and early morning shifts with more severe sleep-related problems.
Stronger Lagrangian bounds by use of slack variables: applications to machine scheduling problems
J.A. Hoogeveen (Han); S.L. van de Velde (Steef)
1995-01-01
textabstractLagrangian relaxation is a powerful bounding technique that has been applied successfully to manyNP-hard combinatorial optimization problems. The basic idea is to see anNP-hard problem as an easy-to-solve problem complicated by a number of nasty side constraints. We show that
Directory of Open Access Journals (Sweden)
C. Christober Asir Rajan
2008-06-01
Full Text Available The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal unit commitment in the power system for the next H hours. A 66-bus utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 24, 57 and 175 buses. Numerical results are shown comparing the cost solutions and computation time obtained by different intelligence and conventional methods.
Directory of Open Access Journals (Sweden)
Eduyn López-Santana
2018-10-01
Full Text Available This paper focuses on the problem of scheduling and routing workers in a courier service to deliver packages for a set of geographically distributed customers and, on a specific date and time window. The crew of workers has a limited capacity and a time window that represents their labor length. The problem deals with a combination of multiples variants of the vehicle routing problem as capacity, multiple periods, time windows, due dates and distance as constraints. Since in the courier services the demands could be of hundreds or thousands of packages to be delivered, the problem is computationally unmanageable. We present a three-phase solution approach. In the first phase, a scheduling model determines the visit date for each customer in the planning horizon by considering the release date, due date to visit and travel times. We use an expert system based on the know-how of the courier service, which uses an inference engine that works as a rule interpreter. In the second phase, a clustering model assigns, for each period, customers to workers according to the travel times, maximum load capacity and customer’s time windows. We use a centroid based and sweep algorithms to solve the resulted problem. Finally, in the third phase, a routing model finds the order in which each worker will visit all customers taking into account their time windows and worker’s available time. To solve the routing problem we use an Ant Colony Optimization metaheuristic. We present some numerical results using a case study, in which the proposed method of this paper finds better results in comparison with the current method used in the case study
Directory of Open Access Journals (Sweden)
Hadi Mokhtari
2015-11-01
Full Text Available In this paper, the flexible job shop scheduling problem with machine flexibility and controllable process times is studied. The main idea is that the processing times of operations may be controlled by consumptions of additional resources. The purpose of this paper to find the best trade-off between processing cost and delay cost in order to minimize the total costs. The proposed model, flexible job shop scheduling with controllable processing times (FJCPT, is formulated as an integer non-linear programming (INLP model and then it is converted into an integer linear programming (ILP model. Due to NP-hardness of FJCPT, conventional analytic optimization methods are not efficient. Hence, in order to solve the problem, a Scatter Search (SS, as an efficient metaheuristic method, is developed. To show the effectiveness of the proposed method, numerical experiments are conducted. The efficiency of the proposed algorithm is compared with that of a genetic algorithm (GA available in the literature for solving FJSP problem. The results showed that the proposed SS provide better solutions than the existing GA.
Operating room scheduling and surgeon assignment problem under surgery durations uncertainty.
Liu, Hongwei; Zhang, Tianyi; Luo, Shuai; Xu, Dan
2017-12-29
Scientific management methods are urgently needed to balance the demand and supply of heath care services in Chinese hospitals. Operating theatre is the bottleneck and costliest department. Therefore, the surgery scheduling is crucial to hospital management. To increase the utilization and reduce the cost of operating theatre, and to improve surgeons' satisfaction in the meantime, a practical surgery scheduling which could assign the operating room (OR) and surgeon for the surgery and sequence surgeries in each OR was provided for hospital managers. Surgery durations were predicted by fitting the distributions. A two-step mixed integer programming model considering surgery duration uncertainty was proposed, and sample average approximation (SAA) method was applied to solve the model. Durations of various surgeries were log-normal distributed respectively. Numerical experiments showed the model and method could get good solutions with different sample sizes. Real-life constraints and duration uncertainty were considered in the study, and the model was also very applicable in practice. Average overtime of each OR was reducing and tending to be stable with the number of surgeons increasing, which is a discipline for OR management.
Cram, Ana Catalina
As worldwide environmental awareness grow, alternative sources of energy have become important to mitigate climate change. Biogas in particular reduces greenhouse gas emissions that contribute to global warming and has the potential of providing 25% of the annual demand for natural gas in the U.S. In 2011, 55,000 metric tons of methane emissions were reduced and 301 metric tons of carbon dioxide emissions were avoided through the use of biogas alone. Biogas is produced by anaerobic digestion through the fermentation of organic material. It is mainly composed of methane with a rage of 50 to 80% in its concentration. Carbon dioxide covers 20 to 50% and small amounts of hydrogen, carbon monoxide and nitrogen. The biogas production systems are anaerobic digestion facilities and the optimal operation of an anaerobic digester requires the scheduling of all batches from multiple feedstocks during a specific time horizon. The availability times, biomass quantities, biogas production rates and storage decay rates must all be taken into account for maximal biogas production to be achieved during the planning horizon. Little work has been done to optimize the scheduling of different types of feedstock in anaerobic digestion facilities to maximize the total biogas produced by these systems. Therefore, in the present thesis, a new genetic algorithm is developed with the main objective of obtaining the optimal sequence in which different feedstocks will be processed and the optimal time to allocate to each feedstock in the digester with the main objective of maximizing the production of biogas considering different types of feedstocks, arrival times and decay rates. Moreover, all batches need to be processed in the digester in a specified time with the restriction that only one batch can be processed at a time. The developed algorithm is applied to 3 different examples and a comparison with results obtained in previous studies is presented.
Granja, C; Almada-Lobo, B; Janela, F; Seabra, J; Mendes, A
2014-12-01
As patient's length of stay in waiting lists increases, governments are looking for strategies to control the problem. Agreements were created with private providers to diminish the workload in the public sector. However, the growth of the private sector is not following the demand for care. Given this context, new management strategies have to be considered in order to minimize patient length of stay in waiting lists while reducing the costs and increasing (or at least maintaining) the quality of care. Appointment scheduling systems are today known to be proficient in the optimization of health care services. Their utilization is focused on increasing the usage of human resources, medical equipment and reducing the patient waiting times. In this paper, a simulation-based optimization approach to the Patient Admission Scheduling Problem is presented. Modeling tools and simulation techniques are used in the optimization of a diagnostic imaging department. The proposed techniques have demonstrated to be effective in the evaluation of diagnostic imaging workflows. A simulated annealing algorithm was used to optimize the patient admission sequence towards minimizing the total completion and total waiting of patients. The obtained results showed average reductions of 5% on the total completion and 38% on the patients' total waiting time. Copyright © 2014 Elsevier Inc. All rights reserved.
Hannan, M A; Akhtar, Mahmuda; Begum, R A; Basri, H; Hussain, A; Scavino, Edgar
2018-01-01
Waste collection widely depends on the route optimization problem that involves a large amount of expenditure in terms of capital, labor, and variable operational costs. Thus, the more waste collection route is optimized, the more reduction in different costs and environmental effect will be. This study proposes a modified particle swarm optimization (PSO) algorithm in a capacitated vehicle-routing problem (CVRP) model to determine the best waste collection and route optimization solutions. In this study, threshold waste level (TWL) and scheduling concepts are applied in the PSO-based CVRP model under different datasets. The obtained results from different datasets show that the proposed algorithmic CVRP model provides the best waste collection and route optimization in terms of travel distance, total waste, waste collection efficiency, and tightness at 70-75% of TWL. The obtained results for 1 week scheduling show that 70% of TWL performs better than all node consideration in terms of collected waste, distance, tightness, efficiency, fuel consumption, and cost. The proposed optimized model can serve as a valuable tool for waste collection and route optimization toward reducing socioeconomic and environmental impacts. Copyright © 2017 Elsevier Ltd. All rights reserved.
Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao
2016-01-01
Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.
Directory of Open Access Journals (Sweden)
Ahmad Zeraatkar Moghaddam
2012-01-01
Full Text Available This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model.
The Home Care Crew Scheduling Problem: Preference-based visit clustering and temporal dependencies
DEFF Research Database (Denmark)
Rasmussen, Matias Sevel; Justesen, Tor Fog; Dohn, Anders Høeg
2012-01-01
branch-and-price solution algorithm, as this method has previously given solid results for classical vehicle routing problems. Temporal dependencies are modelled as generalised precedence constraints and enforced through the branching. We introduce a novel visit clustering approach based on the soft...
DEFF Research Database (Denmark)
Muller, Laurent Flindt
2009-01-01
, where a set of destroy/repair neighborhoods compete to modify the current solution in each iteration of the algorithm. Experiments are performed on the wellknown J30, J60 and J120 benchmark instances, which show that the proposed algorithm is competitive and confirms the strength of the ALNS framework...... previously reported for different variants of the Vehicle Routing Problem....
Baniamerian, Ali; Bashiri, Mahdi; Zabihi, Fahime
2018-03-01
Cross-docking is a new warehousing policy in logistics which is widely used all over the world and attracts many researchers attention to study about in last decade. In the literature, economic aspects has been often studied, while one of the most significant factors for being successful in the competitive global market is improving quality of customer servicing and focusing on customer satisfaction. In this paper, we introduce a vehicle routing and scheduling problem with cross-docking and time windows in a three-echelon supply chain that considers customer satisfaction. A set of homogeneous vehicles collect products from suppliers and after consolidation process in the cross-dock, immediately deliver them to customers. A mixed integer linear programming model is presented for this problem to minimize transportation cost and early/tardy deliveries with scheduling of inbound and outbound vehicles to increase customer satisfaction. A two phase genetic algorithm (GA) is developed for the problem. For investigating the performance of the algorithm, it was compared with exact and lower bound solutions in small and large-size instances, respectively. Results show that there are at least 86.6% customer satisfaction by the proposed method, whereas customer satisfaction in the classical model is at most 33.3%. Numerical examples results show that the proposed two phase algorithm could achieve optimal solutions in small-size instances. Also in large-size instances, the proposed two phase algorithm could achieve better solutions with less gap from the lower bound in less computational time in comparison with the classic GA.
Directory of Open Access Journals (Sweden)
Vinícius Vilar Jacob
2016-01-01
Full Text Available This paper addresses a single-machine scheduling problem with sequence-dependent family setup times. In this problem the jobs are classified into families according to their similarity characteristics. Setup times are required on each occasion when the machine switches from processing jobs in one family to jobs in another family. The performance measure to be minimized is the total tardiness with respect to the given due dates of the jobs. The problem is classified as NP-hard in the ordinary sense. Since the computational complexity associated with the mathematical formulation of the problem makes it difficult for optimization solvers to deal with large-sized instances in reasonable solution time, efficient heuristic algorithms are needed to obtain near-optimal solutions. In this work we propose three heuristics based on the Iterated Local Search (ILS metaheuristic. The first heuristic is a basic ILS, the second uses a dynamic perturbation size, and the third uses a Path Relinking (PR technique as an intensification strategy. We carry out comprehensive computational and statistical experiments in order to analyze the performance of the proposed heuristics. The computational experiments show that the ILS heuristics outperform a genetic algorithm proposed in the literature. The ILS heuristic with dynamic perturbation size and PR intensification has a superior performance compared to other heuristics.
Crane scheduling for a plate storage in a shipyard: Solving the problem
DEFF Research Database (Denmark)
Hansen, Jesper; Kristensen, Torben F.H.
2003-01-01
. These blocks are again welded together in the dock to produce a ship. Two gantry cranes move the plates into, around and out of the storage when needed in production. Different principles for organizing the storage and also different approaches for solving the problem are compared. Our results indicate...... a potential reduction in movements by 67% and reduction in time by 39% compared to current practices. This leads to an estimated cost saving by approx. 1.0 mill. dkr. per year. This paper describes aspects of solving the model developed and described in Hansen and Kristensen (2003a)....
Directory of Open Access Journals (Sweden)
Shangchia Liu
2015-01-01
Full Text Available In the field of distributed decision making, different agents share a common processing resource, and each agent wants to minimize a cost function depending on its jobs only. These issues arise in different application contexts, including real-time systems, integrated service networks, industrial districts, and telecommunication systems. Motivated by its importance on practical applications, we consider two-agent scheduling on a single machine where the objective is to minimize the total completion time of the jobs of the first agent with the restriction that an upper bound is allowed the total completion time of the jobs for the second agent. For solving the proposed problem, a branch-and-bound and three simulated annealing algorithms are developed for the optimal solution, respectively. In addition, the extensive computational experiments are also conducted to test the performance of the algorithms.
Gong, H.; Tang, L.; Duin, C.W.
2010-01-01
Motivated by applications in iron and steel industry, we consider a two-stage flow shop scheduling problem where the first machine is a batching machine subject to the blocking constraint and the second machine is a discrete machine with shared setup times. We show that the problem is strongly
Directory of Open Access Journals (Sweden)
Farahmand-Mehr Mohammad
2014-01-01
Full Text Available In this paper, a hybrid flow shop scheduling problem with a new approach considering time lags and sequence-dependent setup time in realistic situations is presented. Since few works have been implemented in this field, the necessity of finding better solutions is a motivation to extend heuristic or meta-heuristic algorithms. This type of production system is found in industries such as food processing, chemical, textile, metallurgical, printed circuit board, and automobile manufacturing. A mixed integer linear programming (MILP model is proposed to minimize the makespan. Since this problem is known as NP-Hard class, a meta-heuristic algorithm, named Genetic Algorithm (GA, and three heuristic algorithms (Johnson, SPTCH and Palmer are proposed. Numerical experiments of different sizes are implemented to evaluate the performance of presented mathematical programming model and the designed GA in compare to heuristic algorithms and a benchmark algorithm. Computational results indicate that the designed GA can produce near optimal solutions in a short computational time for different size problems.
Cole, Mark R.
1994-01-01
In Experiment 1, a variable-ratio 10 schedule became, successively, a variable-interval schedule with only the minimum interreinforcement intervals yoked to the variable ratio, or a variable-interval schedule with both interreinforcement intervals and reinforced interresponse times yoked to the variable ratio. Response rates in the variable-interval schedule with both interreinforcement interval and reinforced interresponse time yoking fell between the higher rates maintained by the variable-...
International Nuclear Information System (INIS)
Zhao Shuyu; Lu Qinwu; Li Yi
2014-01-01
An important feature of the 3rd generation nuclear power projects of AP1000 is the scale application of the modular design and construction technology. The world's first AP1000 project has been started in 2008 in our country, some problems existing in project construction process, such as the mechanical module manufacturing progress can't well meet the needs of the practical engineering. In this article, through investigating and analyzing the main cause of affecting plant mechanical module manufacturing progress, according to our country's actual situation in design, procurement and construction, explore the measures to improve module building progress in the process of AP1000 modular construction project at this stage, provide suggestions for project smooth implementation. (authors)
Rash, James
2014-01-01
NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial
Directory of Open Access Journals (Sweden)
Chen Ming
2017-01-01
Full Text Available To solve the Flexible Job-shop Scheduling Problem (FJSP with different varieties and small batches, a modified meta-heuristic algorithm based on Genetic Algorithm (GA is proposed in which gene encoding is divided into process encoding and machine encoding, and according to the encoding mode, the machine gene fragment is connected with the process gene fragment and can be changed with the alteration of process genes. In order to get the global optimal solutions, the crossover and mutation operation of the process gene fragment and machine gene fragment are carried out respectively. In the initialization operation, the machines with shorter manufacturing time are more likely to be chosen to accelerate the convergence speed and then the tournament selection strategy is applied due to the minimum optimization objective. Meanwhile, a judgment condition of the crossover point quantity is introduced to speed up the population evolution and as an important interaction bridge between the current machine and alternative machines in the incidence matrix, a novel mutation operation of machine genes is proposed to achieve the replacement of manufacturing machines. The benchmark test shows the correctness of proposed algorithm and the case simulation proves the proposed algorithm has better performance compared with existing algorithms.
Directory of Open Access Journals (Sweden)
Imen Chaieb Memmi
2013-09-01
Full Text Available Purpose: We aim to examine the capacitated multi-item lot sizing problem which is a typical example of a large bucket model, where many different items can be produced on the same machine in one time period. We propose a new approach to determine the production sequence and lot sizes that minimize the sum of start up and setup costs, inventory and production costs over all periods.Design/methodology/approach: The approach is composed of three steps. First, we compute a lower bound on total cost. Then we propose a three sub-steps iteration procedure. We solve optimally the lot sizing problem without considering products sequencing and their cost. Then, we determine products quantities to produce each period while minimizing the storage and variable production costs. Given the products to manufacture each period, we determine its correspondent optimal products sequencing, by using a Branch and Bound algorithm. Given the sequences of products within each period, we evaluate the total start up and setup cost. We compare then the total cost obtained to the lower bound of the total cost. If this value riches a prefixed value, we stop. Otherwise, we modify the results of lot sizing problem.Findings and Originality/value: We show using an illustrative example, that the difference between the total cost and its lower bound is only 10%. This gap depends on the significance of the inventory and production costs and the machine’s capacity. Comparing the approach we develop with a traditional one, we show that we manage to reduce the total cost by 30%.Research limitations/implications: Our model fits better to real-world situations where production systems run continuously. This model is applied for limited number of part types and periods.Practical implications: Our approach determines the products to manufacture each time period, their economic amounts, and their scheduling within each period. This outcome should help decision makers bearing expensive
Directory of Open Access Journals (Sweden)
Eduardo Salazar Hornig
2011-08-01
Full Text Available En este trabajo se estudió el problema de secuenciamiento de trabajos en el taller de flujo de permutación con tiempos de preparación dependientes de la secuencia y minimización de makespan. Para ello se propuso un algoritmo de optimización mediante colonia de hormigas (ACO, llevando el problema original a una estructura semejante al problema del vendedor viajero TSP (Traveling Salesman Problem asimétrico, utilizado para su evaluación problemas propuestos en la literatura y se compara con una adaptación de la heurística NEH (Nawaz-Enscore-Ham. Posteriormente se aplica una búsqueda en vecindad a la solución obtenida tanto por ACO como NEH.This paper studied the permutation flowshop with sequence dependent setup times and makespan minimization. An ant colony algorithm which turns the original problem into an asymmetric TSP (Traveling Salesman Problem structure is presented, and applied to problems proposed in the literature and is compared with an adaptation of the NEH heuristic. Subsequently a neighborhood search was applied to the solution obtained by the ACO algorithm and the NEH heuristic.
When greediness fails: examples from stochastic scheduling
Uetz, Marc Jochen
2003-01-01
The purpose of this paper is to present examples for the sometimes surprisingly different behavior of deterministic and stochastic scheduling problems. In particular, it demonstrates some seemingly counterintuitive properties of optimal scheduling policies for stochastic machine scheduling problems.
Cao, Hui; Yan, Shuangqin; Gu, Chunli; Wang, Sumei; Ni, Lingling; Tao, Huihui; Shao, Ting; Xu, Yeqing; Tao, Fangbiao
2018-01-01
Background Attention-deficit/hyperactivity disorder (ADHD) among children is an increasing public health concern. The identification of behavioral risk factors, including sleep quality, has important public health implications for prioritizing behavioral intervention strategies for ADHD. Herein, this study aimed to investigate the prevalence of high levels of ADHD symptoms and to explore the association between sleep schedules, sleep-related problems and ADHD symptoms among preschoolers aged ...
Directory of Open Access Journals (Sweden)
Mohammad Hassan Sebt
2015-11-01
Full Text Available In this paper, a new genetic algorithm (GA is presented for solving the multi-mode resource-constrained project scheduling problem (MRCPSP with minimization of project makespan as the objective subject to resource and precedence constraints. A random key and the related mode list (ML representation scheme are used as encoding schemes and the multi-mode serial schedule generation scheme (MSSGS is considered as the decoding procedure. In this paper, a simple, efficient fitness function is proposed which has better performance compared to the other fitness functions in the literature. Defining a new mutation operator for ML is the other contribution of the current study. Comparing the results of the proposed GA with other approaches using the well-known benchmark sets in PSPLIB validates the effectiveness of the proposed algorithm to solve the MRCPSP.
Automated Scheduling Via Artificial Intelligence
Biefeld, Eric W.; Cooper, Lynne P.
1991-01-01
Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.
Feedback optimal control of dynamic stochastic two-machine flowshop with a finite buffer
Directory of Open Access Journals (Sweden)
Thang Diep
2010-06-01
Full Text Available This paper examines the optimization of production involving a tandem two-machine system producing a single part type, with each machine being subject to random breakdowns and repairs. An analytical model is formulated with a view to solving an optimal stochastic production problem of the system with machines having up-downtime non-exponential distributions. The model developed is obtained by using a dynamic programming approach and a semi-Markov process. The control problem aims to find the production rates needed by the machines to meet the demand rate, through a minimization of the inventory/shortage cost. Using the Bellman principle, the optimality conditions obtained satisfy the Hamilton-Jacobi-Bellman equation, which depends on time and system states, and ultimately, leads to a feedback control. Consequently, the new model enables us to improve the coefficient of variation (CVup/down to be less than one while it is equal to one in Markov model. Heuristics methods are used to involve the problem because of the difficulty of the analytical model using several states, and to show what control law should be used in each system state (i.e., including Kanban, feedback and CONWIP control. Numerical methods are used to solve the optimality conditions and to show how a machine should produce.
Cao, Hui; Yan, Shuangqin; Gu, Chunli; Wang, Sumei; Ni, Lingling; Tao, Huihui; Shao, Ting; Xu, Yeqing; Tao, Fangbiao
2018-02-19
Attention-deficit/hyperactivity disorder (ADHD) among children is an increasing public health concern. The identification of behavioral risk factors, including sleep quality, has important public health implications for prioritizing behavioral intervention strategies for ADHD. Herein, this study aimed to investigate the prevalence of high levels of ADHD symptoms and to explore the association between sleep schedules, sleep-related problems and ADHD symptoms among preschoolers aged 3 to 6 years in mainland China. A cross-sectional study was conducted, comprising a large sample of 15,291 preschoolers in Ma'anshan city of Anhui Province in China. ADHD symptoms were assessed by the 10-item Chinese version of the Conners Abbreviated Symptom Questionnaire (C-ASQ). Sleep-related variables included caregivers' responses to specific questions addressing children's daytime and nighttime sleep schedules, as well as sleep-related behaviors. Data on other factors were also collected, such as socio-demographic characteristics, TV viewing duration on weekdays and weekends, and outdoor activities. Logistic regression models were used to analyze the relationships between sleep schedules, sleep-related problems and ADHD symptoms. Approximately 8.6% of the total sample of preschoolers had high levels of ADHD symptoms, with boys having higher levels than girls (9.9% vs. 7.2%). In the logistic regression analysis, after adjusting for TV viewing duration, outdoor activities, and socio-demographic characteristics, delayed bedtime was significantly associated with a risk of high levels of ADHD symptoms, with odds ratios (OR) of 2.50 [95% confidence interval (CI): 2.09 ~ 3.00] and 2.04 (95% CI: 1.72 ~ 2.42) for weekdays and weekends, respectively. Longer time falling asleep (≥ 31 min) (OR = 1.76, 95% CI: 1.47 ~ 2.11), no naps (OR = 1.57, 95% CI: 1.34 ~ 1.84) and frequent sleep-related problems (OR = 4.57, 95% CI: 3.86 ~ 5.41) were also significantly
DEFF Research Database (Denmark)
Ju, Suquan; Clausen, Jens
2004-01-01
The ELDSP problem is a combined lot sizing and sequencing problem. A supplier produces and delivers components of different component types to a consumer in batches. The task is to determine the cycle time, i.e. that time between deliveries, which minimizes the total cost per time unit...
