Search results for "021103 operations research"

showing 10 items of 289 documents

Matheuristics for the irregular bin packing problem with free rotations

2017

[EN] We present a number of variants of a constructive algorithm able to solve a wide variety of variants of the Two-Dimensional Irregular Bin Packing Problem (2DIBPP). The aim of the 2DIBPP is to pack a set of irregular pieces, which may have concavities, into stock sheets (bins) with fixed dimensions in such a way that the utilization is maximized. This problem is inspired by a real application from a ceramic company in Spain. In addition, this problem arises in other industries such as the garment industry or ship building. The constructive procedure presented in this paper allows both free orientation for the pieces, as in the case of the ceramic industry, or a finite set of orientation…

Mathematical optimization021103 operations researchInformation Systems and ManagementGeneral Computer ScienceBin packing problemESTADISTICA E INVESTIGACION OPERATIVA0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchStrip packingTwo-dimensional irregular bin packingConstructiveIndustrial and Manufacturing EngineeringBinCutting and packingSet packingCutting stock problemModeling and Simulation0202 electrical engineering electronic engineering information engineeringInteger Programing020201 artificial intelligence & image processingFree rotationFinite setMathematics
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Bidirectional labeling in column-generation algorithms for pickup-and-delivery problems

2018

Abstract For the exact solution of many types of vehicle-routing problems, column-generation based algorithms have become predominant. The column-generation subproblems are then variants of the shortest-path problem with resource constraints which can be solved well with dynamic-programming labeling algorithms. For vehicle-routing problems with a pickup-and-delivery structure, the strongest known dominance between two labels requires the delivery triangle inequality (DTI) for reduced costs to hold. When the direction of labeling is altered from forward labeling to backward labeling, the DTI requirement becomes the pickup triangle inequality (PTI). DTI and PTI cannot be guaranteed at the sam…

Mathematical optimization021103 operations researchInformation Systems and ManagementGeneral Computer ScienceTriangle inequalityComputation0211 other engineering and technologiesStructure (category theory)02 engineering and technologyManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringAccelerationModeling and Simulation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPickupPoint (geometry)Column generationRouting (electronic design automation)AlgorithmMathematicsEuropean Journal of Operational Research
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Advanced Greedy Randomized Adaptive Search Procedure for the Obnoxious p-Median problem

2016

Abstract The Obnoxious p-Median problem consists in selecting a subset of p facilities from a given set of possible locations, in such a way that the sum of the distances between each customer and its nearest facility is maximized. The problem is NP -hard and can be formulated as an integer linear program. It was introduced in the 1990s, and a branch and cut method coupled with a tabu search has been recently proposed. In this paper, we propose a heuristic method – based on the Greedy Randomized Adaptive Search Procedure, GRASP, methodology – for finding approximate solutions to this optimization problem. In particular, we consider an advanced GRASP design in which a filtering mechanism avo…

Mathematical optimization021103 operations researchInformation Systems and ManagementOptimization problemGeneral Computer ScienceHeuristic (computer science)business.industryGRASP0211 other engineering and technologies02 engineering and technologyManagement Science and Operations ResearchIndustrial and Manufacturing EngineeringTabu searchModeling and Simulation0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingLocal search (optimization)businessBranch and cutAlgorithmMetaheuristicGreedy randomized adaptive search procedureMathematicsEuropean Journal of Operational Research
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Multi-objective memetic optimization for the bi-objective obnoxious p -median problem

2018

Abstract Location problems have been studied extensively in the optimization literature, the p-median being probably one of the most tackled models. The obnoxious p-median is an interesting variant that appears in the context of hazardous location. The aim of this paper is to formally introduce a bi-objective optimization model for this problem, in which a solution consists of a set of p locations, and two conflicting objectives arise. On the one hand, the sum of the minimum distance between each client and their nearest open facility and, on the other hand, the dispersion among facilities. Both objective values should be kept as large as possible for a convenient location of dangerous faci…

Mathematical optimization021103 operations researchInformation Systems and Managementbusiness.industryComputer scienceCrossoverFeasible region0211 other engineering and technologiesContext (language use)02 engineering and technologySpace (commercial competition)Management Information SystemsSet (abstract data type)Artificial IntelligenceMutation (genetic algorithm)0202 electrical engineering electronic engineering information engineeringMemetic algorithm020201 artificial intelligence & image processingLocal search (optimization)businessSoftwareKnowledge-Based Systems
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Shaping communities of local optima by perturbation strength

2017

Recent work discovered that fitness landscapes induced by Iterated Local Search (ILS) may consist of multiple clusters, denoted as funnels or communities of local optima. Such studies exist only for perturbation operators (kicks) with low strength. We examine how different strengths of the ILS perturbation operator affect the number and size of clusters. We present an empirical study based on local optima networks from NK fitness landscapes. Our results show that a properly selected perturbation strength can help overcome the effect of ILS getting trapped in clusters of local optima. This has implications for designing effective ILS approaches in practice, where traditionally only small per…

