Search results for "combinatorial"

showing 10 items of 1208 documents

Bamboo-like Chained Cavities and Other Halogen-Bonded Complexes from Tetrahaloethynyl Cavitands with Simple Ditopic Halogen Bond Acceptors

2018

Halogen bonding provides a useful complement to hydrogen bonding and metal-coordination as a tool for organizing supramolecular systems. Resorcinarenes, tetrameric bowl-shaped cavitands, have been previously shown to function as efficient scaffolds for generating dimeric capsules in both solution and solid-phase, and complicated one-, two-, and three-dimensional frameworks in the solid phase. Tetrahaloethynyl resorcinarenes (bromide and iodide) position the halogen atoms in a very promising “crown-like” orientation for acting as organizing halogen-bond donors to help build capsules and higher-order networks. Symmetric divalent halogen bond acceptors including bipyridines, 1,4-dioxane, and 1…

Materials sciencekemiaobligaatiotIodidehalogen bondsSupramolecular chemistrychemistry010402 general chemistry01 natural scienceschemistry.chemical_compoundBromidePhase (matter)halogensGeneral Materials Scienceta116Biochemistry Biophysics and Structural BiologyOctanebondschemistry.chemical_classificationHalogen bondta114halogeenit010405 organic chemistryHydrogen bondGeneral ChemistryCondensed Matter PhysicsCombinatorial chemistry0104 chemical sciencesChemistrychemistryHalogenhalogen-bonded complexes
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Intelligent Multi-Start Methods

2018

Heuristic search procedures aimed at finding globally optimal solutions to hard combinatorial optimization problems usually require some type of diversification to overcome local optimality. One way to achieve diversification is to re-start the procedure from a new solution once a region has been explored, which constitutes a multi-start procedure. In this chapter we describe the best known multi-start methods for solving optimization problems. We also describe their connections with other metaheuristic methodologies. We propose classifying these methods in terms of their use of randomization, memory and degree of rebuild. We also present a computational comparison of these methods on solvi…

Mathematical optimization021103 operations researchOptimization problemDegree (graph theory)Computer sciencemedia_common.quotation_subject0211 other engineering and technologiesCombinatorial optimization problem020206 networking & telecommunications02 engineering and technologyDiversification (marketing strategy)0202 electrical engineering electronic engineering information engineeringQuality (business)Metaheuristicmedia_common
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Greedy Randomized Adaptive Search Procedures

2017

In this chapter, we describe the process of designing heuristic procedures to solve combinatorial optimization problems.

Mathematical optimization021103 operations researchProcess (engineering)Heuristic (computer science)Computer science0211 other engineering and technologies0202 electrical engineering electronic engineering information engineeringCombinatorial optimization problem020201 artificial intelligence & image processing02 engineering and technology
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The Multiple Multidimensional Knapsack with Family-Split Penalties

2021

Abstract The Multiple Multidimensional Knapsack Problem with Family-Split Penalties (MMdKFSP) is introduced as a new variant of both the more classical Multi-Knapsack and Multidimensional Knapsack Problems. It reckons with items categorized into families and where if an individual item is selected to maximize the profit, all the items of the same family must be selected as well. Items belonging to the same family can be assigned to different knapsacks; however, in this case, split penalties are incurred. This problem arises in resource management of distributed computing contexts and Service Oriented Architecture environments. An exact algorithm based on the exploitation of a specific combi…

Mathematical optimizationCombinatorial optimizationInformation Systems and ManagementGeneral Computer ScienceComputer scienceKnapsack Problem0211 other engineering and technologiesBenders’ cuts; Combinatorial optimization; Integer programming; Knapsack Problems; Resource assignmentResource assignment02 engineering and technologyManagement Science and Operations ResearchIndustrial and Manufacturing Engineering0502 economics and businessInteger programming050210 logistics & transportation021103 operations research05 social sciencesBenders’ cutInteger programmingSolverKnapsack ProblemsBenders’ cutsExact algorithmKnapsack problemModeling and SimulationCombinatorial optimizationEuropean Journal of Operational Research
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Dynamic Coalitional TU Games: Distributed Bargaining among Players' Neighbors

2013

We consider a sequence of transferable utility (TU) games where, at each time, the characteristic function is a random vector with realizations restricted to some set of values. The game differs from other ones in the literature on dynamic, stochastic or interval valued TU games as it combines dynamics of the game with an allocation protocol for the players that dynamically interact with each other. The protocol is an iterative and decentralized algorithm that offers a paradigmatic mathematical description of negotiation and bargaining processes. The first part of the paper contributes to the definition of a robust (coalitional) TU game and the development of a distributed bargaining protoc…