DEFF Research Database (Denmark)
Clausen, Jens; Ju, S.
2006-01-01
The ELDSP problem is a combined lot sizing and sequencing problem. A supplier produces and delivers components of different types to a consumer in batches. The task is to determine the cycle time, i.e., the time between deliveries, which minimizes the total cost per time unit. This includes...
Schutten, Johannes M.J.
1998-01-01
The Shifting Bottleneck procedure is an intuitive and reasonably good approximation algorithm for the notoriously difficult classical job shop scheduling problem. The principle of decomposing a classical job shop problem into a series of single-machine problems can also easily be applied to job shop
Sun, Yan; Lang, Maoxiang; Wang, Danzhu
2016-07-28
The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing-Tianjin-Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study.
Sun, Yan; Lang, Maoxiang; Wang, Danzhu
2016-01-01
The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formulate this problem more practicably, minimizing the total generalized costs of transporting the hazardous materials and the social risk along the planned routes are set as the optimization objectives. Meanwhile, the following formulation characteristics will be comprehensively modelled: (1) specific customer demands; (2) multiple hazardous material flows; (3) capacitated schedule-based rail service and uncapacitated time-flexible road service; and (4) environmental risk constraint. A bi-objective mixed integer nonlinear programming model is first built to formulate the routing problem that combines the formulation characteristics above. Then linear reformations are developed to linearize and improve the initial model so that it can be effectively solved by exact solution algorithms on standard mathematical programming software. By utilizing the normalized weighted sum method, we can generate the Pareto solutions to the bi-objective optimization problem for a specific case. Finally, a large-scale empirical case study from the Beijing–Tianjin–Hebei Region in China is presented to demonstrate the feasibility of the proposed methods in dealing with the practical problem. Various scenarios are also discussed in the case study. PMID:27483294
Directory of Open Access Journals (Sweden)
Yu Zhang
2014-01-01
Full Text Available We consider an ad hoc Floyd-A∗ algorithm to determine the a priori least-time itinerary from an origin to a destination given an initial time in an urban scheduled public transport (USPT network. The network is bimodal (i.e., USPT lines and walking and time dependent. The modified USPT network model results in more reasonable itinerary results. An itinerary is connected through a sequence of time-label arcs. The proposed Floyd-A∗ algorithm is composed of two procedures designated as Itinerary Finder and Cost Estimator. The A∗-based Itinerary Finder determines the time-dependent, least-time itinerary in real time, aided by the heuristic information precomputed by the Floyd-based Cost Estimator, where a strategy is formed to preestimate the time-dependent arc travel time as an associated static lower bound. The Floyd-A∗ algorithm is proven to guarantee optimality in theory and, demonstrated through a real-world example in Shenyang City USPT network to be more efficient than previous procedures. The computational experiments also reveal the time-dependent nature of the least-time itinerary. In the premise that lines run punctually, “just boarding” and “just missing” cases are identified.
Block Scheduling in High Schools.
Irmsher, Karen
1996-01-01
Block Scheduling has been considered a cure for a lengthy list of educational problems. This report reviews the literature on block schedules and describes some Oregon high schools that have integrated block scheduling. Major disadvantages included resistance to change and requirements that teachers change their teaching strategies. There is…
Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin
2016-03-01
Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.
Directory of Open Access Journals (Sweden)
Angela Hsiang-Ling Chen
2016-09-01
Full Text Available Modeling and optimizing organizational processes, such as the one represented by the Resource-Constrained Project Scheduling Problem (RCPSP, improve outcomes. Based on assumptions and simplification, this model tackles the allocation of resources so that organizations can continue to generate profits and reinvest in future growth. Nonetheless, despite all of the research dedicated to solving the RCPSP and its multi-mode variations, there is no standardized procedure that can guide project management practitioners in their scheduling tasks. This is mainly because many of the proposed approaches are either based on unrealistic/oversimplified scenarios or they propose solution procedures not easily applicable or even feasible in real-life situations. In this study, we solve a more true-to-life and complex model, Multimode RCPSP with minimal and maximal time lags (MRCPSP/max. The complexity of the model solved is presented, and the practicality of the proposed approach is justified depending on only information that is available for every project regardless of its industrial context. The results confirm that it is possible to determine a robust makespan and to calculate an execution time-frame with gaps lower than 11% between their lower and upper bounds. In addition, in many instances, the solved lower bound obtained was equal to the best-known optimum.
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
Scheduling theory, algorithms, and systems
Pinedo, Michael L
2016-01-01
This new edition of the well-established text Scheduling: Theory, Algorithms, and Systems provides an up-to-date coverage of important theoretical models in the scheduling literature as well as important scheduling problems that appear in the real world. The accompanying website includes supplementary material in the form of slide-shows from industry as well as movies that show actual implementations of scheduling systems. The main structure of the book, as per previous editions, consists of three parts. The first part focuses on deterministic scheduling and the related combinatorial problems. The second part covers probabilistic scheduling models; in this part it is assumed that processing times and other problem data are random and not known in advance. The third part deals with scheduling in practice; it covers heuristics that are popular with practitioners and discusses system design and implementation issues. All three parts of this new edition have been revamped, streamlined, and extended. The reference...
DEFF Research Database (Denmark)
Hansen, Anders Dohn; Clausen, Jens
2008-01-01
. The aim of the planning problem is twofold. A number of compulsory operations are generated, in order to comply with short term planning requirements. These operations are mostly moves of arriving and leaving slabs in the yard. A number of non-compulsory operations with a long term purpose are also...... tests are run on a generic setup with artificially generated data. The test results are very promising. The production delays are reduced significantly in the new solutions compared to the corresponding delays observed in a simulation of manual planning. The work presented in this paper is focused...
Directory of Open Access Journals (Sweden)
Faustino Tello
2018-01-01
Full Text Available We address an air traffic control operator (ATCo work-shift scheduling problem. We consider a multiple objective perspective where the number of ATCos is fixed in advance and a set of ATCo labor conditions have to be satisfied. The objectives deal with the ATCo work and rest periods and positions, the structure of the solution, the number of control center changes, or the distribution of the ATCo workloads. We propose a three-phase problem-solving methodology. In the first phase, a heuristic is used to derive infeasible initial solutions on the basis of templates. Then, a multiple independent run of the simulated annealing metaheuristic is conducted aimed at reaching feasible solutions in the second phase. Finally, a multiple independent simulated annealing run is again conducted from the initial feasible solutions to optimize the objective functions. To do this, we transform the multiple to single optimization problem by using the rank-order centroid function. In the search processes in phases 2 and 3, we use regular expressions to check the ATCo labor conditions in the visited solutions. This provides high testing speed. The proposed approach is illustrated using a real example, and the optimal solution which is reached outperforms an existing template-based reference solution.
Energy Technology Data Exchange (ETDEWEB)
Huebner, Felix; Schellenbaum, Uli; Stuerck, Christian; Gerhards, Patrick; Schultmann, Frank
2017-05-15
The magnitude of widespread nuclear decommissioning and dismantling, regarding deconstruction costs and project duration, exceeds even most of the prominent large-scale projects. The deconstruction costs of one reactor are estimated at several hundred million Euros and the dismantling period for more than a decade. The nuclear power plants built in the 1970s are coming closer to the end of their planned operating lifespan. Therefore, the decommissioning and dismantling of nuclear facilities, which is posing a multitude of challenges to planning and implementation, is becoming more and more relevant. This study describes planning methods for large-scale projects. The goal of this paper is to formulate a project planning problem that appropriately copes with the specific challenges of nuclear deconstruction projects. For this purpose, the requirements for appropriate scheduling methods are presented. Furthermore, a variety of possible scheduling problems are introduced and compared by their specifications and their behaviour. A set of particular scheduling problems including possible extensions and generalisations is assessed in detail. Based on the introduced problems and extensions, a Multi-mode Resource Investment Problem with Tardiness Penalty is chosen to fit the requirements of nuclear facility dismantling. This scheduling problem is then customised and adjusted according to the specific challenges of nuclear deconstruction projects. It can be called a Multi-mode Resource Investment Problem under the consideration of generalized precedence constraints and post-operational costs.
Artificial intelligence approaches to astronomical observation scheduling
Johnston, Mark D.; Miller, Glenn
1988-01-01
Automated scheduling will play an increasing role in future ground- and space-based observatory operations. Due to the complexity of the problem, artificial intelligence technology currently offers the greatest potential for the development of scheduling tools with sufficient power and flexibility to handle realistic scheduling situations. Summarized here are the main features of the observatory scheduling problem, how artificial intelligence (AI) techniques can be applied, and recent progress in AI scheduling for Hubble Space Telescope.
Bouma, Harmen W.; Goldengorin, Boris; Lagakos, S; Perlovsky, L; Jha, M; Covaci, B; Zaharim, A; Mastorakis, N
2009-01-01
In this paper a Boolean Linear Programming (BLP) model is presented for the single machine scheduling problem 1 vertical bar pmtn; p(j) = 2;r(j)vertical bar Sigma w(j)C(j). The problem is a special case of the open problem 1 vertical bar pmtn; p(j) = p; r(j)vertical bar Sigma wj(g)C(j). We show that
Gain scheduling using the Youla parameterization
DEFF Research Database (Denmark)
Niemann, Hans Henrik; Stoustrup, Jakob
1999-01-01
Gain scheduling controllers are considered in this paper. The gain scheduling problem where the scheduling parameter vector cannot be measured directly, but needs to be estimated is considered. An estimation of the scheduling vector has been derived by using the Youla parameterization. The use of...
Gain scheduling using the youla parameterization
DEFF Research Database (Denmark)
Niemann, H.H.; Stoustrup, Jakob
1999-01-01
Gain scheduling controllers are considered in this paper. The gain scheduling problem where the scheduling parameter vector theta cannot be measured directly, but needs to be estimated is considered. An estimation of the scheduling vector theta has been derived by using the Youla parameterization...
Decentralized Ground Staff Scheduling
DEFF Research Database (Denmark)
Sørensen, M. D.; Clausen, Jens
2002-01-01
Typically, ground staff scheduling is centrally planned for each terminal in an airport. The advantage of this is that the staff is efficiently utilized, but a disadvantage is that staff spends considerable time walking between stands. In this paper a decentralized approach for ground staff...... scheduling is investigated. The airport terminal is divided into zones, where each zone consists of a set of stands geographically next to each other. Staff is assigned to work in only one zone and the staff scheduling is planned decentralized for each zone. The advantage of this approach is that the staff...... work in a smaller area of the terminal and thus spends less time walking between stands. When planning decentralized the allocation of stands to flights influences the staff scheduling since the workload in a zone depends on which flights are allocated to stands in the zone. Hence solving the problem...
Schutten, Johannes M.J.
1995-01-01
We consider the problem of scheduling jobs in a hybrid job shop. We use the term 'hybrid' to indicate that we consider a lot of extensions of the classic job shop, such as transportation times, multiple resources, and setup times. The Shifting Bottleneck procedure can be generalized to deal with
Efficient Academic Scheduling at the U.S. Naval Academy
National Research Council Canada - National Science Library
Zane, David
2003-01-01
This research project examined academic scheduling problems at the U.S. Naval Academy. The focus was on devising methods to construct good final exam schedules and improve existing course schedules by facilitation course changes...
2016-04-30
led several cost research initiatives in cloud computing, service-oriented architecture, and agile development and various independent schedule...and he supports DoD and federal acquisition efforts with a focus on rapid and agile practices to speed solutions with the lowest practical program...assessment, and risk management to control cost and deliver on time. A Government Accountability Office (GAO) assessment of 86 programs that made up the
International Nuclear Information System (INIS)
Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali
2017-01-01
Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.
Energy Technology Data Exchange (ETDEWEB)
Jafarzadeh, Hassan; Moradinasab, Nazanin; Gerami, Ali
2017-07-01
Adjusted discrete Multi-Objective Invasive Weed Optimization (DMOIWO) algorithm, which uses fuzzy dominant approach for ordering, has been proposed to solve No-wait two-stage flexible flow shop scheduling problem. Design/methodology/approach: No-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times and probable rework in both stations, different ready times for all jobs and rework times for both stations as well as unrelated parallel machines with regards to the simultaneous minimization of maximum job completion time and average latency functions have been investigated in a multi-objective manner. In this study, the parameter setting has been carried out using Taguchi Method based on the quality indicator for beater performance of the algorithm. Findings: The results of this algorithm have been compared with those of conventional, multi-objective algorithms to show the better performance of the proposed algorithm. The results clearly indicated the greater performance of the proposed algorithm. Originality/value: This study provides an efficient method for solving multi objective no-wait two-stage flexible flow shop scheduling problem by considering sequence-dependent setup times, probable rework in both stations, different ready times for all jobs, rework times for both stations and unrelated parallel machines which are the real constraints.
Vehicle and driver scheduling for public transit.
2009-08-01
The problem of driver scheduling involves the construction of a legal set of shifts, including allowance : of overtime, which cover the blocks in a particular vehicle schedule. A shift is the work scheduled to be performed by : a driver in one day, w...
DEFF Research Database (Denmark)
Dohn, Anders Høeg
to scheduling problems with temporal dependencies between tasks. However, these problems appear in various contexts and with different properties. A group of the problems considered are related to vehicle routing problems, where transportation and time windows are important factors that must be accounted for....... Mathematical and logic-based models are presented for the problems considered. Novel components are added to existing models and the modeling decisions are justified. In one case, the model is solved by a simple, but efficient greedy construction heuristic. In the remaining cases, column generation is applied....... Column generation is an iterative exact solution method based on the theory of linear programming and is capable of providing provably optimal solutions. In some of the applications, the approach is modified to provide feasible solutions of high-quality in less time. The exceptional solution quality...
Automated scheduling and planning from theory to practice
Ozcan, Ender; Urquhart, Neil
2013-01-01
Solving scheduling problems has long presented a challenge for computer scientists and operations researchers. The field continues to expand as researchers and practitioners examine ever more challenging problems and develop automated methods capable of solving them. This book provides 11 case studies in automated scheduling, submitted by leading researchers from across the world. Each case study examines a challenging real-world problem by analysing the problem in detail before investigating how the problem may be solved using state of the art techniques.The areas covered include aircraft scheduling, microprocessor instruction scheduling, sports fixture scheduling, exam scheduling, personnel scheduling and production scheduling. Problem solving methodologies covered include exact as well as (meta)heuristic approaches, such as local search techniques, linear programming, genetic algorithms and ant colony optimisation.The field of automated scheduling has the potential to impact many aspects of our lives...
Planning and Scheduling of Airline Operations
Directory of Open Access Journals (Sweden)
İlkay ORHAN
2010-02-01
Full Text Available The Turkish Civil Aviation sector has grown at a rate of 53 % between the years 2002-2008 owing to countrywide economical developments and some removed restrictions in the aviation field. Successful international companies in the sector use advanced computer-supported solution methods for their planning and scheduling problems. These methods have been providing significant competitive advantages to those companies. There are four major scheduling and planning problems in the airline sector: flight scheduling, aircraft scheduling, crew scheduling and disruptions management. These aforementioned scheduling and planning problems faced by all airline companies in the airline sector were examined in detail. Studies reveal that companies using the advanced methods might gain significant cost reductions. However, even then, the time required for solving large scale problems may not satisfy the decision quality desired by decision makers. In such cases, using modern decision methods integrated with advanced technologies offer companies an opportunity for significant cost-advantages.
Group Elevator Peak Scheduling Based on Robust Optimization Model
ZHANG, J.; ZONG, Q.
2013-01-01
Scheduling of Elevator Group Control System (EGCS) is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization) method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is re...
Appointment scheduling with unscheduled arrivals and reprioritization
Borgman, Nardo J.; Vliegen, Ingrid M.H.; Boucherie, Richard J.; Hans, Erwin W.
2017-01-01
Inspired by the real life problem of a radiology department in a Dutch hospital, we study the problem of scheduling appointments, taking into account unscheduled arrivals and reprioritization. The radiology department offers CT diagnostics to both scheduled and unscheduled patients. Of these
Unrelated Machine Scheduling with Stochastic Processing Times
Skutella, Martin; Sviridenko, Maxim; Uetz, Marc Jochen
Two important characteristics encountered in many real-world scheduling problems are heterogeneous processors and a certain degree of uncertainty about the processing times of jobs. In this paper we address both, and study for the first time a scheduling problem that combines the classical unrelated
Strategic Gang Scheduling for Railroad Maintenance
2012-08-14
We address the railway track maintenance scheduling problem. The problem stems from the : significant percentage of the annual budget invested by the railway industry for maintaining its railway : tracks. The process requires consideration of human r...
Future aircraft networks and schedules
Shu, Yan
2011-07-01
Because of the importance of air transportation scheduling, the emergence of small aircraft and the vision of future fuel-efficient aircraft, this thesis has focused on the study of aircraft scheduling and network design involving multiple types of aircraft and flight services. It develops models and solution algorithms for the schedule design problem and analyzes the computational results. First, based on the current development of small aircraft and on-demand flight services, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. This thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch under the model. In the first step, both a frequency assignment model for scheduled flights that incorporates a passenger path choice model and a frequency assignment model for on-demand flights that incorporates a passenger mode choice model are created. In the second step, a rough fleet assignment model that determines a set of flight legs, each of which is assigned an aircraft type and a rough departure time is constructed. In the third step, a timetable model that determines an exact departure time for each flight leg is developed. Based on the models proposed in the three steps, this thesis creates schedule design instances that involve almost all the major airports and markets in the United States. The instances of the frequency assignment model created in this thesis are large-scale non-convex mixed-integer programming problems, and this dissertation develops an overall network structure and proposes iterative algorithms for solving these instances. The instances of both the rough fleet assignment model and the timetable model created in this thesis are large-scale mixed-integer programming problems, and this dissertation develops subproblem schemes for solving these instances. Based on these solution algorithms, this dissertation also presents
Records Control Schedules Repository
National Archives and Records Administration — The Records Control Schedules (RCS) repository provides access to scanned versions of records schedules, or Standard Form 115, Request for Records Disposition...
A System for Automatically Generating Scheduling Heuristics
Morris, Robert
1996-01-01
The goal of this research is to improve the performance of automated schedulers by designing and implementing an algorithm by automatically generating heuristics by selecting a schedule. The particular application selected by applying this method solves the problem of scheduling telescope observations, and is called the Associate Principal Astronomer. The input to the APA scheduler is a set of observation requests submitted by one or more astronomers. Each observation request specifies an observation program as well as scheduling constraints and preferences associated with the program. The scheduler employs greedy heuristic search to synthesize a schedule that satisfies all hard constraints of the domain and achieves a good score with respect to soft constraints expressed as an objective function established by an astronomer-user.
Optimal randomized scheduling by replacement
Energy Technology Data Exchange (ETDEWEB)
Saias, I.
1996-05-01
In the replacement scheduling problem, a system is composed of n processors drawn from a pool of p. The processors can become faulty while in operation and faulty processors never recover. A report is issued whenever a fault occurs. This report states only the existence of a fault but does not indicate its location. Based on this report, the scheduler can reconfigure the system and choose another set of n processors. The system operates satisfactorily as long as, upon report of a fault, the scheduler chooses n non-faulty processors. We provide a randomized protocol maximizing the expected number of faults the system can sustain before the occurrence of a crash. The optimality of the protocol is established by considering a closely related dual optimization problem. The game-theoretic technical difficulties that we solve in this paper are very general and encountered whenever proving the optimality of a randomized algorithm in parallel and distributed computation.
Optimization of Hierarchically Scheduled Heterogeneous Embedded Systems
DEFF Research Database (Denmark)
Pop, Traian; Pop, Paul; Eles, Petru
2005-01-01
We present an approach to the analysis and optimization of heterogeneous distributed embedded systems. The systems are heterogeneous not only in terms of hardware components, but also in terms of communication protocols and scheduling policies. When several scheduling policies share a resource......, they are organized in a hierarchy. In this paper, we address design problems that are characteristic to such hierarchically scheduled systems: assignment of scheduling policies to tasks, mapping of tasks to hardware components, and the scheduling of the activities. We present algorithms for solving these problems....... Our heuristics are able to find schedulable implementations under limited resources, achieving an efficient utilization of the system. The developed algorithms are evaluated using extensive experiments and a real-life example....
DEFF Research Database (Denmark)
Lusby, Richard Martin; Muller, Laurent Flindt; Petersen, Bjørn
2013-01-01
to be regularly taken down for refueling and maintenance, in such away that the expected cost of meeting the power demand in a number of potential scenarios is minimized. We show that the problem structure naturally lends itself to Benders decomposition; however, not all constraints can be included in the mixed...... integer programming model. We present a two phase approach that first uses Benders decomposition to solve the linear programming relaxation of a relaxed version of the problem. In the second phase, integer solutions are enumerated and a procedure is applied to make them satisfy constraints not included...... on small instances of the problem, but runs into difficulty on larger ones. Unlike heuristic approaches, however, this methodology can be used to provide lower bounds on solution quality....
Non-clairvoyant Scheduling Games
Dürr, Christoph; Nguyen, Kim Thang
In a scheduling game, each player owns a job and chooses a machine to execute it. While the social cost is the maximal load over all machines (makespan), the cost (disutility) of each player is the completion time of its own job. In the game, players may follow selfish strategies to optimize their cost and therefore their behaviors do not necessarily lead the game to an equilibrium. Even in the case there is an equilibrium, its makespan might be much larger than the social optimum, and this inefficiency is measured by the price of anarchy - the worst ratio between the makespan of an equilibrium and the optimum. Coordination mechanisms aim to reduce the price of anarchy by designing scheduling policies that specify how jobs assigned to a same machine are to be scheduled. Typically these policies define the schedule according to the processing times as announced by the jobs. One could wonder if there are policies that do not require this knowledge, and still provide a good price of anarchy. This would make the processing times be private information and avoid the problem of truthfulness. In this paper we study these so-called non-clairvoyant policies. In particular, we study the RANDOM policy that schedules the jobs in a random order without preemption, and the EQUI policy that schedules the jobs in parallel using time-multiplexing, assigning each job an equal fraction of CPU time.