Mathematical optimization021103 operations researchIterated local searchFitness landscapeComputer Science::Neural and Evolutionary Computation0211 other engineering and technologiesPerturbation (astronomy)02 engineering and technologyLocal optima networksLocal optimum0202 electrical engineering electronic engineering information engineeringPerturbation operator020201 artificial intelligence & image processingMathematicsProceedings of the Genetic and Evolutionary Computation Conference
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Stochastic Scheduling of Production Orders Under Uncertainty

2017

This paper attempts to solve the problem of searching minimum production order completion time variants by means of stochastic logical structures with all cost curve descent points and corresponding minimum-cost schedules. The analysis presented in this paper considers scheduling of unique and small batch production, predominantly to order, which accounts for changing requirements of the customer, the complexity and long production process makespan including its technical preparation. Scheduling of production order was performed by means of GAN networks and employed the concept of soft relations. The cost/time relation analysis is based on two-node network models using the cost curve. A new…

Mathematical optimization021103 operations researchJob shop schedulingComputer science0211 other engineering and technologiesScheduling (production processes)0102 computer and information sciences02 engineering and technology01 natural sciences010201 computation theory & mathematicsCost curveProduction orderCompletion timeBatch productionNetwork model
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Communities of Local Optima as Funnels in Fitness Landscapes

2016

We conduct an analysis of local optima networks extracted from fitness landscapes of the Kauffman NK model under iterated local search. Applying the Markov Cluster Algorithm for community detection to the local optima networks, we find that the landscapes consist of multiple clusters. This result complements recent findings in the literature that landscapes often decompose into multiple funnels, which increases their difficulty for iterated local search. Our results suggest that the number of clusters as well as the size of the cluster in which the global optimum is located are correlated to the search difficulty of landscapes. We conclude that clusters found by community detection in local…

Mathematical optimization021103 operations researchMarkov chainFitness landscapeComputer scienceIterated local searchbusiness.industry0211 other engineering and technologies02 engineering and technologyLocal optimumGlobal optimum0202 electrical engineering electronic engineering information engineeringCluster (physics)020201 artificial intelligence & image processingArtificial intelligencebusinessProceedings of the Genetic and Evolutionary Computation Conference 2016
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A biased random-key genetic algorithm for the time-invariant berth allocation and quay crane assignment problem

2017

We address Berth Allocation and Quay Crane Assignment Problems in a heuristic wayWe propose a Biased Random-Key Genetic Algorithm for BACAP and its extension BACASPSolutions of the Genetic Algorithm are improved by a Local SearchThe complete procedure obtains high-quality solutions for large instances Maritime transportation plays a crucial role in the international economy. Port container terminals around the world compete to attract more traffic and are forced to offer better quality of service. This entails reducing operating costs and vessel service times. In doing so, one of the most important problems they face is the Berth Allocation and quay Crane Assignment Problem (BACAP). This pr…

Mathematical optimization021103 operations researchOperations researchHeuristic (computer science)Computer scienceHeuristicbusiness.industry0211 other engineering and technologiesGeneral Engineering02 engineering and technologyComputer Science ApplicationsArtificial IntelligenceContainer (abstract data type)Genetic algorithm0202 electrical engineering electronic engineering information engineeringKey (cryptography)020201 artificial intelligence & image processingLocal search (optimization)businessAssignment problemMetaheuristicLocal search (constraint satisfaction)Expert Systems with Applications
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Heuristics for the Bi-Objective Diversity Problem

2018

Abstract The Max-Sum diversity and the Max-Min diversity are two well-known optimization models to capture the notion of selecting a subset of diverse points from a given set. The resolution of their associated optimization problems provides solutions of different structures, in both cases with desirable characteristics. They have been extensively studied and we can find many metaheuristic methodologies, such as Greedy Randomized Adaptive Search Procedure, Tabu Search, Iterated Greedy, Variable Neighborhood Search, and Genetic algorithms applied to them to obtain high quality solutions. In this paper we solve the bi-objective problem in which both models are simultaneously optimized. No pre…

Mathematical optimization021103 operations researchOptimization problemComputer science0211 other engineering and technologiesGeneral Engineering02 engineering and technologyResolution (logic)Tabu searchComputer Science ApplicationsSet (abstract data type)Artificial IntelligenceGenetic algorithm0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingHeuristicsMetaheuristicVariable neighborhood searchGreedy randomized adaptive search procedureExpert Systems with Applications
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IRA-EMO : Interactive Method Using Reservation and Aspiration Levels for Evolutionary Multiobjective Optimization

2019

We propose a new interactive evolutionary multiobjective optimization method, IRA-EMO. At each iteration, the decision maker (DM) expresses her/his preferences as an interesting interval for objective function values. The DM also specifies the number of representative Pareto optimal solutions in these intervals referred to as regions of interest one wants to study. Finally, a real-life engineering three-objective optimization problem is used to demonstrate how IRA-EMO works in practice for finding the most preferred solution. peerReviewed

Mathematical optimization021103 operations researchOptimization problemComputer sciencemieltymykset0211 other engineering and technologiesReservation02 engineering and technologyInterval (mathematics)interactive methodsMulti-objective optimizationmonitavoiteoptimointievolutionary multi-objective optimization0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingregion of interestreference point
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