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27
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
 ACM COMPUTING SURVEYS
, 2003
"... The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important meta ..."
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Cited by 168 (14 self)
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The field of metaheuristics for the application to combinatorial optimization problems is a rapidly growing field of research. This is due to the importance of combinatorial optimization problems for the scientific as well as the industrial world. We give a survey of the nowadays most important metaheuristics from a conceptual point of view. We outline the different components and concepts that are used in the different metaheuristics in order to analyze their similarities and differences. Two very important concepts in metaheuristics are intensification and diversification. These are the two forces that largely determine the behaviour of a metaheuristic. They are in some way contrary but also complementary to each other. We introduce a framework, that we call the I&D frame, in order to put different intensification and diversification components into relation with each other. Outlining the advantages and disadvantages of different metaheuristic approaches we conclude by pointing out the importance of hybridization of metaheuristics as well as the integration of metaheuristics and other methods for optimization.
Randomized Heuristics for the MaxCut Problem
 Optimization Methods and Software
, 2002
"... Given an undirected graph with edge weights, the MAXCUT problem consists in finding a partition of the nodes into two subsets, such that the sum of the weights of the edges having endpoints in different subsets is maximized. ..."
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Cited by 30 (15 self)
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Given an undirected graph with edge weights, the MAXCUT problem consists in finding a partition of the nodes into two subsets, such that the sum of the weights of the edges having endpoints in different subsets is maximized.
A Hybrid Genetic Algorithm for the Job Shop Scheduling Problem
 EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
, 2002
"... This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using ..."
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Cited by 28 (8 self)
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This paper presents a hybrid genetic algorithm for the Job Shop Scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a priority rule in which the priorities are defined by the genetic algorithm. Schedules are constructed using a procedure that generates parameterized active schedules. After a schedule is obtained a local search heuristic is applied to improve the solution. The approach is tested on a set of standard instances taken from the literature and compared with other approaches. The computation results validate the effectiveness of the proposed algorithm.
GRASP with pathrelinking for the weighted MAXSAT problem
 ACM Journal of Experimental Algorithmics
, 2006
"... A GRASP with path relinking for finding goodquality solutions of the weighted maximum satisfiability problem (MAXSAT) is described in this paper. GRASP, or Greedy Randomized Adaptive Search Procedure, is a randomized multistart metaheuristic, where, at each iteration, locally optimal solutions are ..."
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Cited by 15 (11 self)
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A GRASP with path relinking for finding goodquality solutions of the weighted maximum satisfiability problem (MAXSAT) is described in this paper. GRASP, or Greedy Randomized Adaptive Search Procedure, is a randomized multistart metaheuristic, where, at each iteration, locally optimal solutions are constructed, each independent of the others. Previous experimental results indicate its effectiveness for solving weighted MAXSAT instances. Path relinking is a procedure used to intensify the search around goodquality isolated solutions that have been produced by the GRASP heuristic. Experimental comparison of the pure GRASP (without path relinking) and the GRASP with path relinking illustrates the effectiveness of path relinking in decreasing the average time needed to find a goodquality solution for the weighted maximum satisfiability problem.
GRASP with pathrelinking for the Quadratic Assignment Problem
 Proceedings of Third International Workshop on Experimental and Efficient Algorithms, Lect. Notes Comp. Sci
, 2004
"... This paper describes a GRASP with pathrelinking heuristic for the quadratic assignment problem. GRASP is a multistart procedure, where different points in the search space are probed with local search for highquality solutions. ..."
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Cited by 14 (6 self)
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This paper describes a GRASP with pathrelinking heuristic for the quadratic assignment problem. GRASP is a multistart procedure, where different points in the search space are probed with local search for highquality solutions.
On The Performance Of Heuristics For Broadcast Scheduling
, 2004
"... In the Broadcast Scheduling Problem (BSP), a finite set of stations are to be scheduled in a time division multiple access (TDMA) frame. In a TDMA frame, time is divided into equal length transmission slots. Unconstrained message transmission can result in a collision of messages, rendering them use ..."