Directory of Open Access Journals (Sweden)
Gh. Assadipour
2012-01-01
Full Text Available
ENGLISH ABSTRACT:The trade-off between time, cost, and quality is one of the important problems of project management. This problem assumes that all project activities can be executed in different modes of cost, time, and quality. Thus a manager should select each activity’s mode such that the project can meet the deadline with the minimum possible cost and the maximum achievable quality. As the problem is NP-hard and the objectives are in conflict with each other, a multi-objective meta-heuristic called CellDE, which is a hybrid cellular genetic algorithm, is implemented as the optimisation method. The proposed algorithm provides project managers with a set of non-dominated or Pareto-optimal solutions, and enables them to choose the best one according to their preferences. A set of problems of different sizes is generated and solved using the proposed algorithm. Three metrics are employed for evaluating the performance of the algorithm, appraising the diversity and convergence of the achieved Pareto fronts. Finally a comparison is made between CellDE and another meta-heuristic available in the literature. The results show the superiority of CellDE.
AFRIKAANSE OPSOMMING: ‘n Balans tussen tyd, koste en gehalte is een van die belangrike probleme van projekbestuur. Die vraagstuk maak gewoonlik die aanname dat alle projekaktiwiteite uitgevoer kan word op uiteenlopende wyses wat verband hou met koste, tyd en gehalte. ‘n Projekbestuurder selekteer gewoonlik die uitvoeringsmetodes sodanig per aktiwiteit dat gehoor gegegee word aan minimum koste en maksimum gehalte teen die voorwaarde van voltooiingsdatum wat bereik moet word.
Aangesien die beskrewe problem NP-hard is, word dit behandel ten opsigte van konflikterende doelwitte met ‘n multidoelwit metaheuristiese metode (CellDE. Die metode is ‘n hibride-sellulêre genetiese algoritme. Die algoritme lewer aan die besluitvormer ‘n versameling van ongedomineerde of Pareto
Stochastic scheduling on unrelated machines
Skutella, Martin; Sviridenko, Maxim; Uetz, Marc Jochen
2013-01-01
Two important characteristics encountered in many real-world scheduling problems are heterogeneous machines/processors and a certain degree of uncertainty about the actual sizes of jobs. The first characteristic entails machine dependent processing times of jobs and is captured by the classical
Sun, Yan; Lang, Maoxiang; Wang, Danzhu
2016-01-01
The transportation of hazardous materials is always accompanied by considerable risk that will impact public and environment security. As an efficient and reliable transportation organization, a multimodal service should participate in the transportation of hazardous materials. In this study, we focus on transporting hazardous materials through the multimodal service network and explore the hazardous materials multimodal routing problem from the operational level of network planning. To formu...
Complexity of scheduling multiprocessor tasks with prespecified processor allocations
Hoogeveen, J.A.; van de Velde, S.L.; van de Velde, S.L.; Veltman, Bart
1995-01-01
We investigate the computational complexity of scheduling multiprocessor tasks with prespecified processor allocations. We consider two criteria: minimizing schedule length and minimizing the sum of the task completion times. In addition, we investigate the complexity of problems when precedence
A question of matching rather than scheduling
van de Velde, S.L.
1995-01-01
Proper scheduling maintenance for Air Force C-130 aircraft involves the prevention of mismatches concerning the availability of the aircraft and a new wing kit which would prolong its use. Scheduling maintenance problems include the designation of wing kits in the production sequence to match for a
Widening the Schedulability Hierarchical Scheduling Systems
DEFF Research Database (Denmark)
Boudjadar, Jalil; David, Alexandre; Kim, Jin Hyun
2014-01-01
This paper presents a compositional approach for schedula- bility analysis of hierarchical systems, which enables to prove more sys- tems schedulable by having richer and more detailed scheduling models. We use a lightweight method (statistical model checking) for design ex- ploration, easily ass...
Analysis and Optimisation of Hierarchically Scheduled Multiprocessor Embedded Systems
DEFF Research Database (Denmark)
Pop, Traian; Pop, Paul; Eles, Petru
2008-01-01
We present an approach to the analysis and optimisation of heterogeneous multiprocessor embedded systems. The systems are heterogeneous not only in terms of hardware components, but also in terms of communication protocols and scheduling policies. When several scheduling policies share a resource......, they are organised in a hierarchy. In this paper, we first develop a holistic scheduling and schedulability analysis that determines the timing properties of a hierarchically scheduled system. Second, we address design problems that are characteristic to such hierarchically scheduled systems: assignment...... of scheduling policies to tasks, mapping of tasks to hardware components, and the scheduling of the activities. We also present several algorithms for solving these problems. Our heuristics are able to find schedulable implementations under limited resources, achieving an efficient utilisation of the system...
Long-term home care scheduling
DEFF Research Database (Denmark)
Gamst, Mette; Jensen, Thomas Sejr
In several countries, home care is provided for certain citizens living at home. The long-term home care scheduling problem is to generate work plans spanning several days such that a high quality of service is maintained and the overall cost is kept as low as possible. A solution to the problem...... provides detailed information on visits and visit times for each employee on each of the covered days. We propose a branch-and-price algorithm for the long-term home care scheduling problem. The pricing problem generates one-day plans for an employee, and the master problem merges the plans with respect...
Immunization Schedules for Adults
... ACIP Vaccination Recommendations Why Immunize? Vaccines: The Basics Immunization Schedule for Adults (19 Years of Age and ... diseases that can be prevented by vaccines . 2018 Immunization Schedule Recommended Vaccinations for Adults by Age and ...
Instant Childhood Immunization Schedule
... Recommendations Why Immunize? Vaccines: The Basics Instant Childhood Immunization Schedule Recommend on Facebook Tweet Share Compartir Get ... date. See Disclaimer for additional details. Based on Immunization Schedule for Children 0 through 6 Years of ...
Analyzing scheduling in the food-processing industry
DEFF Research Database (Denmark)
Akkerman, Renzo; van Donk, Dirk Pieter
2009-01-01
Production scheduling has been widely studied in several research areas, resulting in a large number of methods, prescriptions, and approaches. However, the impact on scheduling practice seems relatively low. This is also the case in the food-processing industry, where industry......-specific characteristics induce specific and complex scheduling problems. Based on ideas about decomposition of the scheduling task and the production process, we develop an analysis methodology for scheduling problems in food processing. This combines an analysis of structural (technological) elements of the production...... process with an analysis of the tasks of the scheduler. This helps to understand, describe, and structure scheduling problems in food processing, and forms a basis for improving scheduling and applying methods developed in literature. It also helps in evaluating the organisational structures...
Directory of Open Access Journals (Sweden)
Edilson de J. Santos
2000-08-01
Full Text Available A Programação de Produção de plantas flexíveis tem merecido crescente atenção no âmbito da Engenharia Química nos últimos anos. O objetivo principal da Programação de Produção é a alocação temporal de recursos, tais como disponibilidade de matéria-prima, utilidades e mão-de-obra, procurando otimizar um critério de desempenho. Este tipo de problema é computacionalmente difícil de ser resolvido e as diferentes abordagens propostas têm se mostrado inadequadas no que se refere ao tempo para a obtenção da solução ótima. No presente trabalho, a abordagem MILP (Mixed Integer Linear Problem baseada em uma discretização uniforme do tempo de produção é utilizada juntamente com uma abordagem de interferência lógica externa, esta última desenvolvida utilizando relações lógicas envolvendo recursos compartilhados, as quais são implementadas no sistema OSL (Optimization Subroutine Library.Production scheduling of flexible plants has receiving growing interest in the last years because of its economical importance. The main objective is to allocate the shared resources as availability of equipments, utilities and manpower, in order to minimize some performance criteria as, for example, makespan, tardiness etc. That problem is classified as computationally hard to handle, and different approaches proposed in the literature are unable to solve large problems. This paper introduces another approach using a Mixed Integer Linear Problem (MILP formulation based on the State Task Network (STN representation and the solution is obtained by using logical inference based on shared resources.
Adair, Jerry R.
1994-01-01
This paper is a consolidated report on ten major planning and scheduling systems that have been developed by the National Aeronautics and Space Administration (NASA). A description of each system, its components, and how it could be potentially used in private industry is provided in this paper. The planning and scheduling technology represented by the systems ranges from activity based scheduling employing artificial intelligence (AI) techniques to constraint based, iterative repair scheduling. The space related application domains in which the systems have been deployed vary from Space Shuttle monitoring during launch countdown to long term Hubble Space Telescope (HST) scheduling. This paper also describes any correlation that may exist between the work done on different planning and scheduling systems. Finally, this paper documents the lessons learned from the work and research performed in planning and scheduling technology and describes the areas where future work will be conducted.
Scheduling Network Traffic for Grid Purposes
DEFF Research Database (Denmark)
Gamst, Mette
This thesis concerns scheduling of network traffic in grid context. Grid computing consists of a number of geographically distributed computers, which work together for solving large problems. The computers are connected through a network. When scheduling job execution in grid computing, data...... transmission has so far not been taken into account. This causes stability problems, because data transmission takes time and thus causes delays to the execution plan. This thesis proposes the integration of job scheduling and network routing. The scientific contribution is based on methods from operations...... research and consists of six papers. The first four considers data transmission in grid context. The last two solves the data transmission problem, where the number of paths per data connection is bounded from above. The thesis shows that it is possible to solve the integrated job scheduling and network...
Group Elevator Peak Scheduling Based on Robust Optimization Model
Directory of Open Access Journals (Sweden)
ZHANG, J.
2013-08-01
Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.
Integrating Timetabling and Crew Scheduling at a Freight Railway Operator
L. Bach (Lucas); T.A.B. Dollevoet (Twan); D. Huisman (Dennis)
2014-01-01
markdownabstract__Abstract__ We investigate to what degree we can integrate a Train Timetabling / Engine Scheduling Problem with a Crew Scheduling Problem. In the Timetabling Problem we design a timetable for the desired lines by fixing the departure and arrival times. Also, we allocate
Optimization of Online Patient Scheduling with Urgencies and Preferences
I.B. Vermeulen (Ivan); S.M. Bohte (Sander); P.A.N. Bosman (Peter); S.G. Elkhuizen; P.J.M. Bakker; J.A. La Poutré (Han); C. Combi; Y. Shahar; A. Abu-Hanna
2009-01-01
htmlabstractWe consider the online problem of scheduling patients with urgencies and preferences on hospital resources with limited capacity. To solve this complex scheduling problem effectively we have to address the following sub problems: determining the allocation of capacity to patient
Case mix classification and a benchmark set for surgery scheduling
Leeftink, Gréanne; Hans, Erwin W.
Numerous benchmark sets exist for combinatorial optimization problems. However, in healthcare scheduling, only a few benchmark sets are known, mainly focused on nurse rostering. One of the most studied topics in the healthcare scheduling literature is surgery scheduling, for which there is no widely
A master surgical scheduling approach for cyclic scheduling in operating room departments
van Oostrum, Jeroen M.; van Houdenhoven, M.; Hurink, Johann L.; Hans, Elias W.; Wullink, Gerhard; Kazemier, G.
This paper addresses the problem of operating room (OR) scheduling at the tactical level of hospital planning and control. Hospitals repetitively construct operating room schedules, which is a time-consuming, tedious, and complex task. The stochasticity of the durations of surgical procedures
van Oostrum, J.M.; van Houdenhoven, M.; Hurink, Johann L.; Hans, Elias W.; Wullink, Gerhard; Kazemier, G.
2005-01-01
This paper addresses the problem of operating room scheduling at the tactical level of hospital planning and control. Hospitals repetitively construct operating room schedules, which is a time consuming tedious and complex task. The stochasticity of the durations of surgical procedures complicates
Integrated Job Scheduling and Network Routing
DEFF Research Database (Denmark)
Gamst, Mette; Pisinger, David
2013-01-01
-Wolfe decomposition is presented. The pricing problem is the linear multicommodity flow problem defined on a time-space network. Branching strategies are presented for the branchand-price algorithm and three heuristics and an exact solution method are implemented for finding a feasible start solution. Finally......We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number...... of resources which must be sent to the executing machine through a network with limited capacity. A job cannot start before all of its resources have arrived at the machine. The scheduling problem is formulated as a Mixed Integer Program (MIP) and proved to be NP-hard. An exact solution approach using Dantzig...
Rollout Algorithms for Stochastic Scheduling Problems
1998-04-01
been proposed by Tesauro [1996] in the context of simulation-based computer backgammon (the name "rollout" was introduced by Tesauro as a synonym for...control at a given state x and time k is to use Monte Carlo simulation. This was proposed by Tesauro [TeG96] in the context of backgammon. In particular...for a given backgammon position and a given roll of the dice, Tesauro suggested looking at all possible ways to play the given roll, and do a Monte
The microCHP scheduling problem
Bosman, M.G.C.; Bakker, Vincent; Molderink, Albert; Hurink, Johann L.; Smit, Gerardus Johannes Maria; Hakim Halim, Abdul; Vasant, Pandian; Barsoum, Nader
2009-01-01
The increasing penetration of renewable energy sources, the demand for more energy efficient electricity production and the increase in distributed electricity generation causes a shift in the way electricity is produced and consumed. The downside of these changes in the electricity grid is that
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
Scheduling for decommissioning projects
International Nuclear Information System (INIS)
Podmajersky, O.E.
1987-01-01
This paper describes the Project Scheduling system being employed by the Decommissioning Operations Contractor at the Shippingport Station Decommissioning Project (SSDP). Results from the planning system show that the project continues to achieve its cost and schedule goals. An integrated cost and schedule control system (C/SCS) which uses the concept of earned value for measurement of performance was instituted in accordance with DOE orders. The schedule and cost variances generated by the C/SCS system are used to confirm management's assessment of project status. This paper describes the types of schedules and tools used on the SSDP project to plan and monitor the work, and identifies factors that are unique to a decommissioning project that make scheduling critical to the achievement of the project's goals. 1 fig
Richards, Stephen F.
1991-01-01
Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.
Sedwal, Mona; Kamat, Sangeeta
2008-01-01
The Scheduled Castes (SCs, also known as Dalits) and Scheduled Tribes (STs, also known as Adivasis) are among the most socially and educationally disadvantaged groups in India. This paper examines issues concerning school access and equity for Scheduled Caste and Scheduled Tribe communities and also highlights their unique problems, which may…
MEDICAL STAFF SCHEDULING USING SIMULATED ANNEALING
Directory of Open Access Journals (Sweden)
Ladislav Rosocha
2015-07-01
Full Text Available Purpose: The efficiency of medical staff is a fundamental feature of healthcare facilities quality. Therefore the better implementation of their preferences into the scheduling problem might not only rise the work-life balance of doctors and nurses, but also may result into better patient care. This paper focuses on optimization of medical staff preferences considering the scheduling problem.Methodology/Approach: We propose a medical staff scheduling algorithm based on simulated annealing, a well-known method from statistical thermodynamics. We define hard constraints, which are linked to legal and working regulations, and minimize the violations of soft constraints, which are related to the quality of work, psychic, and work-life balance of staff.Findings: On a sample of 60 physicians and nurses from gynecology department we generated monthly schedules and optimized their preferences in terms of soft constraints. Our results indicate that the final value of objective function optimized by proposed algorithm is more than 18-times better in violations of soft constraints than initially generated random schedule that satisfied hard constraints.Research Limitation/implication: Even though the global optimality of final outcome is not guaranteed, desirable solutionwas obtained in reasonable time. Originality/Value of paper: We show that designed algorithm is able to successfully generate schedules regarding hard and soft constraints. Moreover, presented method is significantly faster than standard schedule generation and is able to effectively reschedule due to the local neighborhood search characteristics of simulated annealing.
Simultaneous scheduling of machines and mobile robots
DEFF Research Database (Denmark)
Dang, Vinh Quang; Nielsen, Izabela Ewa
2013-01-01
This paper deals with the problem of simultaneously scheduling machines and a number of autonomous mobile robots in a flexible manufacturing system (FMS). Besides capability of transporting materials between machines, the considered mobile robots are different from other material handling devices...... in terms of their advanced ability to perform tasks at machines by using their manipulation arms. The mobile robots thus have to be scheduled in relation to scheduling of machines so as to increase the efficiency of the overall system. The performance criterion is to minimize time required to complete all...
Integrating job scheduling and constrained network routing
DEFF Research Database (Denmark)
Gamst, Mette
2010-01-01
This paper examines the NP-hard problem of scheduling jobs on resources such that the overall profit of executed jobs is maximized. Job demand must be sent through a constrained network to the resource before execution can begin. The problem has application in grid computing, where a number...
Randomized online scheduling on two uniform machines
Epstein, Leah; Noga, John; Seiden, Steve S.; Sgall, Jirí; Woeginger, Gerhard
2001-01-01
We study the problem of on-line scheduling on two uniform machines with speeds 1 and s⩾1. A ϕ≈1.61803 competitive deterministic algorithm was already known. We present the first randomized results for this problem: We show that randomization does not help for speeds s⩾2, but does help for all s<2.
Empirical results on scheduling and dynamic backtracking
Boddy, Mark S.; Goldman, Robert P.
1994-01-01
At the Honeywell Technology Center (HTC), we have been working on a scheduling problem related to commercial avionics. This application is large, complex, and hard to solve. To be a little more concrete: 'large' means almost 20,000 activities, 'complex' means several activity types, periodic behavior, and assorted types of temporal constraints, and 'hard to solve' means that we have been unable to eliminate backtracking through the use of search heuristics. At this point, we can generate solutions, where solutions exist, or report failure and sometimes why the system failed. To the best of our knowledge, this is among the largest and most complex scheduling problems to have been solved as a constraint satisfaction problem, at least that has appeared in the published literature. This abstract is a preliminary report on what we have done and how. In the next section, we present our approach to treating scheduling as a constraint satisfaction problem. The following sections present the application in more detail and describe how we solve scheduling problems in the application domain. The implemented system makes use of Ginsberg's Dynamic Backtracking algorithm, with some minor extensions to improve its utility for scheduling. We describe those extensions and the performance of the resulting system. The paper concludes with some general remarks, open questions and plans for future work.
Optimal Grid Scheduling Using Improved Artificial Bee Colony Algorithm
T. Vigneswari; M. A. Maluk Mohamed
2015-01-01
Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Hete...
Intelligent scheduling support for the US Coast Guard
Energy Technology Data Exchange (ETDEWEB)
Darby-Dowman, K.; Lucas, C.; Mitra, G. [Brunel Univ., Uxbridge (United Kingdom); Fink, R. [Idaho National Engineering Lab., Idaho Falls, ID (United States); Kingsley, L.; Smith, J.W. [Coast Guard Research and Development Center, Groton, CT (United States)
1992-12-31
This paper will discuss a joint effort by the U.S. Coast Guard Research & Development Center, Idaho National Engineering Laboratory and Brunel University to provide the necessary tools to increase the human scheduler`s capability to handle the scheduling process more efficiently and effectively. Automating the scheduling process required a system that could think independently of the scheduler, that is, the systems needed its own control mechanism and knowledge base. Further, automated schedule generation became a design requirement and sophisticated algorithms were formulated to solve a complex combinatorial problem. In short, the resulting design can be viewed as a hybrid knowledge-based mathematical programming application system. This document contains an overview of the integrated system, a discrete optimization model for scheduling, and schedule diagnosis and analysis.
Mathematical programming and financial objectives for scheduling projects
Kimms, Alf
2001-01-01
Mathematical Programming and Financial Objectives for Scheduling Projects focuses on decision problems where the performance is measured in terms of money. As the title suggests, special attention is paid to financial objectives and the relationship of financial objectives to project schedules and scheduling. In addition, how schedules relate to other decisions is treated in detail. The book demonstrates that scheduling must be combined with project selection and financing, and that scheduling helps to give an answer to the planning issue of the amount of resources required for a project. The author makes clear the relevance of scheduling to cutting budget costs. The book is divided into six parts. The first part gives a brief introduction to project management. Part two examines scheduling projects in order to maximize their net present value. Part three considers capital rationing. Many decisions on selecting or rejecting a project cannot be made in isolation and multiple projects must be taken fully into a...
Cyclic machine scheduling with tool transportation - additional calculations
Kuijpers, C.M.H.
2001-01-01
In the PhD Thesis of Kuijpers a cyclic machine scheduling problem with tool transportation is considered. For the problem with two machines, it is shown that there always exists an optimal schedule with a certain structure. This is done by means of an elaborate case study. For a number of cases some
Scheduling train crews: a case study for the Dutch Railways
R. Freling (Richard); R.M. Lentink (Ramon); M.A. Odijk
2000-01-01
textabstractIn this paper the problem of scheduling train crew is considered. We discuss a general framework of which the method for solving the train crew scheduling problem is a special case. In particular, our method is a heuristic branch-and-price algorithm suitable for large scale crew
Multi-agent Pareto appointment exchanging in hospital patient scheduling
I.B. Vermeulen (Ivan); S.M. Bohte (Sander); D.J.A. Somefun (Koye); J.A. La Poutré (Han)
2007-01-01
htmlabstractWe present a dynamic and distributed approach to the hospital patient scheduling problem, in which patients can have multiple appointments that have to be scheduled to different resources. To efficiently solve this problem we develop a multi-agent Pareto-improvement appointment
Directory of Open Access Journals (Sweden)
William R. Veal
1999-09-01
Full Text Available This study examined the effects of a tri-schedule on the academic achievement of students in a high school. The tri-schedule consists of traditional, 4x4 block, and hybrid schedules running at the same time in the same high school. Effectiveness of the schedules was determined from the state mandated test of basic skills in reading, language, and mathematics. Students who were in a particular schedule their freshman year were tested at the beginning of their sophomore year. A statistical ANCOVA test was performed using the schedule types as independent variables and cognitive skill index and GPA as covariates. For reading and language, there was no statistically significant difference in test results. There was a statistical difference mathematics-computation. Block mathematics is an ideal format for obtaining more credits in mathematics, but the block format does little for mathematics achievement and conceptual understanding. The results have content specific implications for schools, administrations, and school boards who are considering block scheduling adoption.
2-Layered Architecture of Vague Logic Based Multilevel Queue Scheduler
Directory of Open Access Journals (Sweden)
Supriya Raheja
2014-01-01
Full Text Available In operating system the decisions which CPU scheduler makes regarding the sequence and length of time the task may run are not easy ones, as the scheduler has only a limited amount of information about the tasks. A good scheduler should be fair, maximizes throughput, and minimizes response time of system. A scheduler with multilevel queue scheduling partitions the ready queue into multiple queues. While assigning priorities, higher level queues always get more priorities over lower level queues. Unfortunately, sometimes lower priority tasks get starved, as the scheduler assures that the lower priority tasks may be scheduled only after the higher priority tasks. While making decisions scheduler is concerned only with one factor, that is, priority, but ignores other factors which may affect the performance of the system. With this concern, we propose a 2-layered architecture of multilevel queue scheduler based on vague set theory (VMLQ. The VMLQ scheduler handles the impreciseness of data as well as improving the starvation problem of lower priority tasks. This work also optimizes the performance metrics and improves the response time of system. The performance is evaluated through simulation using MatLab. Simulation results prove that the VMLQ scheduler performs better than the classical multilevel queue scheduler and fuzzy based multilevel queue scheduler.