Mathematical optimizationComputer Science::Computer Science and Game TheorySequential gameComputer scienceCombinatorial game theoryExample of a game without a valueFOS: MathematicsSimultaneous gameElectrical and Electronic EngineeringTransferable utilityMathematics - Optimization and ControlGame theoryBondareva–Shapley theoremBargaining problemNon-cooperative gameUtility theoryStochastic gameComputingMilieux_PERSONALCOMPUTINGScreening gameComputer Science ApplicationsBargaining processCore (game theory)Control and Systems EngineeringOptimization and Control (math.OC)Repeated gameSettore MAT/09 - Ricerca OperativaoptimizationMathematical economicsGame theory
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Heuristics for the capacitated dispersion problem

2020

Mathematical optimizationComputer scienceManagement of Technology and InnovationStrategy and ManagementDispersion (optics)Combinatorial optimizationManagement Science and Operations ResearchBusiness and International ManagementHeuristicsMetaheuristicComputer Science ApplicationsInternational Transactions in Operational Research
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Reactive GRASP for the strip-packing problem

2008

This paper presents a greedy randomized adaptive search procedure (GRASP) for the strip packing problem, which is the problem of placing a set of rectangular pieces into a strip of a given width and infinite height so as to minimize the required height. We investigate several strategies for the constructive and improvement phases and several choices for critical search parameters. We perform extensive computational experiments with well-known instances which have been previously reported, first to select the best alternatives and then to compare the efficiency of our algorithm with other procedures. The results show that the GRASP algorithm outperforms recently reported metaheuristics.

Mathematical optimizationGeneral Computer ScienceBin packing problemGRASPManagement Science and Operations ResearchRandomized algorithmCutting stock problemModeling and SimulationCombinatorial optimizationGreedy algorithmMetaheuristicAlgorithmGreedy randomized adaptive search procedureMathematicsComputers & Operations Research
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GRASP for the uncapacitated r-allocation p-hub median problem

2014

In this paper we propose a heuristic for the Uncapacitated r-Allocation p-Hub Median Problem. In the classical p-hub location problem, given a set of nodes with pairwise traffic demands, we must select p of them as hub locations and route all traffics through them at a minimum cost. We target here an extension, called the r-allocation p-hub median problem, recently proposed by Yaman [19], in which every node is assigned to r of the p selected hubs (r@?p) and we are restricted to route the traffic of the nodes through their associated r hubs. As it is usual in this type of problems, our method has three phases: location, assignment and routing. Specifically, we propose a heuristic based on t…

Mathematical optimizationGeneral Computer ScienceHeuristic (computer science)business.industryNode (networking)GRASPManagement Science and Operations ResearchModeling and SimulationCombinatorial optimizationPairwise comparisonLocal search (optimization)Routing (electronic design automation)HeuristicsbusinessMathematicsComputers & Operations Research
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Variable neighborhood search for the linear ordering problem

2006

Given a matrix of weights, the linear ordering problem (LOP) consists of finding a permutation of the columns and rows in order to maximize the sum of the weights in the upper triangle. This NP-complete problem can also be formulated in terms of graphs, as finding an acyclic tournament with a maximal sum of arc weights in a complete weighted graph. In this paper, we first review the previous methods for the LOP and then propose a heuristic algorithm based on the variable neighborhood search (VNS) methodology. The method combines different neighborhoods for an efficient exploration of the search space. We explore different search strategies and propose a hybrid method in which the VNS is cou…

Mathematical optimizationGeneral Computer Sciencebusiness.industryTriangulation (social science)Management Science and Operations ResearchDirected acyclic graphTabu searchRandom searchModeling and SimulationCombinatorial optimizationLocal search (optimization)businessMetaheuristicAlgorithmVariable neighborhood searchMathematicsComputers & Operations Research
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Separating capacity constraints in the CVRP using tabu search

1998

Abstract Branch and Cut methods have shown to be very successful in the resolution of some hard combinatorial optimization problems. The success has been remarkable for the Symmetric Traveling Salesman Problem (TSP). The crucial part in the method is the cutting plane algorithm: the algorithm that looks for valid inequalities that cut off the current nonfeasible linear program (LP) solution. In turn this part relies on a good knowledge of the corresponding polyhedron and our ability to design algorithms that can identify violated valid inequalities. This paper deals with the separation of the capacity constraints for the Capacitated Vehicle Routing Problem (CVRP). Three algorithms are prese…

Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceLinear programmingManagement Science and Operations ResearchTravelling salesman problemIndustrial and Manufacturing EngineeringTabu searchModeling and SimulationVehicle routing problemCombinatorial optimizationGreedy algorithmBranch and cutMetaheuristicAlgorithmMathematicsEuropean Journal of Operational Research
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