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Cited by 9 (8 self)
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In the Broadcast Scheduling Problem (BSP), a finite set of stations are to be scheduled in a time division multiple access (TDMA) frame. In a TDMA frame, time is divided into equal length transmission slots. Unconstrained message transmission can result in a collision of messages, rendering them useless. Therefore, the objective of the BSP is to provide a collision free broadcast schedule which minimizes the total frame length and maximizes the slot utilization within the frame. In this chapter, we introduce the BSP, show that it is NP complete, and discuss several heuristics which have been applied to the problem. The heuristics are tested on over 60 networks of varying sizes and densities and the results are compared.
GRASP WITH PATHRELINKING FOR THE GENERALIZED QUADRATIC ASSIGNMENT PROBLEM
"... Abstract. The generalized quadratic assignment problem (GQAP) is a generalization of the NPhard quadratic assignment problem (QAP) that allows multiple facilities to be assigned to a single location as long as the capacity of the location allows. In this paper, we propose several GRASP with pathrel ..."
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Cited by 6 (3 self)
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Abstract. The generalized quadratic assignment problem (GQAP) is a generalization of the NPhard quadratic assignment problem (QAP) that allows multiple facilities to be assigned to a single location as long as the capacity of the location allows. In this paper, we propose several GRASP with pathrelinking heuristics for the GQAP using different construction, local search, and pathrelinking procedures. Experimental results using timetotarget plots illustrate the relative effectiveness of these variants on instances found in the literature. 1.
Pathrelinking intensification methods for stochastic local search algorithms
 J. of Heuristics
"... Abstract. Pathrelinking is major enhancement to heuristic search methods for solving combinatorial optimization problems, leading to significant improvements in both solution quality and running times. We review its fundamentals and implementation strategies, as well as advanced hybridizations with ..."
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Cited by 6 (4 self)
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Abstract. Pathrelinking is major enhancement to heuristic search methods for solving combinatorial optimization problems, leading to significant improvements in both solution quality and running times. We review its fundamentals and implementation strategies, as well as advanced hybridizations with more elaborate metaheuristic schemes such as genetic algorithms and scatter search. Numerical examples are discussed and algorithms compared based on their run time distributions. 1. Introduction and
A GREEDY RANDOMIZED ADAPTIVE SEARCH PROCEDURE FOR THE POINTFEATURE CARTOGRAPHIC LABEL PLACEMENT
"... The pointfeature cartographic label placement problem (PFCLP) is an NPhard problem which appears during the production of maps. The labels must be placed in predefined places avoiding overlaps and considering cartographic preferences. Due to its high complexity several heuristics have been present ..."
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Cited by 5 (0 self)
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The pointfeature cartographic label placement problem (PFCLP) is an NPhard problem which appears during the production of maps. The labels must be placed in predefined places avoiding overlaps and considering cartographic preferences. Due to its high complexity several heuristics have been presented searching for approximated solutions. This paper proposes a greedy randomized adaptive search procedure (GRASP) for the PFCLP that is based on its associated conflict graph. The computational results show that this metaheuristic is a good strategy for PFCLP, generating better solutions than all those reported in the literature in reasonable computational times.
Parallel strategies for GRASP with pathrelinking
, 2005
"... ABSTRACT. A Greedy Randomized Adaptive Search Procedure (GRASP) is a metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and a local search. Pathrelinking is an intensification strategy that explores trajectories that ..."
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Cited by 4 (2 self)
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ABSTRACT. A Greedy Randomized Adaptive Search Procedure (GRASP) is a metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and a local search. Pathrelinking is an intensification strategy that explores trajectories that connect high quality solutions. We analyze two parallel strategies for GRASP with pathrelinking and propose a criterion to predict parallel speedup based on experiments with a sequential implementation of the algorithm. Independent and cooperative parallel strategies are described and implemented for the 3index assignment problem and the jobshop scheduling problem. The computational results for independent parallel strategies are shown to qualitatively behave as predicted by the criterion. 1.