Schedule Matters: Understanding the Relationship between Schedule Delays and Costs on Overruns
Majerowicz, Walt; Shinn, Stephen A.
2016-01-01
This paper examines the relationship between schedule delays and cost overruns on complex projects. It is generally accepted by many project practitioners that cost overruns are directly related to schedule delays. But what does "directly related to" actually mean? Some reasons or root causes for schedule delays and associated cost overruns are obvious, if only in hindsight. For example, unrealistic estimates, supply chain difficulties, insufficient schedule margin, technical problems, scope changes, or the occurrence of risk events can negatively impact schedule performance. Other factors driving schedule delays and cost overruns may be less obvious and more difficult to quantify. Examples of these less obvious factors include project complexity, flawed estimating assumptions, over-optimism, political factors, "black swan" events, or even poor leadership and communication. Indeed, is it even possible the schedule itself could be a source of delay and subsequent cost overrun? Through literature review, surveys of project practitioners, and the authors' own experience on NASA programs and projects, the authors will categorize and examine the various factors affecting the relationship between project schedule delays and cost growth. The authors will also propose some ideas for organizations to consider to help create an awareness of the factors which could cause or influence schedule delays and associated cost growth on complex projects.
An introduction to optimal satellite range scheduling
Vázquez Álvarez, Antonio José
2015-01-01
The satellite range scheduling (SRS) problem, an important operations research problem in the aerospace industry consisting of allocating tasks among satellites and Earth-bound objects, is examined in this book. SRS principles and solutions are applicable to many areas, including: Satellite communications, where tasks are communication intervals between sets of satellites and ground stations Earth observation, where tasks are observations of spots on the Earth by satellites Sensor scheduling, where tasks are observations of satellites by sensors on the Earth. This self-contained monograph begins with a structured compendium of the problem and moves on to explain the optimal approach to the solution, which includes aspects from graph theory, set theory, game theory and belief networks. This book is accessible to students, professionals and researchers in a variety of fields, including: operations research, optimization, scheduling theory, dynamic programming and game theory. Taking account of the distributed, ...
Integrated scheduling and resource management. [for Space Station Information System
Ward, M. T.
1987-01-01
This paper examines the problem of integrated scheduling during the Space Station era. Scheduling for Space Station entails coordinating the support of many distributed users who are sharing common resources and pursuing individual and sometimes conflicting objectives. This paper compares the scheduling integration problems of current missions with those anticipated for the Space Station era. It examines the facilities and the proposed operations environment for Space Station. It concludes that the pattern of interdependecies among the users and facilities, which are the source of the integration problem is well structured, allowing a dividing of the larger problem into smaller problems. It proposes an architecture to support integrated scheduling by scheduling efficiently at local facilities as a function of dependencies with other facilities of the program. A prototype is described that is being developed to demonstrate this integration concept.
Concept of Indoor 3D-Route UAV Scheduling System
DEFF Research Database (Denmark)
Khosiawan, Yohanes; Nielsen, Izabela Ewa; Do, Ngoc Ang Dung
2016-01-01
The objective of the proposed concept is to develop a methodology to support Unmanned Aerial Vehicles (UAVs) operation with a path planning and scheduling system in 3D environments. The proposed 3D path-planning and scheduling allows the system to schedule UAVs routing to perform tasks in 3D indoor...... environment. On top of that, the multi-source productive best-first-search concept also supports efficient real-time scheduling in response to uncertain events. Without human intervention, the proposed work provides an automatic scheduling system for UAV routing problem in 3D indoor environment....
Schedule-Aware Workflow Management Systems
Mans, Ronny S.; Russell, Nick C.; van der Aalst, Wil M. P.; Moleman, Arnold J.; Bakker, Piet J. M.
Contemporary workflow management systems offer work-items to users through specific work-lists. Users select the work-items they will perform without having a specific schedule in mind. However, in many environments work needs to be scheduled and performed at particular times. For example, in hospitals many work-items are linked to appointments, e.g., a doctor cannot perform surgery without reserving an operating theater and making sure that the patient is present. One of the problems when applying workflow technology in such domains is the lack of calendar-based scheduling support. In this paper, we present an approach that supports the seamless integration of unscheduled (flow) and scheduled (schedule) tasks. Using CPN Tools we have developed a specification and simulation model for schedule-aware workflow management systems. Based on this a system has been realized that uses YAWL, Microsoft Exchange Server 2007, Outlook, and a dedicated scheduling service. The approach is illustrated using a real-life case study at the AMC hospital in the Netherlands. In addition, we elaborate on the experiences obtained when developing and implementing a system of this scale using formal techniques.
Ada and cyclic runtime scheduling
Hood, Philip E.
1986-01-01
An important issue that must be faced while introducing Ada into the real time world is efficient and prodictable runtime behavior. One of the most effective methods employed during the traditional design of a real time system is the cyclic executive. The role cyclic scheduling might play in an Ada application in terms of currently available implementations and in terms of implementations that might be developed especially to support real time system development is examined. The cyclic executive solves many of the problems faced by real time designers, resulting in a system for which it is relatively easy to achieve approporiate timing behavior. Unfortunately a cyclic executive carries with it a very high maintenance penalty over the lifetime of the software that is schedules. Additionally, these cyclic systems tend to be quite fragil when any aspect of the system changes. The findings are presented of an ongoing SofTech investigation into Ada methods for real time system development. The topics covered include a description of the costs involved in using cyclic schedulers, the sources of these costs, and measures for future systems to avoid these costs without giving up the runtime performance of a cyclic system.
U.S. Department of Health & Human Services — This website is designed to provide information on services covered by the Medicare Physician Fee Schedule (MPFS). It provides more than 10,000 physician services,...
DEFF Research Database (Denmark)
Mizouni, Rabeb; Lazarova-Molnar, Sanja
2015-01-01
Despite several attempts to accurately predict duration and cost of software projects, initial plans still do not reflect real-life situations. Since commitments with customers are usually decided based on these initial plans, software companies frequently fail to deliver on time and many projects...... overrun both their budget and time. To improve the quality of initial project plans, we show in this paper the importance of (1) reflecting features’ priorities/risk in task schedules and (2) considering uncertainties related to human factors in plan schedules. To make simulation tasks reflect features......’ priority as well as multimodal team allocation, enhanced project schedules (EPS), where remedial actions scenarios (RAS) are added, were introduced. They reflect potential schedule modifications in case of uncertainties and promote a dynamic sequencing of involved tasks rather than the static conventional...
U.S. Department of Health & Human Services — The CMS Records Schedule provides disposition authorizations approved by the National Archives and Records Administration (NARA) for CMS program-related records...
U.S. Department of Health & Human Services — The list contains the fee schedule amounts, floors, and ceilings for all procedure codes and payment category, jurisdication, and short description assigned to each...
... Navigation Bar Home Current Issue Past Issues Childhood Vaccine Schedule Past Issues / Spring 2008 Table of Contents ... please turn Javascript on. When to Vaccinate What Vaccine Why Birth (or any age if not previously ...
DEFF Research Database (Denmark)
Andersson, Niclas; Christensen, Knud
the predominant scheduling method since it was introduced in the late 1950s. Over the years, CPM has proven to be a very powerful technique for planning, scheduling and controlling projects, which among other things is indicated by the development of a large number of CPM-based software applications available...... on the market. However, CPM is primarily an activity based method that takes the activity as the unit of focus and there is criticism raised, specifically in the case of construction projects, on the method for deficient management of construction work and continuous flow of resources. To seek solutions...... to the identified limitations of the CPM method, an alternative planning and scheduling methodology that includes locations is tested. Location-based Scheduling (LBS) implies a shift in focus, from primarily the activities to the flow of work through the various locations of the project, i.e. the building. LBS uses...
2003-01-01
The CERN Council held its 125th session on 20 June. Highlights of the meeting included confirmation that the LHC is on schedule for a 2007 start-up, and the announcement of a new organizational structure in 2004.
Fee Schedules - General Information
U.S. Department of Health & Human Services — A fee schedule is a complete listing of fees used by Medicare to pay doctors or other providers-suppliers. This comprehensive listing of fee maximums is used to...
Clinical Laboratory Fee Schedule
U.S. Department of Health & Human Services — Outpatient clinical laboratory services are paid based on a fee schedule in accordance with Section 1833(h) of the Social Security Act. The clinical laboratory fee...
Crane Scheduling for a Plate Storage
DEFF Research Database (Denmark)
Hansen, Jesper; Clausen, Jens
2002-01-01
Odense Steel Shipyard produces the worlds largest container ships. The first process of producing the steel ships is handling arrival and storage of steel plates until they are needed in production. This paper considers the problem of scheduling two cranes that carry out the movements of plates...... into, around and out of the storage. The system is required to create a daily schedule for the cranes, but also handle possible disruptions during the execution of the plan. The problem is solved with a Simulated Annealing algorithm....
Anesthesiology Nurse Scheduling using Particle Swarm Optimization
Directory of Open Access Journals (Sweden)
Leopoldo Altamirano
2012-02-01
Full Text Available In this article we present an approach designed to solve a real world problem: the Anesthesiology Nurse Scheduling Problem (ANSP at a public French hospital. The anesthesiology nurses are one of the most shared resources in the hospital and we attempt to find a fair/balanced schedule for them, taking into account a set of constraints and the nursesarsquo; stated preferences, concerning the different shifts. We propose a particle swarm optimization algorithm to solve the ANSP. Finally, we compare our technique with previous results obtained using integer programming.
Efficient Load Scheduling Method For Power Management
Directory of Open Access Journals (Sweden)
Vijo M Joy
2015-08-01
Full Text Available An efficient load scheduling method to meet varying power supply needs is presented in this paper. At peak load times the power generation system fails due to its instability. Traditionally we use load shedding process. In load shedding process disconnect the unnecessary and extra loads. The proposed method overcomes this problem by scheduling the load based on the requirement. Artificial neural networks are used for this optimal load scheduling process. For generate economic scheduling artificial neural network has been used because generation of power from each source is economically different. In this the total load required is the inputs of this network and the power generation from each source and power losses at the time of transmission are the output of the neural network. Training and programming of the artificial neural networks are done using MATLAB.
Kotamaki, M
The goal during the last few months has been to freeze and baseline as much as possible the schedules of various ATLAS systems and activities. The main motivations for the re-baselining of the schedules have been the new LHC schedule aiming at first collisions in early 2006 and the encountered delays in civil engineering as well as in the production of some of the detectors. The process was started by first preparing a new installation schedule that takes into account all the new external constraints and the new ATLAS staging scenario. The installation schedule version 3 was approved in the March EB and it provides the Ready For Installation (RFI) milestones for each system, i.e. the date when the system should be available for the start of the installation. TCn is now interacting with the systems aiming at a more realistic and resource loaded version 4 before the end of the year. Using the new RFI milestones as driving dates a new summary schedule has been prepared, or is under preparation, for each system....
Technology for planning and scheduling under complex constraints
Alguire, Karen M.; Pedro Gomes, Carla O.
1997-02-01
Within the context of law enforcement, several problems fall into the category of planning and scheduling under constraints. Examples include resource and personnel scheduling, and court scheduling. In the case of court scheduling, a schedule must be generated considering available resources, e.g., court rooms and personnel. Additionally, there are constraints on individual court cases, e.g., temporal and spatial, and between different cases, e.g., precedence. Finally, there are overall objectives that the schedule should satisfy such as timely processing of cases and optimal use of court facilities. Manually generating a schedule that satisfies all of the constraints is a very time consuming task. As the number of court cases and constraints increases, this becomes increasingly harder to handle without the assistance of automatic scheduling techniques. This paper describes artificial intelligence (AI) technology that has been used to develop several high performance scheduling applications including a military transportation scheduler, a military in-theater airlift scheduler, and a nuclear power plant outage scheduler. We discuss possible law enforcement applications where we feel the same technology could provide long-term benefits to law enforcement agencies and their operations personnel.
Planning and scheduling - A schedule's performance
International Nuclear Information System (INIS)
Whitman, N.M.
1993-01-01
Planning and scheduling is a process whose time has come to PSI Energy. With an awareness of the challenges ahead, individuals must look for ways to enhance the corporate competitiveness. Working toward this goal means that each individual has to dedicate themselves to this more competitive corporate environment. Being competitive may be defined as the ability of each employee to add value to the corporation's economic well being. The timely and successful implementation of projects greatly enhances competitiveness. Those projects that do not do well often suffer from lack of proper execution - not for lack of talent or strategic vision. Projects are consumers of resources such as cash and people. They produce a return when completed and will generate a better return when properly completed utilizing proven project management techniques. Completing projects on time, within budget and meeting customer expectations is the way a corporation builds it's future. This paper offers suggestions on implementing planning and scheduling and provides a review of results in the form of management reports
Energy Technology Data Exchange (ETDEWEB)
Cardoso, Goncalo [Technical Univ. of Lisbon (Portugal); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Center for Energy and Innovation Technologies (Austria); Bozchalui, Mohammed C. [NEC Laboratories American Inc., Irving, TX (United States); Sharma, Ratnesh [NEC Laboratories American Inc., Irving, TX (United States); Marnay, Chris [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Barbosa-Povoa, Ana [Technical Univ. of Lisbon (Portugal); Ferrao, Paulo [Technical Univ. of Lisbon (Portugal)
2013-12-06
The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained using the stochastic formulation of the problem.
Intelligent scheduling support for the US Coast Guard
Energy Technology Data Exchange (ETDEWEB)
Darby-Dowman, K.; Lucas, C.; Mitra, G. (Brunel Univ., Uxbridge (United Kingdom)); Fink, R. (Idaho National Engineering Lab., Idaho Falls, ID (United States)); Kingsley, L.; Smith, J.W. (Coast Guard Research and Development Center, Groton, CT (United States))
1992-01-01
This paper will discuss a joint effort by the U.S. Coast Guard Research Development Center, Idaho National Engineering Laboratory and Brunel University to provide the necessary tools to increase the human scheduler's capability to handle the scheduling process more efficiently and effectively. Automating the scheduling process required a system that could think independently of the scheduler, that is, the systems needed its own control mechanism and knowledge base. Further, automated schedule generation became a design requirement and sophisticated algorithms were formulated to solve a complex combinatorial problem. In short, the resulting design can be viewed as a hybrid knowledge-based mathematical programming application system. This document contains an overview of the integrated system, a discrete optimization model for scheduling, and schedule diagnosis and analysis.
Developing optimal nurses work schedule using integer programming
Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena
2017-08-01
Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.
International Nuclear Information System (INIS)
Kobayashi, Yasuhiro; Takamoto, Masanori; Nonaka, Hisanori; Yamada, Naoyuki
1994-01-01
A scheduling system has been developed by integrating symbolic processing functions for constraint handling and modification guidance, with numeric processing functions for schedule optimization and evaluation. The system is composed of an automatic schedule generation module, interactive schedule revision module and schedule evaluation module. The goal of the problem solving is the flattening of the daily resources requirement throughout the scheduling period. The automatic schedule generation module optimizes the initial schedule according to the formulatable portion of requirement description specified in a predicate-like language. A planning engineer refines the near-goal schedule through a knowledge-based interactive optimization process to obtain the goal schedule which fully covers the requirement description, with the interactive schedule revision module and schedule evaluation module. A scheduling system has been implemented on the basis of the proposed problem solving framework and experimentally applied to real-world sized scheduling problems for plant construction. With a result of the overall plant construction scheduling, a section schedule optimization process is described with the emphasis on the symbolic processing functions. (author)
Healthcare Scheduling by Data Mining: Literature Review and Future Directions
Directory of Open Access Journals (Sweden)
Maria M. Rinder
2012-01-01
Full Text Available This article presents a systematic literature review of the application of industrial engineering methods in healthcare scheduling, with a focus on the role of patient behavior in scheduling. Nine articles that used mathematical programming, data mining, genetic algorithms, and local searches for optimum schedules were obtained from an extensive search of literature. These methods are new approaches to solve the problems in healthcare scheduling. Some are adapted from areas such as manufacturing and transportation. Key findings from these studies include reduced time for scheduling, capability of solving more complex problems, and incorporation of more variables and constraints simultaneously than traditional scheduling methods. However, none of these methods modeled no-show and walk-ins patient behavior. Future research should include more variables related to patient and/or environment.
Experience in scheduled maintenance
International Nuclear Information System (INIS)
Tsai, M.T.
1985-01-01
As outage management affects both the cost and reliability of a nuclear power plant, performance of a scheduled maintenance outage in an efficient and effective manner is an important task in the operation of nuclear power plant. This paper covers the experience gained in the past ten refueling outages for the two BWR units at the First Nuclear Power Station of Taipower. The key to optimizing both the cost and schedule of a refueling outage is to maintain a high level of quality workmanship. The outage management in planning, scheduling, preparation, coordination, and cooperation, accompanied by the qualified in-house capability and sufficient outside support, have placed the refueling outages at the FNPS in a well controlled situation and have established the capacity factors of these two BWR units at a level which is 20% higher than the world average in the past years
Sahoo, Prasan Kumar; Thakkar, Hiren Kumar; Hwang, I-Shyan
2017-12-19
The K -coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K -covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K -coverage Group Scheduling (PSKGS) and Self-Organized K -coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized.
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway
Su, Ruiye; Zhou, Leishan; Tang, Jinjin
2015-01-01
The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP) through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utiliz...
Spiking Neural P Systems With Scheduled Synapses.
Cabarle, Francis George C; Adorna, Henry N; Jiang, Min; Zeng, Xiangxiang
2017-12-01
Spiking neural P systems (SN P systems) are models of computation inspired by biological spiking neurons. SN P systems have neurons as spike processors, which are placed on the nodes of a directed and static graph (the edges in the graph are the synapses). In this paper, we introduce a variant called SN P systems with scheduled synapses (SSN P systems). SSN P systems are inspired and motivated by the structural dynamism of biological synapses, while incorporating ideas from nonstatic (i.e., dynamic) graphs and networks. In particular, synapses in SSN P systems are available only at specific durations according to their schedules. The SSN P systems model is a response to the problem of introducing durations to synapses of SN P systems. Since SN P systems are in essence static graphs, it is natural to consider them for dynamic graphs also. We introduce local and global schedule types, also taking inspiration from the above-mentioned sources. We prove that SSN P systems are computationally universal as number generators and acceptors for both schedule types, under a normal form (i.e., a simplifying set of restrictions). The introduction of synapse schedules for either schedule type proves useful in programming the system, despite restrictions in the normal form.
Construction of basic match schedules for sports competitions by using graph theory
van Weert, Arjan; Schreuder, J.A.M.; Burke, Edmund; Carter, Michael
1997-01-01
Basic Match Schedules are important for constructing sports timetables. Firstly these schedules guarantee the fairness of the sports competitions and secondly they reduce the complexity of the problem. This paper presents an approach to the problem of finding Basic Match Schedules for sports
Scheduling drayage operations in synchromodal transport
Rivera, Arturo E.Pérez; Mes, Martijn R.K.; Bektas, Tolga; Coniglio, Stefano; Martinez-Sykora, Antonio; Voss, Stefan
2017-01-01
We study the problem of scheduling drayage operations in synchromodal transport. Besides the usual decisions to time the pick-up and delivery of containers, and to route the vehicles that transport them, synchromodal transport includes the assignment of terminals for empty and loaded containers. The
Step-by-step cyclic processes scheduling
DEFF Research Database (Denmark)
Bocewicz, G.; Nielsen, Izabela Ewa; Banaszak, Z.
2013-01-01
is to provide a declarative model enabling to state a constraint satisfaction problem aimed at AGVs fleet scheduling subject to assumed itineraries of concurrently manufactured product types. In other words, assuming a given layout of FMS’s material handling and production routes of simultaneously manufactured...
Scheduling in Engineering, Project, and Production Management
Chien-Ho Ko
2015-01-01
This issue presents five papers selected from the 2013 (4th) International Conference on Engineering, Project, and Production Management (EPPM2013) held in Bangkok, Thailand. Three of the papers deal with scheduling problems faced in project and production management, while the remaining two focus on engineering management issues.
Multimodal Plan Representation for Adaptable BML Scheduling
Reidsma, Dennis; van Welbergen, H.; Zwiers, Jakob; Vilhjálmsson, Hannes Högni; Kopp, Stefan; Marsella, Stacy; Thórisson, Kristinn R.
In this paper we show how behavior scheduling for Virtual Humans can be viewed as a constraint optimization problem, and how Elckerlyc uses this view to maintain a extensible behavior plan representation that allows one to make micro-adjustments to behaviors while keeping constraints between them
Scheduling in Engineering, Project, and Production Management
Directory of Open Access Journals (Sweden)
Chien-Ho Ko
2015-01-01
Full Text Available This issue presents five papers selected from the 2013 (4th International Conference on Engineering, Project, and Production Management (EPPM2013 held in Bangkok, Thailand. Three of the papers deal with scheduling problems faced in project and production management, while the remaining two focus on engineering management issues.
Split Scheduling with Uniform Setup Times
Schalekamp, F.; Sitters, R.A.; van der Ster, S.L.; Stougie, L.; Verdugo, V.; van Zuylen, A.
2015-01-01
We study a scheduling problem in which jobs may be split into parts, where the parts of a split job may be processed simultaneously on more than one machine. Each part of a job requires a setup time, however, on the machine where the job part is processed. During setup, a machine cannot process or
Split scheduling with uniform setup times.
F. Schalekamp; R.A. Sitters (René); S.L. van der Ster; L. Stougie (Leen); V. Verdugo; A. van Zuylen
2015-01-01
htmlabstractWe study a scheduling problem in which jobs may be split into parts, where the parts of a split job may be processed simultaneously on more than one machine. Each part of a job requires a setup time, however, on the machine where the job part is processed. During setup, a
Power Efficient Hierarchical Scheduling for DSP Transformations
Directory of Open Access Journals (Sweden)
P. K. Merakos
2002-01-01
Full Text Available In this paper, the problem of scheduling the computation of partial products in transformational Digital Signal Processing (DSP algorithms, aiming at the minimization of the switching activity in data and address buses, is addressed. The problem is stated as a hierarchical scheduling problem. Two different optimization algorithms, which are based on the Travelling Salesman Problem (TSP, are defined. The proposed optimization algorithms are independent on the target architecture and can be adapted to take into account it. Experimental results obtained from the application of the proposed algorithms in various widely used DSP transformations, like Discrete Cosine Transform (DCT and Discrete Fourier Transform (DFT, show that significant switching activity savings in data and address buses can be achieved, resulting in corresponding power savings. In addition, the differences between the two proposed methods are underlined, providing envisage for their suitable selection for implementation, in particular transformational algorithms and architectures.
Fuzzy HRRN CPU Scheduling Algorithm
Bashir Alam; R. Biswas; M. Alam
2011-01-01
There are several scheduling algorithms like FCFS, SRTN, RR, priority etc. Scheduling decisions of these algorithms are based on parameters which are assumed to be crisp. However, in many circumstances these parameters are vague. The vagueness of these parameters suggests that scheduler should use fuzzy technique in scheduling the jobs. In this paper we have proposed a novel CPU scheduling algorithm Fuzzy HRRN that incorporates fuzziness in basic HRRN using fuzzy Technique FIS.
Online Algorithms for Parallel Job Scheduling and Strip Packing
Hurink, Johann L.; Paulus, J.J.
We consider the online scheduling problem of parallel jobs on parallel machines, $P|online{−}list,m_j |C_{max}$. For this problem we present a 6.6623-competitive algorithm. This improves the best known 7-competitive algorithm for this problem. The presented algorithm also applies to the problem
No-Wait Job Shop Scheduling, a Constraint Propagation Approach
Lennartz, P.M.
2006-01-01
Multi-machine scheduling problems have earned themselves a reputation of intractability. In this thesis we try to solve a special kind of these problems, the so-called no-wait job shop problems. In an instance of this problem-class we are given a number of operations that are to be executed on a
Spike: Artificial intelligence scheduling for Hubble space telescope
Johnston, Mark; Miller, Glenn; Sponsler, Jeff; Vick, Shon; Jackson, Robert
1990-01-01
Efficient utilization of spacecraft resources is essential, but the accompanying scheduling problems are often computationally intractable and are difficult to approximate because of the presence of numerous interacting constraints. Artificial intelligence techniques were applied to the scheduling of the NASA/ESA Hubble Space Telescope (HST). This presents a particularly challenging problem since a yearlong observing program can contain some tens of thousands of exposures which are subject to a large number of scientific, operational, spacecraft, and environmental constraints. New techniques were developed for machine reasoning about scheduling constraints and goals, especially in cases where uncertainty is an important scheduling consideration and where resolving conflicts among conflicting preferences is essential. These technique were utilized in a set of workstation based scheduling tools (Spike) for HST. Graphical displays of activities, constraints, and schedules are an important feature of the system. High level scheduling strategies using both rule based and neural network approaches were developed. While the specific constraints implemented are those most relevant to HST, the framework developed is far more general and could easily handle other kinds of scheduling problems. The concept and implementation of the Spike system are described along with some experiments in adapting Spike to other spacecraft scheduling domains.
Column generation approaches to ship scheduling with flexible cargo sizes
DEFF Research Database (Denmark)
Brønmo, Geir; Nygreen, Bjørn; Lysgaard, Jens
2010-01-01
We present a Dantzig-Wolfe procedure for the ship scheduling problem with flexible cargo sizes. This problem is similar to the well-known pickup and delivery problem with time windows, but the cargo sizes are defined by intervals instead of by fixed values. The flexible cargo sizes have consequen......We present a Dantzig-Wolfe procedure for the ship scheduling problem with flexible cargo sizes. This problem is similar to the well-known pickup and delivery problem with time windows, but the cargo sizes are defined by intervals instead of by fixed values. The flexible cargo sizes have...
Iterative robust multiprocessor scheduling
Adyanthaya, S.; Geilen, M.; Basten, T.; Voeten, J.; Schiffelers, R.
2015-01-01
General purpose platforms are characterized by unpredictable timing behavior. Real-time schedules of tasks on general purpose platforms need to be robust against variations in task execution times. We define robustness in terms of the expected number of tasks that miss deadlines. We present an
CMS multicore scheduling strategy
International Nuclear Information System (INIS)
Yzquierdo, Antonio Pérez-Calero; Hernández, Jose; Holzman, Burt; Majewski, Krista; McCrea, Alison
2014-01-01
In the next years, processor architectures based on much larger numbers of cores will be most likely the model to continue 'Moore's Law' style throughput gains. This not only results in many more jobs in parallel running the LHC Run 1 era monolithic applications, but also the memory requirements of these processes push the workernode architectures to the limit. One solution is parallelizing the application itself, through forking and memory sharing or through threaded frameworks. CMS is following all of these approaches and has a comprehensive strategy to schedule multicore jobs on the GRID based on the glideinWMS submission infrastructure. The main component of the scheduling strategy, a pilot-based model with dynamic partitioning of resources that allows the transition to multicore or whole-node scheduling without disallowing the use of single-core jobs, is described. This contribution also presents the experiences made with the proposed multicore scheduling schema and gives an outlook of further developments working towards the restart of the LHC in 2015.
Production planning and scheduling in refinery industry
Energy Technology Data Exchange (ETDEWEB)
Persson, Jan
1999-06-01
In this thesis we consider production planning and scheduling in refinery industry, in particular we study the planning and scheduling at the Nynaes AB refinery and at the Scanraff AB refinery. The purpose is to contribute to the development and the use of optimization models to support efficient decision making. We identify various decision problems concerning the aggregated production planning, the shipment planning, the scheduling of operation modes, and the utilization of pipes and tanks; and we discuss the potential to successfully apply optimization models on these problems. We formulate a mixed integer linear programming model for the scheduling of operation modes at Nynaes. The model concerns decisions about which mode of operation to use at a particular point in time in order to minimize costs of changing modes and costs of keeping inventories, given demands for products. We derive several types of valid inequalities for this mathematical problem and show how these inequalities can improve the lower bound obtained from the linear programming relaxation of the problem. We also show how the valid inequalities can be used to improve the performance of a branch and bound solution approach. Further, a tabu search heuristic is developed for the scheduling problem. The solution methods are tested on data provided by the Nynaes refinery, and the performance of the methods are discussed. We present several extensions of the proposed model, and illustrate how the model can be used to support both operational and strategic decision making at the refinery. 66 refs, 6 figs, 32 tabs. Also published as: Dissertation from the International Graduate School of Management and Industrial Engineering, No 25, Licenciate Thesis
Production planning and scheduling in refinery industry
Energy Technology Data Exchange (ETDEWEB)
Persson, Jan
1999-07-01
In this thesis we consider production planning and scheduling in refinery industry, in particular we study the planning and scheduling at the Nynaes AB refinery and at the Scanraff AB refinery. The purpose is to contribute to the development and the use of optimization models to support efficient decision making. We identify various decision problems concerning the aggregated production planning, the shipment planning, the scheduling of operation modes, and the utilization of pipes and tanks; and we discuss the potential to successfully apply optimization models on these problems. We formulate a mixed integer linear programming model for the scheduling of operation modes at Nynaes. The model concerns decisions about which mode of operation to use at a particular point in time in order to minimize costs of changing modes and costs of keeping inventories, given demands for products. We derive several types of valid inequalities for this mathematical problem and show how these inequalities can improve the lower bound obtained from the linear programming relaxation of the problem. We also show how the valid inequalities can be used to improve the performance of a branch and bound solution approach. Further, a tabu search heuristic is developed for the scheduling problem. The solution methods are tested on data provided by the Nynaes refinery, and the performance of the methods are discussed. We present several extensions of the proposed model, and illustrate how the model can be used to support both operational and strategic decision making at the refinery. 66 refs, 6 figs, 32 tabs. Also published as: Dissertation from the International Graduate School of Management and Industrial Engineering, No 25, Licenciate Thesis.
Production planning and scheduling in refinery industry
International Nuclear Information System (INIS)
Persson, Jan.
1999-01-01
In this thesis we consider production planning and scheduling in refinery industry, in particular we study the planning and scheduling at the Nynaes AB refinery and at the Scanraff AB refinery. The purpose is to contribute to the development and the use of optimization models to support efficient decision making. We identify various decision problems concerning the aggregated production planning, the shipment planning, the scheduling of operation modes, and the utilization of pipes and tanks; and we discuss the potential to successfully apply optimization models on these problems. We formulate a mixed integer linear programming model for the scheduling of operation modes at Nynaes. The model concerns decisions about which mode of operation to use at a particular point in time in order to minimize costs of changing modes and costs of keeping inventories, given demands for products. We derive several types of valid inequalities for this mathematical problem and show how these inequalities can improve the lower bound obtained from the linear programming relaxation of the problem. We also show how the valid inequalities can be used to improve the performance of a branch and bound solution approach. Further, a tabu search heuristic is developed for the scheduling problem. The solution methods are tested on data provided by the Nynaes refinery, and the performance of the methods are discussed. We present several extensions of the proposed model, and illustrate how the model can be used to support both operational and strategic decision making at the refinery. 66 refs, 6 figs, 32 tabs. Also published as: Dissertation from the International Graduate School of Management and Industrial Engineering, No 25, Licenciate Thesis
1999-10-01
A general mathematical formulation has been developed for scheduling of construction projects and applied to the problem of highway construction scheduling. Repetitive and non-repetitive tasks, work continuity considerations, multiple-crew strategies...
Linearly Ordered Attribute Grammar Scheduling Using SAT-Solving
Bransen, Jeroen; van Binsbergen, L.Thomas; Claessen, Koen; Dijkstra, Atze
2015-01-01
Many computations over trees can be specified using attribute grammars. Compilers for attribute grammars need to find an evaluation order (or schedule) in order to generate efficient code. For the class of linearly ordered attribute grammars such a schedule can be found statically, but this problem
Heuristic algorithms for scheduling heat-treatment furnaces of steel ...
Indian Academy of Sciences (India)
job-families and non-identical job sizes. We were led to this problem through a real- world application involving the scheduling of heat-treatment operations of steel casting. The scheduling of furnaces for heat-treatment of castings is of considerable interest as a large proportion of the total production time is the processing ...
Improving the performance of sorter systems by scheduling inbound containers
Haneyah, S.W.A.; Schutten, Johannes M.J.; Fikse, K.
2013-01-01
This paper addresses the inbound containers scheduling problem for automated sorter systems in two different industrial sectors: parcel & postal sorting and baggage handling. We build on existing literature, particularly on the dynamic load balancing algorithm designed for the parcel hub scheduling
Duality-based algorithms for scheduling on unrelated parallel machines
van de Velde, S.L.; van de Velde, S.L.
1993-01-01
We consider the following parallel machine scheduling problem. Each of n independent jobs has to be scheduled on one of m unrelated parallel machines. The processing of job J[sub l] on machine Mi requires an uninterrupted period of positive length p[sub lj]. The objective is to find an assignment of
Improving Patient Schedules by Multi-agent Pareto Appointment Exchanging
I.B. Vermeulen (Ivan); S.M. Bohte (Sander); D.J.A. Somefun (Koye); J.A. La Poutré (Han)
2006-01-01
textabstractWe present a dynamic and distributed approach to the hospital patient scheduling problem: the multi-agent Pareto-improvement appointment exchanging algorithm, MPAEX. It respects the decentralization of scheduling authorities and is capable of continuously adjusting the different patient
Decentralized Online Scheduling of Combination-Appointments in Hospitals
I.B. Vermeulen (Ivan); S.M. Bohte (Sander); S.G. Elkhuizen; P.J.M. Bakker; J.A. La Poutré (Han); S. Raaijmakers; J. Rintanen; B. Nebel; J.C. Beck
2008-01-01
htmlabstractWe consider the online problem of scheduling combination appointments for outpatients. Scheduling multiple appointments on a single day is high on the list of outpatient preferences. It is hard to achieve for two reasons: first, due to the typical distributed authority in hospitals,
A note on simulated annealing to computer laboratory scheduling ...
African Journals Online (AJOL)
Simulated Annealing algorithm is used in solving real life problem of Computer Laboratory scheduling in order to maximize the use of scarce and insufficient resources. KEY WORDS: Simulated Annealing (SA), Computer Laboratory Scheduling, Statistical Thermodynamics, Energy Function, and Heuristic etc. Global Jnl of ...
Real-time systems scheduling 2 focuses
Chetto, Maryline
2014-01-01
Real-time systems are used in a wide range of applications, including control, sensing, multimedia, etc. Scheduling is a central problem for these computing/communication systems since it is responsible for software execution in a timely manner. This book, the second of two volumes on the subject, brings together knowledge on specific topics and discusses the recent advances for some of them. It addresses foundations as well as the latest advances and findings in real-time scheduling, giving comprehensive references to important papers, but the chapters are short and not overloaded with co
Real-time systems scheduling fundamentals
Chetto, Maryline
2014-01-01
Real-time systems are used in a wide range of applications, including control, sensing, multimedia, etc. Scheduling is a central problem for these computing/communication systems since responsible of software execution in a timely manner. This book provides state of knowledge in this domain with special emphasis on the key results obtained within the last decade. This book addresses foundations as well as the latest advances and findings in Real-Time Scheduling, giving all references to important papers. But nevertheless the chapters will be short and not overloaded with confusing details.
Broadcast scheduling with data bundles
Chen, Fangfei; Pizzocaro, Diego; Johnson, Matthew P.; Bar-Noy, Amotz; Preece, Alun; La Porta, Thomas
2011-06-01
Broadcast scheduling has been extensively studied in wireless environments, where a base station broadcasts data to multiple users. Due to the sole wireless channel's limited bandwidth, only a subset of the needs may be satisfiable, and so maximizing total (weighted) throughput is a popular objective. In many realistic applications, however, data are dependent or correlated in the sense that the joint utility of a set of items is not simply the sum of their individual utilities. On the one hand, substitute data may provide overlapping information, so one piece of data item may have lower value if a second data item has already been delivered; on the other hand, complementary data are more valuable than the sum of their parts, if, for example, one data item is only useful in the presence of a second data item. In this paper, we define a data bundle to be a set of data items with possibly nonadditive joint utility, and we study a resulting broadcast scheduling optimization problem whose objective is to maximize the utility provided by the data delivered.
Cost-efficient scheduling of FAST observations
Luo, Qi; Zhao, Laiping; Yu, Ce; Xiao, Jian; Sun, Jizhou; Zhu, Ming; Zhong, Yi
2018-03-01
A cost-efficient schedule for the Five-hundred-meter Aperture Spherical radio Telescope (FAST) requires to maximize the number of observable proposals and the overall scientific priority, and minimize the overall slew-cost generated by telescope shifting, while taking into account the constraints including the astronomical objects visibility, user-defined observable times, avoiding Radio Frequency Interference (RFI). In this contribution, first we solve the problem of maximizing the number of observable proposals and scientific priority by modeling it as a Minimum Cost Maximum Flow (MCMF) problem. The optimal schedule can be found by any MCMF solution algorithm. Then, for minimizing the slew-cost of the generated schedule, we devise a maximally-matchable edges detection-based method to reduce the problem size, and propose a backtracking algorithm to find the perfect matching with minimum slew-cost. Experiments on a real dataset from NASA/IPAC Extragalactic Database (NED) show that, the proposed scheduler can increase the usage of available times with high scientific priority and reduce the slew-cost significantly in a very short time.
APGEN Scheduling: 15 Years of Experience in Planning Automation
Maldague, Pierre F.; Wissler, Steve; Lenda, Matthew; Finnerty, Daniel
2014-01-01
In this paper, we discuss the scheduling capability of APGEN (Activity Plan Generator), a multi-mission planning application that is part of the NASA AMMOS (Advanced Multi- Mission Operations System), and how APGEN scheduling evolved over its applications to specific Space Missions. Our analysis identifies two major reasons for the successful application of APGEN scheduling to real problems: an expressive DSL (Domain-Specific Language) for formulating scheduling algorithms, and a well-defined process for enlisting the help of auxiliary modeling tools in providing high-fidelity, system-level simulations of the combined spacecraft and ground support system.
Locomotive Schedule Optimization for Da-qin Heavy Haul Railway
Directory of Open Access Journals (Sweden)
Ruiye Su
2015-01-01
Full Text Available The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP hard. Therefore, we convert the multilocomotive traction problem into a single-locomotive traction problem. Then, the single-locomotive traction problem (SLTP can be converted into an assignment problem. The Hungarian algorithm is applied to solve the model and obtain the optimal locomotive schedule. We use the variance of detention time of locomotives at stations to evaluate the stability of locomotive schedule. In order to evaluate the effectiveness of the proposed optimization model, case studies for 20 kt and 30 kt heavy-loaded combined trains on Da-qin Railway are both conducted. Compared to the current schedules, the optimal schedules from the proposed models can save 62 and 47 locomotives for 20 kt and 30 kt heavy-loaded combined trains, respectively. Therefore, the effectiveness of the proposed model and its solution algorithm are both valid.
Distributed Research Project Scheduling Based on Multi-Agent Methods
Directory of Open Access Journals (Sweden)
Constanta Nicoleta Bodea
2011-01-01
Full Text Available Different project planning and scheduling approaches have been developed. The Operational Research (OR provides two major planning techniques: CPM (Critical Path Method and PERT (Program Evaluation and Review Technique. Due to projects complexity and difficulty to use classical methods, new approaches were developed. Artificial Intelligence (AI initially promoted the automatic planner concept, but model-based planning and scheduling methods emerged later on. The paper adresses the project scheduling optimization problem, when projects are seen as Complex Adaptive Systems (CAS. Taken into consideration two different approaches for project scheduling optimization: TCPSP (Time- Constrained Project Scheduling and RCPSP (Resource-Constrained Project Scheduling, the paper focuses on a multiagent implementation in MATLAB for TCSP. Using the research project as a case study, the paper includes a comparison between two multi-agent methods: Genetic Algorithm (GA and Ant Colony Algorithm (ACO.
Where do we stand with fuzzy project scheduling?
Bonnal, Pierre; Lacoste, Germain
2004-01-01
Fuzzy project scheduling has interested several researchers in the past two decades; about 20 articles have been written on this issue. Contrary to stochastic project-scheduling approaches that are used by many project schedulers, and even if the axiomatic associated to the theory of probabilities is not always compatible with decision-making situations, fuzzy project-scheduling approaches that are most suited to these situations have been kept in the academic sphere. This paper starts by recalling the differences one can observe between uncertainty and imprecision. Then most of the published research works that have been done in this field are summarized. Finally, a framework for addressing the resource-constrained fuzzy project- scheduling problem is proposed. This framework uses temporal linguistic descriptors, which might become very interesting features to the project-scheduling practitioners.
Conception of Self-Construction Production Scheduling System
Xue, Hai; Zhang, Xuerui; Shimizu, Yasuhiro; Fujimura, Shigeru
With the high speed innovation of information technology, many production scheduling systems have been developed. However, a lot of customization according to individual production environment is required, and then a large investment for development and maintenance is indispensable. Therefore now the direction to construct scheduling systems should be changed. The final objective of this research aims at developing a system which is built by it extracting the scheduling technique automatically through the daily production scheduling work, so that an investment will be reduced. This extraction mechanism should be applied for various production processes for the interoperability. Using the master information extracted by the system, production scheduling operators can be supported to accelerate the production scheduling work easily and accurately without any restriction of scheduling operations. By installing this extraction mechanism, it is easy to introduce scheduling system without a lot of expense for customization. In this paper, at first a model for expressing a scheduling problem is proposed. Then the guideline to extract the scheduling information and use the extracted information is shown and some applied functions are also proposed based on it.
Model Justified Search Algorithms for Scheduling Under Uncertainty
National Research Council Canada - National Science Library
Howe, Adele; Whitley, L. D
2008-01-01
.... We also identified plateaus as a significant barrier to superb performance of local search on scheduling and have studied several canonical discrete optimization problems to discover and model the nature of plateaus...
M-machine SDST flow shop scheduling using modified heuristic ...
African Journals Online (AJOL)
SDST) have seen an increasing attention of managers and researchers in recent years. A very restricted research has been reported on bi-criteria SDST flow shop scheduling problems dealing with due date related performance measures.
Oversubscribed Mission Scheduler Conflict Resolution System, Phase I
National Aeronautics and Space Administration — The allocation and scheduling of limited communication assets to an increasing number of satellites and other spacecraft remains a complex and challenging problem....
Robust Aircraft Squadron Scheduling in the Face of Absenteeism
National Research Council Canada - National Science Library
Gokcen, Osman B
2008-01-01
Air Force fighter aircraft squadrons the world over share a unique problem. Each requires complex training schedules coupling aircraft to pilots, the duo to missions and airspaces, and then the entire combination to a feasible time slot...
CMS Multicore Scheduling Strategy
Perez-Calero Yzquierdo, Antonio
2014-01-01
In the next years, processor architectures based on much larger numbers of cores will be most likely the model to continue Moores Law style throughput gains. This not only results in many more jobs in parallel running the LHC Run 1 era monolithic applications. Also the memory requirements of these processes push the workernode architectures to the limit. One solution is parallelizing the application itself, through forking and memory sharing or through threaded frameworks. CMS is following all of these approaches and has a comprehensive strategy to schedule multi-core jobs on the GRID based on the glideIn WMS submission infrastructure. We will present the individual components of the strategy, from special site specific queues used during provisioning of resources and implications to scheduling; to dynamic partitioning within a single pilot to allow to transition to multi-core or whole-node scheduling on site level without disallowing single-core jobs. In this presentation, we will present the experiences mad...
Distributed project scheduling at NASA: Requirements for manual protocols and computer-based support
Richards, Stephen F.
1992-01-01
The increasing complexity of space operations and the inclusion of interorganizational and international groups in the planning and control of space missions lead to requirements for greater communication, coordination, and cooperation among mission schedulers. These schedulers must jointly allocate scarce shared resources among the various operational and mission oriented activities while adhering to all constraints. This scheduling environment is complicated by such factors as the presence of varying perspectives and conflicting objectives among the schedulers, the need for different schedulers to work in parallel, and limited communication among schedulers. Smooth interaction among schedulers requires the use of protocols that govern such issues as resource sharing, authority to update the schedule, and communication of updates. This paper addresses the development and characteristics of such protocols and their use in a distributed scheduling environment that incorporates computer-aided scheduling tools. An example problem is drawn from the domain of Space Shuttle mission planning.
National Research Council Canada - National Science Library
2002-01-01
... (the JFACC Planner/Scheduler, or JPS) that supports generation of tightly linked air operations plans and schedules, as well as their adaptation in response to changing tasks and resource availability...
Using Simulation for Scheduling and Rescheduling of Batch Processes
Girish Joglekar
2017-01-01
The problem of scheduling multiproduct and multipurpose batch processes has been studied for more than 30 years using math programming and heuristics. In most formulations, the manufacturing recipes are represented by simplified models using state task network (STN) or resource task network (RTN), transfers of materials are assumed to be instantaneous, constraints due to shared utilities are often ignored, and scheduling horizons are kept small due to the limits on the problem size that can b...
Planning and Scheduling for Environmental Sensor Networks
Frank, J. D.
2005-12-01
Environmental Sensor Networks are a new way of monitoring the environment. They comprise autonomous sensor nodes in the environment that record real-time data, which is retrieved, analyzed, integrated with other data sets (e.g. satellite images, GIS, process models) and ultimately lead to scientific discoveries. Sensor networks must operate within time and resource constraints. Sensors have limited onboard memory, energy, computational power, communications windows and communications bandwidth. The value of data will depend on when, where and how it was collected, how detailed the data is, how long it takes to integrate the data, and how important the data was to the original scientific question. Planning and scheduling of sensor networks is necessary for effective, safe operations in the face of these constraints. For example, power bus limitations may preclude sensors from simultaneously collecting data and communicating without damaging the sensor; planners and schedulers can ensure these operations are ordered so that they do not happen simultaneously. Planning and scheduling can also ensure best use of the sensor network to maximize the value of collected science data. For example, if data is best recorded using a particular camera angle but it is costly in time and energy to achieve this, planners and schedulers can search for times when time and energy are available to achieve the optimal camera angle. Planning and scheduling can handle uncertainty in the problem specification; planners can be re-run when new information is made available, or can generate plans that include contingencies. For example, if bad weather may prevent the collection of data, a contingent plan can check lighting conditions and turn off data collection to save resources if lighting is not ideal. Both mobile and immobile sensors can benefit from planning and scheduling. For example, data collection on otherwise passive sensors can be halted to preserve limited power and memory
Scheduling Broadcasts in a Network of Timelines
Manzoor, Emaad A.
2015-05-12
Broadcasts and timelines are the primary mechanism of information exchange in online social platforms today. Services like Facebook, Twitter and Instagram have enabled ordinary people to reach large audiences spanning cultures and countries, while their massive popularity has created increasingly competitive marketplaces of attention. Timing broadcasts to capture the attention of such geographically diverse audiences has sparked interest from many startups and social marketing gurus. However, formal study is lacking on both the timing and frequency problems. In this thesis, we introduce, motivate and solve the broadcast scheduling problem of specifying the timing and frequency of publishing content to maximise the attention received. We validate and quantify three interacting behavioural phenomena to parametrise social platform users: information overload, bursty circadian rhythms and monotony aversion, which is defined here for the first time. Our analysis of the influence of monotony refutes the common assumption that posts on social network timelines are consumed piecemeal independently. Instead, we reveal that posts are consumed in chunks, which has important consequences for any future work considering human behaviour over social network timelines. Our quantification of monotony aversion is also novel, and has applications to problems in various domains such as recommender list diversification, user satiation and variety-seeking consumer behaviour. Having studied the underlying behavioural phenomena, we link schedules, timelines, attention and behaviour by formalising a timeline information exchange process. Our formulation gives rise to a natural objective function that quantifies the expected collective attention an arrangement of posts on a timeline will receive. We apply this formulation as a case-study on real-data from Twitter, where we estimate behavioural parameters, calculate the attention potential for different scheduling strategies and, using the
Advance Resource Provisioning in Bulk Data Scheduling
Energy Technology Data Exchange (ETDEWEB)
Balman, Mehmet
2012-10-01
Today?s scientific and business applications generate mas- sive data sets that need to be transferred to remote sites for sharing, processing, and long term storage. Because of increasing data volumes and enhancement in current net- work technology that provide on-demand high-speed data access between collaborating institutions, data handling and scheduling problems have reached a new scale. In this paper, we present a new data scheduling model with ad- vance resource provisioning, in which data movement operations are defined with earliest start and latest comple- tion times. We analyze time-dependent resource assign- ment problem, and propose a new methodology to improve the current systems by allowing researchers and higher-level meta-schedulers to use data-placement as-a-service, so they can plan ahead and submit transfer requests in advance. In general, scheduling with time and resource conflicts is NP-hard. We introduce an efficient algorithm to organize multiple requests on the fly, while satisfying users? time and resource constraints. We successfully tested our algorithm in a simple benchmark simulator that we have developed, and demonstrated its performance with initial test results.
Column generation approaches to ship scheduling with flexible cargo sizes
DEFF Research Database (Denmark)
Brønmo, Geir; Nygreen, Bjørn; Lysgaard, Jens
We present a Dantzig-Wolfe procedure for the ship scheduling problem with flexible cargo sizes. This problem is similar to the well-known pickup and delivery problem with time windows, but the cargo sizes are defined by an interval instead of a fixed value. We show that the introduction of flexible...
NRC comprehensive records disposition schedule
International Nuclear Information System (INIS)
1982-07-01
Effective January 1, 1982, NRC will institute records retention and disposal practices in accordance with the approved Comprehensive Records Disposition Schedule (CRDS). CRDS is comprised of NRC Schedules (NRCS) 1 to 4 which apply to the agency's program or substantive records and General Records Schedules (GRS) 1 to 22 which apply to housekeeping or facilitative records. The schedules are assembled functionally/organizationally to facilitate their use. Preceding the records descriptions and disposition instructions for both NRCS and GRS, there are brief statements on the organizational units which accumulate the records in each functional area, and other information regarding the schedules' applicability
International Nuclear Information System (INIS)
Cardoso, G.; Stadler, M.; Bozchalui, M.C.; Sharma, R.; Marnay, C.; Barbosa-Póvoa, A.; Ferrão, P.
2014-01-01
The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained using the stochastic formulation of the problem. - Highlights: • This paper introduces a new EV aggregator model in the DER-CAM model and expands it with a stochastic formulation. • The model is used to analyze the impact of EVs in DER investment decisions in a large office building. • The uncertainty in EV driving patterns is considered through scenarios based on data from a daily commute driving survey. • Results indicate that EVs have a significant impact in optimal DER decisions, particularly when looking at short payback periods. • Furthermore, results indicate that uncertainty in EV driving schedules has little impact on DER investment decisions
Muñoz, Gonzalo; Espinoza, Daniel; Goycoolea, Marcos; Moreno, Eduardo; Queyranne, Maurice; Rivera, Orlando
2016-01-01
We study a Lagrangian decomposition algorithm recently proposed by Dan Bienstock and Mark Zuckerberg for solving the LP relaxation of a class of open pit mine project scheduling problems. In this study we show that the Bienstock-Zuckerberg (BZ) algorithm can be used to solve LP relaxations corresponding to a much broader class of scheduling problems, including the well-known Resource Constrained Project Scheduling Problem (RCPSP), and multi-modal variants of the RCPSP that consider batch proc...
Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes
Directory of Open Access Journals (Sweden)
Damon Petersen
2017-12-01
Full Text Available A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP dynamic optimization problems and mixed-integer linear programming (MILP problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation’s closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios presented. Computational performance is sufficiently light to enable online operation in a dual-loop feedback structure.
Using the principles of circadian physiology enhances shift schedule design
International Nuclear Information System (INIS)
Connolly, J.J.; Moore-Ede, M.C.
1987-01-01
Nuclear power plants must operate 24 h, 7 days a week. For the most part, shift schedules currently in use at nuclear power plants have been designed to meet operational needs without considering the biological clocks of the human operators. The development of schedules that also take circadian principles into account is a positive step that can be taken to improve plant safety by optimizing operator alertness. These schedules reduce the probability of human errors especially during backshifts. In addition, training programs that teach round-the-clock workers how to deal with the problems of shiftwork can help to optimize performance and alertness. These programs teach shiftworkers the underlying causes of the sleep problems associated with shiftwork and also provide coping strategies for improving sleep and dealing with the transition between shifts. When these training programs are coupled with an improved schedule, the problems associated with working round-the-clock can be significantly reduced
Meyer, C.M.; Kok, A.L.; Kopfer, H.; Schutten, Johannes M.J.
2009-01-01
We analyze the problem of combined vehicle routing and break scheduling from a distributed decision making perspective. The problem of combined vehicle routing and break scheduling can be defined as the problem of finding vehicle routes to serve a set of customers such that a cost criterion is
A tabu search algorithm for scheduling a single robot in a job-shop environment
Hurink, Johann L.; Knust, S.
1999-01-01
We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time
A tabu search algorithm for scheduling a single robot in a job-shop environment
Hurink, Johann L.; Knust, Sigrid
2002-01-01
We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time
Directory of Open Access Journals (Sweden)
Geórgia Pereira Silveira Souza
2011-01-01
realidad institucional, buscando posibles acciones resolutivas frente a los problemas identificadosThe objective of this study was to discuss the complexity of preparing the monthly nursing schedule during the Nursing Administration course, in an inpatient unit of a public teaching hospital, in São Paulo. We started from the position that the preparation of a monthly schedule consisted of a series of coordinated actions which required: recognition of staff, collection of data needed to characterize the clinical reality, comparison of those data with the literature, and development of a proposal for action, which we would discuss with the nurses in the unit. This experience provided the possibility to reflect on empowerment and the understanding of these professionals about the factors involved in the implementation of this management activity. It allowed us, as well, to demonstrate the importance of diagnosing the needs of the unit and comparing it with the institutional reality, with a view toward possible actions to resolve the identified problems
Dynamic scheduling and analysis of real time systems with multiprocessors
Directory of Open Access Journals (Sweden)
M.D. Nashid Anjum
2016-08-01
Full Text Available This research work considers a scenario of cloud computing job-shop scheduling problems. We consider m realtime jobs with various lengths and n machines with different computational speeds and costs. Each job has a deadline to be met, and the profit of processing a packet of a job differs from other jobs. Moreover, considered deadlines are either hard or soft and a penalty is applied if a deadline is missed where the penalty is considered as an exponential function of time. The scheduling problem has been formulated as a mixed integer non-linear programming problem whose objective is to maximize net-profit. The formulated problem is computationally hard and not solvable in deterministic polynomial time. This research work proposes an algorithm named the Tube-tap algorithm as a solution to this scheduling optimization problem. Extensive simulation shows that the proposed algorithm outperforms existing solutions in terms of maximizing net-profit and preserving deadlines.
International Nuclear Information System (INIS)
Anon.
1998-01-01
The first phase of the Le Nordais wind farm project in the Gaspe Peninsula in Quebec is on schedule. It was announced that the project's first turbines will be turning by September 1998. Hydro-Quebec has agreed to buy power from the 100 MW wind farm. The Le Nordais consortium plans to have 76,750 kW turbines in service in Cap-Chat by December 1998. Many of the foundations for the towers are poured and a substation is under construction. The turbines that are currently in use come from Denmark, but 20 of the 76 turbines being slated for installation this year will come from NEG Micon Canada Inc.'s assembly plant in Quebec. The Quebec government is providing a $5.6 million grant for their production and for turbine assembly in Quebec. During phase two, an additional 57 turbines will be installed in Matane by the end of 1999. 1 fig
Manufacturing scheduling systems an integrated view on models, methods and tools
Framinan, Jose M; Ruiz García, Rubén
2014-01-01
The book is devoted to the problem of manufacturing scheduling, which is the efficient allocation of jobs (orders) over machines (resources) in a manufacturing facility. It offers a comprehensive and integrated perspective on the different aspects required to design and implement systems to efficiently and effectively support manufacturing scheduling decisions. Obtaining economic and reliable schedules constitutes the core of excellence in customer service and efficiency in manufacturing operations. Therefore, scheduling forms an area of vital importance for competition in manufacturing companies. However, only a fraction of scheduling research has been translated into practice, due to several reasons. First, the inherent complexity of scheduling has led to an excessively fragmented field in which different sub problems and issues are treated in an independent manner as goals themselves, therefore lacking a unifying view of the scheduling problem. Furthermore, mathematical brilliance and elegance has sometime...
Joint opportunistic scheduling and network coding for bidirectional relay channel
Shaqfeh, Mohammad
2013-07-01
In this paper, we consider a two-way communication system in which two users communicate with each other through an intermediate relay over block-fading channels. We investigate the optimal opportunistic scheduling scheme in order to maximize the long-term average transmission rate in the system assuming symmetric information flow between the two users. Based on the channel state information, the scheduler decides that either one of the users transmits to the relay, or the relay transmits to a single user or broadcasts to both users a combined version of the two users\\' transmitted information by using linear network coding. We obtain the optimal scheduling scheme by using the Lagrangian dual problem. Furthermore, in order to characterize the gains of network coding and opportunistic scheduling, we compare the achievable rate of the system versus suboptimal schemes in which the gains of network coding and opportunistic scheduling are partially exploited. © 2013 IEEE.
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
Directory of Open Access Journals (Sweden)
Imam Ahmad Ashari
2016-11-01
Full Text Available Scheduling problems at the university is a complex type of scheduling problems. The scheduling process should be carried out at every turn of the semester's. The core of the problem of scheduling courses at the university is that the number of components that need to be considered in making the schedule, some of the components was made up of students, lecturers, time and a room with due regard to the limits and certain conditions so that no collision in the schedule such as mashed room, mashed lecturer and others. To resolve a scheduling problem most appropriate technique used is the technique of optimization. Optimization techniques can give the best results desired. Metaheuristic algorithm is an algorithm that has a lot of ways to solve the problems to the very limit the optimal solution. In this paper, we use a genetic algorithm and ant colony optimization algorithm is an algorithm metaheuristic to solve the problem of course scheduling. The two algorithm will be tested and compared to get performance is the best. The algorithm was tested using data schedule courses of the university in Semarang. From the experimental results we conclude that the genetic algorithm has better performance than the ant colony optimization algorithm in solving the case of course scheduling.
NRC comprehensive records disposition schedule
International Nuclear Information System (INIS)
1992-03-01
Title 44 United States Code, ''Public Printing and Documents,'' regulations cited in the General Services Administration's (GSA) ''Federal Information Resources Management Regulations'' (FIRMR), Part 201-9, ''Creation, Maintenance, and Use of Records,'' and regulation issued by the National Archives and Records Administration (NARA) in 36 CFR Chapter XII, Subchapter B, ''Records Management,'' require each agency to prepare and issue a comprehensive records disposition schedule that contains the NARA approved records disposition schedules for records unique to the agency and contains the NARA's General Records Schedules for records common to several or all agencies. The approved records disposition schedules specify the appropriate duration of retention and the final disposition for records created or maintained by the NRC. NUREG-0910, Rev. 2, contains ''NRC's Comprehensive Records Disposition Schedule,'' and the original authorized approved citation numbers issued by NARA. Rev. 2 totally reorganizes the records schedules from a functional arrangement to an arrangement by the host office. A subject index and a conversion table have also been developed for the NRC schedules to allow staff to identify the new schedule numbers easily and to improve their ability to locate applicable schedules
Automated Long - Term Scheduling for the SOFIA Airborne Observatory
Civeit, Thomas
2013-01-01
The NASA Stratospheric Observatory for Infrared Astronomy (SOFIA) is a joint US/German project to develop and operate a gyro-stabilized 2.5-meter telescope in a Boeing 747SP. SOFIA's first science observations were made in December 2010. During 2011, SOFIA accomplished 30 flights in the "Early Science" program as well as a deployment to Germany. The new observing period, known as Cycle 1, is scheduled to begin in 2012. It includes 46 science flights grouped in four multi-week observing campaigns spread through a 13-month span. Automation of the flight scheduling process offers a major challenge to the SOFIA mission operations. First because it is needed to mitigate its relatively high cost per unit observing time compared to space-borne missions. Second because automated scheduling techniques available for ground-based and space-based telescopes are inappropriate for an airborne observatory. Although serious attempts have been made in the past to solve part of the problem, until recently mission operations staff was still manually scheduling flights. We present in this paper a new automated solution for generating SOFIA long-term schedules that will be used in operations from the Cycle 1 observing period. We describe the constraints that should be satisfied to solve the SOFIA scheduling problem in the context of real operations. We establish key formulas required to efficiently calculate the aircraft course over ground when evaluating flight schedules. We describe the foundations of the SOFIA long-term scheduler, the constraint representation, and the random search based algorithm that generates observation and instrument schedules. Finally, we report on how the new long-term scheduler has been used in operations to date.
2017-05-03
The Administrator of the Drug Enforcement Administration is issuing this temporary scheduling order to schedule the synthetic opioid, N-(4-fluorophenyl)-N-(1-phenethylpiperidin-4-yl)isobutyramide (4-fluoroisobutyryl fentanyl or para-fluoroisobutyryl fentanyl), and its isomers, esters, ethers, salts and salts of isomers, esters, and ethers, into schedule I pursuant to the temporary scheduling provisions of the Controlled Substances Act. This action is based on a finding by the Administrator that the placement of 4-fluoroisobutyryl fentanyl into schedule I of the Controlled Substances Act is necessary to avoid an imminent hazard to the public safety. As a result of this order, the regulatory controls and administrative, civil, and criminal sanctions applicable to schedule I controlled substances will be imposed on persons who handle (manufacture, distribute, reverse distribute, import, export, engage in research, conduct instructional activities or chemical analysis, or possess), or propose to handle, 4-fluoroisobutyryl fentanyl.
An Automatic Course Scheduling Approach Using Instructors' Preferences
Directory of Open Access Journals (Sweden)
Hossam Faris
2012-03-01
Full Text Available University Courses Timetabling problem has been extensively researched in the last decade. Therefore, numerous approaches were proposed to solve UCT problem. This paper proposes a new approach to process a sequence of meetings between instructors, rooms, and students in predefined periods of time with satisfying a set of constraints divided in variety of types. In addition, this paper proposes new representation for courses timetabling and conflict-free for each time slot by mining instructor preferences from previous schedules to avoid undesirable times for instructors. Experiments on different real data showed the approach achieved increased satisfaction degree for each instructor and gives feasible schedule with satisfying all hard constraints in construction operation. The generated schedules have high satisfaction degrees comparing with schedules created manually. The research conducts experiments on collected data gathered from the computer science department and other related departments in Jordan University of Science and Technology- Jordan.
Using Integer Programming for Airport Service Planning in Staff Scheduling
Directory of Open Access Journals (Sweden)
W.H. Ip
2010-09-01
Full Text Available Reliability and safety in flight is extremely necessary and that depend on the adoption of proper maintenance system. Therefore, it is essential for aircraft maintenance companies to perform the manpower scheduling efficiently. One of the objectives of this paper is to provide an Integer Programming approach to determine the optimal solutions to aircraft maintenance planning and scheduling and hence the planning and scheduling processes can become more efficient and effective. Another objective is to develop a set of computational schedules for maintenance manpower to cover all scheduled flights. In this paper, a sequential methodology consisting of 3 stages is proposed. They are initial maintenance demand schedule, the maintenance pairing and the maintenance group(s assignment. Since scheduling would split up into different stages, different mathematical techniques have been adopted to cater for their own problem characteristics. Microsoft Excel would be used. Results from the first stage and second stage would be inputted into integer programming model using Microsoft Excel Solver to find the optimal solution. Also, Microsoft Excel VBA is used for devising a scheduling system in order to reduce the manual process and provide a user friendly interface. For the results, all can be obtained optimal solution and the computation time is reasonable and acceptable. Besides, the comparison of the peak time and non-peak time is discussed.
Engineering schedule control of nuclear power project planning and management
International Nuclear Information System (INIS)
Meng Hao
2014-01-01
Nuclear power design is the important part of project management of nuclear power project, it is the way to control the project organization, design schedule, design progress, design quality and cost control. The good schedule system and control is the key to the success for the project. It is also analyzed the problem during the project, by using some theory and analyze the project structure, design schedule management, IED and document management and interface management propose some new idea for better improve the design management to finally better improve the management quality and efficiency. (author)
Schedulability of Herschel revisited using statistical model checking
DEFF Research Database (Denmark)
David, Alexandre; Larsen, Kim Guldstrand; Legay, Axel
2015-01-01
to obtain some guarantee on the (un)schedulability of the model even in the presence of undecidability. Two methods are considered: symbolic model checking and statistical model checking. Since the model uses stop-watches, the reachability problem becomes undecidable so we are using an over......-approximation technique. We can safely conclude that the system is schedulable for varying values of BCET. For the cases where deadlines are violated, we use polyhedra to try to confirm the witnesses. Our alternative method to confirm non-schedulability uses statistical model-checking (SMC) to generate counter...
Routing and scheduling and fleet management for liner shipping
DEFF Research Database (Denmark)
Kjeldsen, Karina Hjortshøj
2009-01-01
The problem of routing, scheduling and fleet management in global liner shipping is presented. The developed model incorporates the ships' speed as a decision variable. Furthermore, the model must be able to handle problems of the size and complexity experienced by the global liner shipping compa...
The Price of Anarchy for Minsum Related Machine Scheduling
Hoeksma, R.P.; Uetz, Marc Jochen
We address the classical uniformly related machine scheduling problem with minsum objective. The problem is solvable in polynomial time by the algorithm of Horowitz and Sahni. In that solution, each machine sequences its jobs shortest first. However when jobs may choose the machine on which they are
The price of anarchy for minsum related machine scheduling
Hoeksma, R.P.; Uetz, Marc Jochen; Solis-Oba, R; Persiano, G
2012-01-01
We address the classical uniformly related machine scheduling problem with minsum objective. The problem is solvable in polynomial time by the algorithm of Horowitz and Sahni. In that solution, each machine sequences its jobs shortest first. However when jobs may choose the machine on which they are
Learning Search Control Knowledge for Deep Space Network Scheduling
Gratch, Jonathan; Chien, Steve; DeJong, Gerald
1993-01-01
While the general class of most scheduling problems is NP-hard in worst-case complexity, in practice, for specific distributions of problems and constraints, domain-specific solutions have been shown to perform in much better than exponential time.
Scheduling technicians and tasks in a telecommunications company
DEFF Research Database (Denmark)
Cordeau, J. F.; Laporte, G.; Pasin, F.
2010-01-01
This paper proposes a construction heuristic and an adaptive large neighborhood search heuristic for the technician and task scheduling problem arising in a large telecommunications company. This problem was solved within the framework of the 2007 challenge set up by the French Operational Research...
Staff Scheduling within the Retail Business in Denmark
DEFF Research Database (Denmark)
Leedgaard, Jesper; Mortensen, Kim H.; Larsen, Allan
2002-01-01
as a Mixed Integer Problem. The retail staff scheduling problem is solved using the metaheuristic {\\$\\backslash\\$it Simulated Annealing}. The heuristic is implemented by modifying the original MIP model. Some of the constraints defined in the MIP are relaxed, entered into the objective function and weighted...
A solution approach for dynamic vehicle and crew scheduling
D. Huisman (Dennis); A.P.M. Wagelmans (Albert)
2004-01-01
textabstractIn this paper, we discuss the dynamic vehicle and crew scheduling problem and we propose a solution approach consisting of solving a sequence of optimization problems. Furthermore, we explain why it is useful to consider such a dynamic approach and compare it with a static one. Moreover,
An improved formulation of the underground mine scheduling ...
African Journals Online (AJOL)
The use of mixed integer programming is a modelling approach well suited to formulate the mine scheduling optimisation problem for both open pit and underground mining. The resolution applied for discretising the problem, however, has a direct eect on both the level of selectivity that can be applied to improve protability, ...
Nontraditional work schedules for pharmacists.
Mahaney, Lynnae; Sanborn, Michael; Alexander, Emily
2008-11-15
Nontraditional work schedules for pharmacists at three institutions are described. The demand for pharmacists and health care in general continues to increase, yet significant material changes are occurring in the pharmacy work force. These changing demographics, coupled with historical vacancy rates and turnover trends for pharmacy staff, require an increased emphasis on workplace changes that can improve staff recruitment and retention. At William S. Middleton Memorial Veterans Affairs Hospital in Madison, Wisconsin, creative pharmacist work schedules and roles are now mainstays to the recruitment and retention of staff. The major challenge that such scheduling presents is the 8 hours needed to prepare a six-week schedule. Baylor Medical Center at Grapevine in Dallas, Texas, has a total of 45 pharmacy employees, and slightly less than half of the 24.5 full-time-equivalent staff work full-time, with most preferring to work one, two, or three days per week. As long as the coverage needs of the facility are met, Envision Telepharmacy in Alpine, Texas, allows almost any scheduling arrangement preferred by individual pharmacists or the pharmacist group covering the facility. Staffing involves a great variety of shift lengths and intervals, with shifts ranging from 2 to 10 hours. Pharmacy leaders must be increasingly aware of opportunities to provide staff with unique scheduling and operational enhancements that can provide for a better work-life balance. Compressed workweeks, job-sharing, and team scheduling were the most common types of alternative work schedules implemented at three different institutions.
Scheduling in the operating theatre.
Rose, M. B.; Davies, D. C.
1984-01-01
The effect of scheduling on the use of operating theatre time has been studied. Scheduling involved determining the average length of common operations and fitting them into the calculated available operating time. The technique has been shown to reduce significantly the variation in length of operating sessions, and it ensures the best use of available operating time.
TECHNICAL COORDINATION SCHEDULE & INTEGRATION
W. Zeuner
Introduction The endgame of CMS installation in the underground cavern is in full swing, with several major milestones having been passed since the last CMS week. The Tracker was installed inside the Vactank just before the CERN end-of-year shutdown. Shortly after the reopening in 2008, the two remaining endcap disks, YE-2 and YE-1, were lowered, marking the completion of eight years of assembly in the surface building SX5. The remaining tasks, before the detector can be closed for the Cosmic Run At Four Tesla (CRAFT), are the installation of the thermal shields, the cabling of the negative endcap, the cabling of the tracker and the beam pipe installation. In addition to these installation tasks, a test closure of the positive endcap is planned just before the installation of the central beam pipe. The schedule is tight and complicated but the goal to close CMS by the end of May for a cosmic test with magnetic field remains feasible. Safety With all large components now being underground, the shortage...
Publications Section, DG-CO Group
2011-01-01
The final edition (Nos 51-52/2011 and 1-2-3/2012) of the Bulletin this year will be published on Friday 16 December and will cover events at CERN from 19 December 2011 to 19 January 2012. Announcements for publication in this issue should reach the Communication Group or the Staff Association, as appropriate, by noon on Tuesday 13 December. Bulletin publication schedule for 2012 The table below lists the 2012 publication dates for the paper version of the Bulletin and the corresponding deadlines for the submission of announcements. Please note that all announcements must be submitted by 12.00 noon on Tuesdays at the latest. Bulletin No. Week number Submission of announcements (before 12.00 midday) Bulletin Web version Bulletin Printed version 4-5 Tuesday 17 January Fridays 20 and 27 January Wednesday25 January 6-7 Tuesday 31 January Fridays 3 and 10 February Wednesday 8 February 8-9 Tuesday 14 February Fridays 17 and 24 february Wednesday 22 Februa...
A Network Simulation Tool for Task Scheduling
Directory of Open Access Journals (Sweden)
Ondřej Votava
2012-01-01
Full Text Available Distributed computing may be looked at from many points of view. Task scheduling is the viewpoint, where a distributed application can be described as a Directed Acyclic Graph and every node of the graph is executed independently. There are, however, data dependencies and the nodes have to be executed in a specified order. Hence the parallelism of the execution is limited. The scheduling problem is difficult and therefore heuristics are used. However, many inaccuracies are caused by the model used for the system, in which the heuristics are being tested. In this paper we present a tool for simulating the execution of the distributed application on a “real” computer network, and try to tell how the executionis influenced compared to the model.
Artificial intelligence for the CTA Observatory scheduler
Colomé, Josep; Colomer, Pau; Campreciós, Jordi; Coiffard, Thierry; de Oña, Emma; Pedaletti, Giovanna; Torres, Diego F.; Garcia-Piquer, Alvaro
2014-08-01
The Cherenkov Telescope Array (CTA) project will be the next generation ground-based very high energy gamma-ray instrument. The success of the precursor projects (i.e., HESS, MAGIC, VERITAS) motivated the construction of this large infrastructure that is included in the roadmap of the ESFRI projects since 2008. CTA is planned to start the construction phase in 2015 and will consist of two arrays of Cherenkov telescopes operated as a proposal-driven open observatory. Two sites are foreseen at the southern and northern hemispheres. The CTA observatory will handle several observation modes and will have to operate tens of telescopes with a highly efficient and reliable control. Thus, the CTA planning tool is a key element in the control layer for the optimization of the observatory time. The main purpose of the scheduler for CTA is the allocation of multiple tasks to one single array or to multiple sub-arrays of telescopes, while maximizing the scientific return of the facility and minimizing the operational costs. The scheduler considers long- and short-term varying conditions to optimize the prioritization of tasks. A short-term scheduler provides the system with the capability to adapt, in almost real-time, the selected task to the varying execution constraints (i.e., Targets of Opportunity, health or status of the system components, environment conditions). The scheduling procedure ensures that long-term planning decisions are correctly transferred to the short-term prioritization process for a suitable selection of the next task to execute on the array. In this contribution we present the constraints to CTA task scheduling that helped classifying it as a Flexible Job-Shop Problem case and finding its optimal solution based on Artificial Intelligence techniques. We describe the scheduler prototype that uses a Guarded Discrete Stochastic Neural Network (GDSN), for an easy representation of the possible long- and short-term planning solutions, and Constraint
Astronaut Office Scheduling System Software
Brown, Estevancio
2010-01-01
AOSS is a highly efficient scheduling application that uses various tools to schedule astronauts weekly appointment information. This program represents an integration of many technologies into a single application to facilitate schedule sharing and management. It is a Windows-based application developed in Visual Basic. Because the NASA standard office automation load environment is Microsoft-based, Visual Basic provides AO SS developers with the ability to interact with Windows collaboration components by accessing objects models from applications like Outlook and Excel. This also gives developers the ability to create newly customizable components that perform specialized tasks pertaining to scheduling reporting inside the application. With this capability, AOSS can perform various asynchronous tasks, such as gathering/ sending/ managing astronauts schedule information directly to their Outlook calendars at any time.
Using a vision cognitive algorithm to schedule virtual machines
Directory of Open Access Journals (Sweden)
Zhao Jiaqi
2014-09-01
Full Text Available Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption
Airport Ground Staff Scheduling
DEFF Research Database (Denmark)
Clausen, Tommy
Modern airports are centers of transportation that service a large number of aircraft and passengers every day. To facilitate this large volume of transportation, airports are subject to many logistical and decision problems that must continuously be solved to make sure each flight and passenger ...
Fundamentals of Shiftwork Scheduling
2006-04-01
menstrual irregularities, colds, flu, weight gain, and cardiovascular problems than day workers. It is not known whether shiftwork-related stressors or...absorbed from the stomach, its half-life in the blood stream is about three to five hours. A cup (not a mug) of coffee provides about 100 mg of caffeine
Real-Time Scheduling Approaches for Vehicle-Based Internal Transport Systems
T. Le-Anh (Tuan); M.B.M. de Koster (René)
2004-01-01
textabstractIn this paper, we study the problem of scheduling and dispatching vehicles in vehicle-based internal transport systems within warehouses and production facilities. We develop and use two rolling horizon policies to solve real-time vehicle scheduling problems. To solve static instances of
Autonomous power system: Integrated scheduling
Ringer, Mark J.
1992-01-01
The Autonomous Power System (APS) project at NASA Lewis Research Center is designed to demonstrate the abilities of integrated intelligent diagnosis, control and scheduling techniques to space power distribution hardware. The project consists of three elements: the Autonomous Power Expert System (APEX) for fault diagnosis, isolation, and recovery (FDIR), the Autonomous Intelligent Power Scheduler (AIPS) to determine system configuration, and power hardware (Brassboard) to simulate a space-based power system. Faults can be introduced into the Brassboard and in turn, be diagnosed and corrected by APEX and AIPS. The Autonomous Intelligent Power Scheduler controls the execution of loads attached to the Brassboard. Each load must be executed in a manner that efficiently utilizes available power and satisfies all load, resource, and temporal constraints. In the case of a fault situation on the Brassboard, AIPS dynamically modifies the existing schedule in order to resume efficient operation conditions. A database is kept of the power demand, temporal modifiers, priority of each load, and the power level of each source. AIPS uses a set of heuristic rules to assign start times and resources to each load based on load and resource constraints. A simple improvement engine based upon these heuristics is also available to improve the schedule efficiency. This paper describes the operation of the Autonomous Intelligent Power Scheduler as a single entity, as well as its integration with APEX and the Brassboard. Future plans are discussed for the growth of the Autonomous Intelligent Power Scheduler.
Optimal physicians schedule in an Intensive Care Unit
Hidri, L.; Labidi, M.
2016-05-01
In this paper, we consider a case study for the problem of physicians scheduling in an Intensive Care Unit (ICU). The objective is to minimize the total overtime under complex constraints. The considered ICU is composed of three buildings and the physicians are divided accordingly into six teams. The workload is assigned to each team under a set of constraints. The studied problem is composed of two simultaneous phases: composing teams and assigning the workload to each one of them. This constitutes an additional major hardness compared to the two phase's process: composing teams and after that assigning the workload. The physicians schedule in this ICU is used to be done manually each month. In this work, the studied physician scheduling problem is formulated as an integer linear program and solved optimally using state of the art software. The preliminary experimental results show that 50% of the overtime can be saved.
Scheduling multirobot operations in manufacturing by truncated Petri nets
Chen, Qin; Luh, J. Y.
1995-08-01
Scheduling of operational sequences in manufacturing processes is one of the important problems in automation. Methods of applying Petri nets to model and analyze the problem with constraints on precedence relations, multiple resources allocation, etc. have been available in literature. Searching for an optimum schedule can be implemented by combining the branch-and-bound technique with the execution of the timed Petri net. The process usually produces a large Petri net which is practically not manageable. This disadvantage, however, can be handled by a truncation technique which divides the original large Petri net into several smaller size subnets. The complexity involved in the analysis of each subnet individually is greatly reduced. However, when the locally optimum schedules of the resulting subnets are combined together, it may not yield an overall optimum schedule for the original Petri net. To circumvent this problem, algorithms are developed based on the concepts of Petri net execution and modified branch-and-bound process. The developed technique is applied to a multi-robot task scheduling problem of the manufacturing work cell.
Directory of Open Access Journals (Sweden)
A. Stawowy
2012-04-01
Full Text Available Mathematical programming, constraint programming and computational intelligence techniques, presented in the literature in the field of operations research and production management, are generally inadequate for planning real-life production process. These methods are in fact dedicated to solving the standard problems such as shop floor scheduling or lot-sizing, or their simple combinations such as scheduling with batching. Whereas many real-world production planning problems require the simultaneous solution of several problems (in addition to task scheduling and lot-sizing, the problems such as cutting, workforce scheduling, packing and transport issues, including the problems that are difficult to structure. The article presents examples and classification of production planning and scheduling systems in the foundry industry described in the literature, and also outlines the possible development directions of models and algorithms used in such systems.
International Nuclear Information System (INIS)
Sajid, Mohammad; Raza, Zahid
2017-01-01
The problem of optimal scheduling of precedence-constrained jobs as well as finding the Pareto-optimal sets for multi objective scheduling problem have been proven to be nondeterministic polynomial time (NP)-complete. The growing consumption of energy has compelled the researchers to consider energy consumption as an important parameter along with other parameters in multi-objective scheduling problem. Accordingly, many energy-aware precedence-constraints scheduling algorithms have been reported in the literature. Most of the algorithms have a limitation of treating this problem as a single objective optimization problem modelling with deterministic execution times rather than stochastic execution times. This work proposes energy-aware stochastic scheduler to schedule the batch of precedence-constrained jobs on dynamic voltage frequency scaling-enabled processors in order to optimize the energy consumption and the turnaround time. The execution and inter-communication times are stochastic which are drawn from independent probability distributions. A novel encoding for batch of precedence-constrained jobs, stochastic turnaround time and energy models are also proposed. Experimental results show that, compared with other algorithms, the proposed scheduler offers reduced turnaround time and reduced energy consumption. - Highlights: • This paper reports stochastic scheduler for energy management of data centres. • Novel encoding, turnaround time and energy consumption models are proposed. • Clark's equations are used to compute the turnaround time and energy consumption. • The proposed scheduler offers reduced turnaround time as well as energy consumption.
Immunization Schedules for Infants and Children
... ACIP Vaccination Recommendations Why Immunize? Vaccines: The Basics Immunization Schedule for Infants and Children (Birth through 6 ... any questions please talk to your doctor. 2018 Immunization Schedule Recommended Vaccinations for Infants and Children Schedule ...
Immunization Schedules for Preteens and Teens
... Vaccines: The Basics Immunization Schedule for Preteens and Teens (7 through 18 Years) Recommend on Facebook Tweet ... 2018 Immunization Schedule Recommended Vaccinations for Preteens and Teens Schedule for preteens and teens (7 through 18 ...
Scheduling Spitzer: The SIRPASS Story
Mittman, David S.; Hawkins, Robert
2013-01-01
NASA's Spitzer Space Telescope was launched on August 25, 2003 from Florida's Cape Canaveral Air Force Base. Drifting in a unique Earth-trailing orbit around the Sun, Spitzer sees an optically invisible universe dominated by dust and stars. Since 1997, the Spitzer Integrated Resource Planning and Scheduling System (SIRPASS) has helped produce spacecraft activity plans for the Spitzer Space Telescope. SIRPASS is used by members of the Observatory Planning and Scheduling Team to plan, schedule and sequence the Telescope from data made available to them from the science and engineering community. Because of the volume of data that needs to be scheduled, SIRPASS offers a variety of automated assistants to aid in this task. This paper will describe the functional elements of the SIRPASS software system -- emphasizing the role that automation plays in the system -- and will highlight lessons learned for the software developer from a decade of Spitzer Space Telescope operations experience.
Executive Schedule C System (ESCS)
Office of Personnel Management — Used to store information on Federal employees in the Senior Executive Service (SES) and appointed employees in the Schedule C System. Every four years, just after...
General Services Administration — Schedule Sales Query presents sales volume figures as reported to GSA by contractors. The reports are generated as quarterly reports for the current year and the...
Multiagent scheduling models and algorithms
Agnetis, Alessandro; Gawiejnowicz, Stanisław; Pacciarelli, Dario; Soukhal, Ameur
2014-01-01
This book presents multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. It discusses complexity results, approximation schemes, heuristics and exact algorithms.
Estimating exponential scheduling preferences
DEFF Research Database (Denmark)
Hjorth, Katrine; Börjesson, Maria; Engelson, Leonid
2015-01-01
distributed independent random variables: Assuming smooth preferences; this holds only for specifications with a constant marginal utility of time at the origin and an exponential or affine marginal utility of time at the destination. We apply a generalized version of this model to stated preference data...... utility of being at the origin. Another issue is that models with the exponential marginal utility formulation suffer from empirical identification problems. Though our results are not decisive, they partly support the constant-affine specification, in which the value of travel time variability...
Construction schedules slack time minimizing
Krzemiński, Michał
2017-07-01
The article presents two copyright models for minimizing downtime working brigades. Models have been developed for construction schedules performed using the method of work uniform. Application of flow shop models is possible and useful for the implementation of large objects, which can be divided into plots. The article also presents a condition describing gives which model should be used, as well as a brief example of optimization schedule. The optimization results confirm the legitimacy of the work on the newly-developed models.
Workload Schedulers - Genesis, Algorithms and Comparisons
Sliwko, L.; Getov, Vladimir
2015-01-01
In this article we provide brief descriptions of three classes of schedulers: Operating Systems Process Schedulers, Cluster Systems, Jobs Schedulers and Big Data Schedulers. We describe their evolution from early adoptions to modern implementations, considering both the use and features of algorithms. In summary, we discuss differences between all presented classes of schedulers and discuss their chronological development. In conclusion, we highlight similarities in the focus of scheduling st...
Computer-aided resource planning and scheduling for radiological services
Garcia, Hong-Mei C.; Yun, David Y.; Ge, Yiqun; Khan, Javed I.
1996-05-01
There exists tremendous opportunity in hospital-wide resource optimization based on system integration. This paper defines the resource planning and scheduling requirements integral to PACS, RIS and HIS integration. An multi-site case study is conducted to define the requirements. A well-tested planning and scheduling methodology, called Constrained Resource Planning model, has been applied to the chosen problem of radiological service optimization. This investigation focuses on resource optimization issues for minimizing the turnaround time to increase clinical efficiency and customer satisfaction, particularly in cases where the scheduling of multiple exams are required for a patient. How best to combine the information system efficiency and human intelligence in improving radiological services is described. Finally, an architecture for interfacing a computer-aided resource planning and scheduling tool with the existing PACS, HIS and RIS implementation is presented.
Distributed continuous energy scheduling for dynamic virtual power plants
International Nuclear Information System (INIS)
Niesse, Astrid
2015-01-01
This thesis presents DynaSCOPE as distributed control method for continuous energy scheduling for dynamic virtual power plants (DVPP). DVPPs aggregate the flexibility of distributed energy units to address current energy markets. As an extension of the Virtual Power Plant concept they show high dynamics in aggregation and operation of energy units. Whereas operation schedules are set up for all energy units in a day-ahead planning procedure, incidents may render these schedules infeasible during execution, like deviation from prognoses or outages. Thus, a continuous scheduling process is needed to ensure product fulfillment. With DynaSCOPE, software agents representing single energy units solve this problem in a completely distributed heuristic approach. Using a stepped concept, several damping mechanisms are applied to allow minimum disturbance while continuously trying to fulfill the product as contracted at the market.
The applicability of knowledge-based scheduling to the utilities industry
International Nuclear Information System (INIS)
Yoshimoto, G.; Gargan, R. Jr.; Duggan, P.
1992-01-01
The Electric Power Research Institute (EPRI), Nuclear Power Division, has identified the three major goals of high technology applications for nuclear power plants. These goals are to enhance power production through increasing power generation efficiency, to increase productivity of the operations, and to reduce the threats to the safety of the plant. Our project responds to the second goal by demonstrating that significant productivity increases can be achieved for outage maintenance operations based on existing knowledge-based scheduling technology. Its use can also mitigate threats to potential safety problems by means of the integration of risk assessment features into the scheduler. The scheduling approach uses advanced techniques enabling the automation of the routine scheduling decision process that previously was handled by people. The process of removing conflicts in scheduling is automated. This is achieved by providing activity representations that allow schedulers to express a variety of different scheduling constraints and by implementing scheduling mechanisms that simulate kinds of processes that humans use to find better solutions from a large number of possible solutions. This approach allows schedulers to express detailed constraints between activities and other activities, resources (material and personnel), and requirements that certain states exist for their execution. Our scheduler has already demonstrated its benefit to improving the shuttle processing flow management at Kennedy Space Center. Knowledge-based scheduling techniques should be examined by utilities industry researchers, developers, operators and management for application to utilities planning problems because of its great cost benefit potential. 4 refs., 4 figs
Semi-online patient scheduling in pathology laboratories.
Azadeh, Ali; Baghersad, Milad; Farahani, Mehdi Hosseinabadi; Zarrin, Mansour
2015-07-01
Nowadays, effective scheduling of patients in clinics, laboratories, and emergency rooms is becoming increasingly important. Hospitals are required to maximize the level of patient satisfaction, while they are faced with lack of space and facilities. An effective scheduling of patients in existing conditions is vital for improving healthcare delivery. The shorter waiting time of patients improves healthcare service quality and efficiency. Focusing on real settings, this paper addresses a semi-online patient scheduling problem in a pathology laboratory located in Tehran, Iran, as a case study. Due to partial precedence constraints of laboratory tests, the problem is formulated as a semi-online hybrid shop scheduling problem and a mixed integer linear programming model is proposed. A genetic algorithm (GA) is developed for solving the problem and response surface methodology is used for setting GA parameters. A lower bound is also calculated for the problem, and several experiments are conducted to estimate the validity of the proposed algorithm. Based on the empirical data collected from the pathology laboratory, comparison between the current condition of the laboratory and the results obtained by the proposed approach is performed through simulation experiments. The results indicate that the proposed approach can significantly reduce waiting time of the patients and improve operations efficiency. The proposed approach has been successfully applied to scheduling patients in a pathology laboratory considering the real-world settings including precedence constraints of tests, constraint on the number of sites or operators for taking tests (i.e. multi-machine problem), and semi-online nature of the problem. Copyright © 2015 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Felipe Baesler
2008-12-01
Full Text Available El presente artículo introduce una variante de la metaheurística simulated annealing, para la resolución de problemas de optimización multiobjetivo. Este enfoque se demonina MultiObjective Simulated Annealing with Random Trajectory Search, MOSARTS. Esta técnica agrega al algoritmo Simulated Annealing elementos de memoria de corto y largo plazo para realizar una búsqueda que permita balancear el esfuerzo entre todos los objetivos involucrados en el problema. Los resultados obtenidos se compararon con otras tres metodologías en un problema real de programación de máquinas paralelas, compuesto por 24 trabajos y 2 máquinas idénticas. Este problema corresponde a un caso de estudio real de la industria regional del aserrío. En los experimentos realizados, MOSARTS se comportó de mejor manera que el resto de la herramientas de comparación, encontrando mejores soluciones en términos de dominancia y dispersión.This paper introduces a variant of the metaheuristic simulated annealing, oriented to solve multiobjective optimization problems. This technique is called MultiObjective Simulated Annealing with Random Trajectory Search (MOSARTS. This technique incorporates short an long term memory concepts to Simulated Annealing in order to balance the search effort among all the objectives involved in the problem. The algorithm was tested against three different techniques on a real life parallel machine scheduling problem, composed of 24 jobs and two identical machines. This problem represents a real life case study of the local sawmill industry. The results showed that MOSARTS behaved much better than the other methods utilized, because found better solutions in terms of dominance and frontier dispersion.
2010-07-22
.... Return of Partnership Income), Schedule D (Capital Gains and Losses), Schedule K-1 (Partner's Share of...' Capital Accounts), and Schedule M-3 (Net Income (Loss) Reconciliation for Certain Partnerships)). DATES... Partnership Income (Form 1065), Capital Gains and Losses (Schedule D), Partner's Share of Income, Credits...
Shin, Kaikou; Kuroda, Mitsuru; Natsuyama, Kouichi
Advanced Planning and Scheduling (APS) has been widely recognized as a promising method for solving real production planning and scheduling problems. Based on the proposal of a real-time job shop scheduling mechanism under an APS environment, which adopts the Lagrangean relaxation method as the optimization logic, the present paper describes a feasibility study of this mechanism by evaluating its calculation speed and re-scheduling quality. Numerical experiments have been carried out for various models having different scales, as well as different densities and strengths of random events, such as the arrival of new jobs or changes to the due dates for existing jobs. The results of experiments show that the proposed scheduling mechanism has the potential to satisfy the real-time scheduling requirements, not only in terms of calculation speed and solution quality, but also with respect to predictability of the calculation load. Finally, an improvement to the Lagrangean relaxation method is proposed to improve re-scheduling quality.
Simulation methods for nuclear production scheduling
International Nuclear Information System (INIS)
Miles, W.T.; Markel, L.C.
1975-01-01
Recent developments and applications of simulation methods for use in nuclear production scheduling and fuel management are reviewed. The unique characteristics of the nuclear fuel cycle as they relate to the overall optimization of a mixed nuclear-fossil system in both the short-and mid-range time frame are described. Emphasis is placed on the various formulations and approaches to the mid-range planning problem, whose objective is the determination of an optimal (least cost) system operation strategy over a multi-year planning horizon. The decomposition of the mid-range problem into power system simulation, reactor core simulation and nuclear fuel management optimization, and system integration models is discussed. Present utility practices, requirements, and research trends are described. 37 references
Multiuser switched diversity scheduling schemes
Shaqfeh, Mohammad
2012-09-01
Multiuser switched-diversity scheduling schemes were recently proposed in order to overcome the heavy feedback requirements of conventional opportunistic scheduling schemes by applying a threshold-based, distributed, and ordered scheduling mechanism. The main idea behind these schemes is that slight reduction in the prospected multiuser diversity gains is an acceptable trade-off for great savings in terms of required channel-state-information feedback messages. In this work, we characterize the achievable rate region of multiuser switched diversity systems and compare it with the rate region of full feedback multiuser diversity systems. We propose also a novel proportional fair multiuser switched-based scheduling scheme and we demonstrate that it can be optimized using a practical and distributed method to obtain the feedback thresholds. We finally demonstrate by numerical examples that switched-diversity scheduling schemes operate within 0.3 bits/sec/Hz from the ultimate network capacity of full feedback systems in Rayleigh fading conditions. © 2012 IEEE.
NRC comprehensive records disposition schedule
International Nuclear Information System (INIS)
1983-05-01
Effective January 1, 1982, NRC will institute records retention and disposal practives in accordance with the approved Comprehensive Records Disposition Schedule (CRDS). CRDS is comprised of NRC Schedules (NRCS) 1 to 4 which apply to the agency's program or substantive records and General Records Schedules (GRS) 1 to 24 which apply to housekeeping or facilitative records. NRCS-I applies to records common to all or most NRC offices; NRCS-II applies to program records as found in the various offices of the Commission, Atomic Safety and Licensing Board Panel, and the Atomic Safety and Licensing Appeal Panel; NRCS-III applies to records accumulated by the Advisory Committee on Reactor Safeguards; and NRCS-IV applies to records accumulated in the various NRC offices under the Executive Director for Operations. The schedules are assembled functionally/organizationally to facilitate their use. Preceding the records descriptions and disposition instructions for both NRCS and GRS, there are brief statements on the organizational units which accumulate the records in each functional area, and other information regarding the schedules' applicability
Environmental surveillance master sampling schedule
International Nuclear Information System (INIS)
Bisping, L.E.
1991-01-01
Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest Laboratory (PNL) for the US Department of Energy (DOE). This document contains the planned schedule for routine sample collection for the Surface Environmental Surveillance Project (SESP) and Ground-Water Monitoring Project. The routine sampling plan for the SESP has been revised this year to reflect changing site operations and priorities. Some sampling previously performed at least annually has been reduced in frequency, and some new sampling to be performed at a less than annual frequency has been added. Therefore, the SESP schedule reflects sampling to be conducted in calendar year 1991 as well as future years. The ground-water sampling schedule is for 1991. This schedule is subject to modification during the year in response to changes in Site operation, program requirements, and the nature of the observed results. Operational limitations such as weather, mechanical failures, sample availability, etc., may also require schedule modifications. Changes will be documented in the respective project files, but this plan will not be reissued. The purpose of these monitoring projects is to evaluate levels of radioactive and nonradioactive pollutants in the Hanford evirons
Environmental surveillance master sampling schedule
Energy Technology Data Exchange (ETDEWEB)
Bisping, L.E.
1991-01-01
Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest Laboratory (PNL) for the US Department of Energy (DOE). This document contains the planned schedule for routine sample collection for the Surface Environmental Surveillance Project (SESP) and Ground-Water Monitoring Project. The routine sampling plan for the SESP has been revised this year to reflect changing site operations and priorities. Some sampling previously performed at least annually has been reduced in frequency, and some new sampling to be performed at a less than annual frequency has been added. Therefore, the SESP schedule reflects sampling to be conducted in calendar year 1991 as well as future years. The ground-water sampling schedule is for 1991. This schedule is subject to modification during the year in response to changes in Site operation, program requirements, and the nature of the observed results. Operational limitations such as weather, mechanical failures, sample availability, etc., may also require schedule modifications. Changes will be documented in the respective project files, but this plan will not be reissued. The purpose of these monitoring projects is to evaluate levels of radioactive and nonradioactive pollutants in the Hanford evirons.
Multi-objective approach for energy-aware workflow scheduling in cloud computing environments.
Yassa, Sonia; Chelouah, Rachid; Kadima, Hubert; Granado, Bertrand
2013-01-01
We address the problem of scheduling workflow applications on heterogeneous computing systems like cloud computing infrastructures. In general, the cloud workflow scheduling is a complex optimization problem which requires considering different criteria so as to meet a large number of QoS (Quality of Service) requirements. Traditional research in workflow scheduling mainly focuses on the optimization constrained by time or cost without paying attention to energy consumption. The main contribution of this study is to propose a new approach for multi-objective workflow scheduling in clouds, and present the hybrid PSO algorithm to optimize the scheduling performance. Our method is based on the Dynamic Voltage and Frequency Scaling (DVFS) technique to minimize energy consumption. This technique allows processors to operate in different voltage supply levels by sacrificing clock frequencies. This multiple voltage involves a compromise between the quality of schedules and energy. Simulation results on synthetic and real-world scientific applications highlight the robust performance of the proposed approach.
Environmental surveillance master sampling schedule
International Nuclear Information System (INIS)
Bisping, L.E.
1997-01-01
Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest National Laboratory (PNNL)(a) for the US Department of Energy (DOE). This document contains the planned 1997 schedules for routine collection of samples for the Surface Environmental Surveillance Project (SESP) and Drinking Water Monitoring Project. In addition, Section 3.0, Biota, also reflects a rotating collection schedule identifying the year a specific sample is scheduled for collection. The purpose of these monitoring projects is to evaluate levels of radioactive and nonradioactive pollutants in the Hanford environs, as required in DOE Order 5400.1, General Environmental Protection Program, and DOE Order 5400.5, Radiation Protection of the Public and the Environment. The sampling methods will be the same as those described in the Environmental Monitoring Plan, US Department of Energy, Richland Operations Office, DOE/RL91-50, Rev. 1, US Department of Energy, Richland, Washington
Schedulability Analysis for Java Finalizers
DEFF Research Database (Denmark)
Bøgholm, Thomas; Hansen, Rene Rydhof; Søndergaard, Hans
2010-01-01
Java finalizers perform clean-up and finalisation of objects at garbage collection time. In real-time Java profiles the use of finalizers is either discouraged (RTSJ, Ravenscar Java) or even disallowed (JSR-302), mainly because of the unpredictability of finalizers and in particular their impact...... on the schedulability analysis. In this paper we show that a controlled scoped memory model results in a structured and predictable execution of finalizers, more reminiscent of C++ destructors than Java finalizers. Furthermore, we incorporate finalizers into a (conservative) schedulability analysis for Predictable Java...... programs. Finally, we extend the SARTS tool for automated schedulability analysis of Java bytecode programs to handle finalizers in a fully automated way....
Schedulability Analysis for Java Finalizers
DEFF Research Database (Denmark)
Bøgholm, Thomas; Hansen, Rene Rydhof; Ravn, Anders P.
2010-01-01
Java finalizers perform clean-up and finalisation of objects at garbage collection time. In real-time Java profiles the use of finalizers is either discouraged (RTSJ, Ravenscar Java) or even disallowed (JSR-302), mainly because of the unpredictability of finalizers and in particular their impact ...... programs. Finally, we extend the SARTS tool for automated schedulability analysis of Java bytecode programs to handle finalizers in a fully automated way.......Java finalizers perform clean-up and finalisation of objects at garbage collection time. In real-time Java profiles the use of finalizers is either discouraged (RTSJ, Ravenscar Java) or even disallowed (JSR-302), mainly because of the unpredictability of finalizers and in particular their impact...... on the schedulability analysis. In this paper we show that a controlled scoped memory model results in a structured and predictable execution of finalizers, more reminiscent of C++ destructors than Java finalizers. Furthermore, we incorporate finalizers into a (conservative) schedulability analysis for Predictable Java...
Starshade Observation Scheduling for WFIRST
Soto, Gabriel; Garrett, Daniel; Delacroix, Christian; Savransky, Dmitry
2018-01-01
An exoplanet direct imaging mission can employ an external starshade for starlight suppression to achieve higher contrasts and potentially higher throughput than with an internal coronagraph. This separately-launched starshade spacecraft is assumed to maintain a single, constant separation distance from the space telescope—for this study, the Wide Field Infrared Survey Telescope (WFIRST)—based on a designated inner working angle during integration times. The science yield of such a mission can be quantified using the Exoplanet Open-Source Imaging Simulator (EXOSIMS): this simulator determines the distributions of mission outcomes, such as the types and amount of exoplanet detections, based on ensembles of end-to-end simulations of the mission. This study adds a starshade class to the survey simulation module of EXOSIMS and outlines a method for efficiently determining observation schedules. The new starshade class solves boundary value problems using circular restricted three-body dynamics to find fast, high-accuracy estimates of the starshade motion while repositioning between WFIRST observations. Fuel usage dictates the mission lifetime of the starshade given its limited fuel supply and is dominated by the Δv used to reposition the starshade between the LOS of different targets; the repositioning time-of-flight is kept constant in this study. A starshade burns less fuel to reach certain target stars based on their relative projected positions on a skymap; other targets with costly transfers can be filtered out to increase the starshade mission duration. Because the initial target list can consist of nearly 2000 stars, calculating the Δv required to move the starshade to every other star on the target list would be too computationally expensive and renders running ensembles of survey simulations infeasible. Assuming the starshade begins its transfer at the LOS of a certain star, a Δv curve is approximated for the remaining target stars based on their right
Multi-Objective Task Scheduling in the Cloud Computing based on the Patrice Swarm Optimization
Farnaz Sharifi Milani; Ahmad Habibizad Navin
2015-01-01
Cloud computing is the latest emerging trend in distributed computing, where shared resources are provided to end-users in an on demand fashion that brings many advantages, including data ubiquity, flexibility of access, high availability of resources, and flexibility. In this type of systems many challenges are existed that the task scheduling problem is one of them. The task scheduling problem in Cloud computing is an NP-hard problem. Therefore, many heuristics have bee...
A tabu search algorithm for scheduling a single robot in a job-shop environment
Hurink, Johann; Knust, Sigrid
2002-01-01
We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time windows, where additionally generalized precedence constraints have to be respected. The objective is to determine a sequence of all nodes and corresponding starting times in the given time window...
Range and mission scheduling automation using combined AI and operations research techniques
Arbabi, Mansur; Pfeifer, Michael
1987-01-01
Ground-based systems for Satellite Command, Control, and Communications (C3) operations require a method for planning, scheduling and assigning the range resources such as: antenna systems scattered around the world, communications systems, and personnel. The method must accommodate user priorities, last minute changes, maintenance requirements, and exceptions from nominal requirements. Described are computer programs which solve 24 hour scheduling problems, using heuristic algorithms and a real time interactive scheduling process.
Scheduling Parallel Jobs Using Migration and Consolidation in the Cloud
Directory of Open Access Journals (Sweden)
Xiaocheng Liu
2012-01-01
Full Text Available An increasing number of high performance computing parallel applications leverages the power of the cloud for parallel processing. How to schedule the parallel applications to improve the quality of service is the key to the successful host of parallel applications in the cloud. The large scale of the cloud makes the parallel job scheduling more complicated as even simple parallel job scheduling problem is NP-complete. In this paper, we propose a parallel job scheduling algorithm named MEASY. MEASY adopts migration and consolidation to enhance the most popular EASY scheduling algorithm. Our extensive experiments on well-known workloads show that our algorithm takes very good care of the quality of service. For two common parallel job scheduling objectives, our algorithm produces an up to 41.1% and an average of 23.1% improvement on the average response time; an up to 82.9% and an average of 69.3% improvement on the average slowdown. Our algorithm is robust even in terms that it allows inaccurate CPU usage estimation and high migration cost. Our approach involves trivial modification on EASY and requires no additional technique; it is practical and effective in the cloud environment.
customer-teller scheduling system for optimizing banks service
African Journals Online (AJOL)
due to idle times. On the other hand, good scheduling results in low waiting cost, good. Teller utilization, customer satisfaction, and more profit. Operations managers are faced with the problem of ... As service speeds up, time spent waiting on queue decreases. ... Nigerian Journal of Technology. Vol. 30, No. 1, March 2011.
On the computational complexity of (maximum) shift class scheduling
L.G. Kroon (Leo); A.W.J. Kolen
1993-01-01
textabstractIn this paper we consider a generalization of the Fixed Job Scheduling Problem (FSP) which appears in a natural way in the aircraft maintenance process at an airport. A number of jobs has to be carried out, where the main attributes of a job are: a fixed start time, a fixed finish time
On the computational complexity of (maximum) class scheduling
L.G. Kroon (Leo); A.W.J. Kolen
1991-01-01
textabstractIn this paper we consider several generalizations of the Fixed Job Scheduling Problem (FSP) which appear in a natural way in the aircraft maintenance process at an airport: A number of jobs have to be carried out, where the main attributes of a job are: a fixed start time, a fixed finish
A transportation-scheduling system for managing silvicultural projects
Jorge F. Valenzuela; H. Hakan Balci; Timothy McDonald
2005-01-01
A silvicultural project encompasses tasks such as sitelevel planning, regeneration, harvestin, and stand-tending treatments. an essential problem in managing silvicultural projects is to efficiently schedule the operations while considering project task due dates and costs of moving scarce resources to specific job locations. Transportation costs represent a...
Effects of resource management regimes on project schedule
Al-Jibouri, Saad H.S.
2002-01-01
This paper deals with the problem of resource scheduling within given resource constraints on a sectionalised construction project. A computer model has been developed which realistically simulates the progress of projects. A project has been selected and divided into sections whereby section
Models, algorithms and performance analysis for adaptive operating room scheduling
G. Xiao (Guanlian); W.L. van Jaarsveld (Willem); M. Dong (Ming); J.J. van de Klundert (Joris)
2017-01-01
textabstractThe complex optimisation problems arising in the scheduling of operating rooms have received considerable attention in recent scientific literature because of their impact on costs, revenues and patient health. For an important part, the complexity stems from the stochastic nature of the
Time-constrained project scheduling with adjacent resources
Hurink, Johann L.; Kok, A.L.; Paulus, J.J.; Schutten, Johannes M.J.
2008-01-01
We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with Adjacent Resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by
Time-constrained project scheduling with adjacent resources
Hurink, Johann L.; Kok, A.L.; Paulus, J.J.; Schutten, Johannes M.J.
We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with adjacent resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by
On project scheduling with irregular starting time costs
Möhring, Rolf H.; Schulz, Andreas S.; Stork, Frederik; Uetz, Marc Jochen
Maniezzo and Mingozzi (Oper. Res. Lett. 25 (1999) 175–182) study a project scheduling problem with irregular starting time costs. Starting from the assumption that its computational complexity status is open, they develop a branch-and-bound procedure and they identify special cases that are solvable
Automatic Choice of Scheduling Heuristics for Parallel/Distributed Computing
Directory of Open Access Journals (Sweden)
Clayton S. Ferner
1999-01-01
Full Text Available Task mapping and scheduling are two very difficult problems that must be addressed when a sequential program is transformed into a parallel program. Since these problems are NP‐hard, compiler writers have opted to concentrate their efforts on optimizations that produce immediate gains in performance. As a result, current parallelizing compilers either use very simple methods to deal with task scheduling or they simply ignore it altogether. Unfortunately, the programmer does not have this luxury. The burden of repartitioning or rescheduling, should the compiler produce inefficient parallel code, lies entirely with the programmer. We were able to create an algorithm (called a metaheuristic, which automatically chooses a scheduling heuristic for each input program. The metaheuristic produces better schedules in general than the heuristics upon which it is based. This technique was tested on a suite of real scientific programs written in SISAL and simulated on four different network configurations. Averaged over all of the test cases, the metaheuristic out‐performed all eight underlying scheduling algorithms; beating the best one by 2%, 12%, 13%, and 3% on the four separate network configurations. It is able to do this, not always by picking the best heuristic, but rather by avoiding the heuristics when they would produce very poor schedules. For example, while the metaheuristic only picked the best algorithm about 50% of the time for the 100 Gbps Ethernet, its worst decision was only 49% away from optimal. In contrast, the best of the eight scheduling algorithms was optimal 30% of the time, but its worst decision was 844% away from optimal.
Decentralized Scheduling Algorithm for DAG Based Tasks on P2P Grid
Directory of Open Access Journals (Sweden)
Piyush Chauhan
2014-01-01
Full Text Available Complex problems consisting of interdependent subtasks are represented by a direct acyclic graph (DAG. Subtasks of this DAG are scheduled by the scheduler on various grid resources. Scheduling algorithms for grid strive to optimize the schedule. Nowadays a lot of grid resources are attached by P2P approach. Grid systems and P2P model both are newfangled distributed computing approaches. Combining P2P model and grid systems we get P2P grid systems. P2P grid systems require fully decentralized scheduling algorithm, which can schedule interreliant subtasks among nonuniform computational resources. Absence of central scheduler caused the need for decentralized scheduling algorithm. In this paper we have proposed scheduling algorithm which not only is fruitful in optimizing schedule but also does so in fully decentralized fashion. Hence, this unconventional approach suits well for P2P grid systems. Moreover, this algorithm takes accurate scheduling decisions depending on both computation cost and communication cost associated with DAG’s subtasks.
Ship routing and scheduling: the cart before the horse conjecture
DEFF Research Database (Denmark)
Psaraftis, Harilaos N.
2017-01-01
The literature on ship routing and scheduling has grown substantially over the last few decades, with many papers authored by top experts in this area and examining various versions of the problem. Many publication outlets have hosted these papers, with a broad variety of problem formulations, so....... To investigate this hypothesis, this paper tries to explain some misconceptions, refers to a limited sample of such papers, and suggests possible ways to rectify this situation in the future....
Fisher, Wayne W; Greer, Brian D; Fuhrman, Ashley M; Querim, Angie C
2015-12-01
Multiple schedules with signaled periods of reinforcement and extinction have been used to thin reinforcement schedules during functional communication training (FCT) to make the intervention more practical for parents and teachers. We evaluated whether these signals would also facilitate rapid transfer of treatment effects across settings and therapists. With 2 children, we conducted FCT in the context of mixed (baseline) and multiple (treatment) schedules introduced across settings or therapists using a multiple baseline design. Results indicated that when the multiple schedules were introduced, the functional communication response came under rapid discriminative control, and problem behavior remained at near-zero rates. We extended these findings with another individual by using a more traditional baseline in which problem behavior produced reinforcement. Results replicated those of the previous participants and showed rapid reductions in problem behavior when multiple schedules were implemented across settings. © Society for the Experimental Analysis of Behavior.
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...
DEVELOPMENT OF GENETIC ALGORITHM-BASED METHODOLOGY FOR SCHEDULING OF MOBILE ROBOTS
DEFF Research Database (Denmark)
Dang, Vinh Quang
problem and finding optimal solutions for each one. However, the formulated mathematical models could only be applicable to small-scale problems in practice due to the significant increase of computation time as the problem size grows. Note that making schedules of mobile robots is part of real......-time operations of production managers. Hence to deal with large-scale applications, each heuristic based on genetic algorithms is then developed to find near-optimal solutions within a reasonable computation time for each problem. The quality of these solutions is then compared and evaluated by using......This thesis addresses the issues of scheduling of mobile robot(s) at operational levels of manufacturing systems. More specifically, two problems of scheduling of a single mobile robot with part-feeding tasks and scheduling of multiple mobile robots with preemptive tasks are taken into account...
Endogenous scheduling preferences and congestion
DEFF Research Database (Denmark)
Fosgerau, Mogens; Small, Kenneth
2010-01-01
Dynamic models of congestion so far rely on exogenous scheduling preferences of travelers, based for example on disutility of deviation from a preferred departure or arrival time for a trip. This paper provides a more fundamental view in which travelers derive utility just from consumption and le...
Environmental surveillance master sampling schedule
International Nuclear Information System (INIS)
Bisping, L.E.
1996-02-01
Environmental surveillance of the Hanford Site and surrounding areas is conducted by the Pacific Northwest National Laboratory (PNNL) for the US Department of Energy (DOE). This document contains the planned 1996 schedules for routine collection of samples for the Surface Environmental Surveillance Project (SESP), Drinking Water Project, and Ground-Water Surveillance Project
Course Scheduling and Academic Performance
Dills, Angela K.; Hernandez-Julian, Rey
2008-01-01
This paper examines the relationship between course scheduling and student achievement, controlling for student and course characteristics. The literature in psychology recognizes that performance varies by time of day and that spacing learning out over time may foster greater long-term memory of items. We use student grades as a measure of…
Job scheduling, cooperation and control
Calleja, P.; Estevez Fernandez, M.A.; Borm, P.; Hamers, H.
2006-01-01
This paper studies one machine job scheduling situations where clients can have more than one job to be processed and where a job can be of interest for different players. Corresponding cooperative games are introduced and a result on balancedness is provided. © 2005 Elsevier B.V. All rights
Endogenous scheduling preferences and congestion
DEFF Research Database (Denmark)
Fosgerau, Mogens; Small, Kenneth
2010-01-01
and leisure, but agglomeration economies at home and at work lead to scheduling preferences forming endogenously. Using bottleneck congestion technology, we obtain an equilibrium queuing pattern consistent with a general version of the Vickrey bottleneck model. However, the policy implications are different...
Lifetime Improvement by Battery Scheduling
Jongerden, M.R.; Schmitt, Jens B.; Haverkort, Boudewijn R.H.M.
The use of mobile devices is often limited by the lifetime of their batteries. For devices that have multiple batteries or that have the option to connect an extra battery, battery scheduling, thereby exploiting the recovery properties of the batteries, can help to extend the system lifetime. Due to
Lifetime improvement by battery scheduling
Jongerden, M.R.; Haverkort, Boudewijn R.H.M.
The use of mobile devices is often limited by the lifetime of its battery. For devices that have multiple batteries or that have the option to connect an extra battery, battery scheduling, thereby exploiting the recovery properties of the batteries, can help to extend the system lifetime. Due to the