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Pathrelinking intensification methods for stochastic local search algorithms
 Journal of Heuristics
, 2012
"... 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 wit ..."
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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.
Scatter search and pathrelinking: Fundamentals, advances, and applications.
 Handbook of Metaheuristics,
, 2010
"... Abstract Scatter search is an evolutionary metaheuristic that explores solution spaces by evolving a set of reference points, operating on a small set of solutions while making only limited use of randomization. We give a comprehensive description of the elements and methods that make up its templa ..."
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Cited by 9 (5 self)
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Abstract Scatter search is an evolutionary metaheuristic that explores solution spaces by evolving a set of reference points, operating on a small set of solutions while making only limited use of randomization. We give a comprehensive description of the elements and methods that make up its template, including the most recent elements incorporated in successful applications in both global and combinatorial optimization. Pathrelinking is an intensification strategy to explore trajectories connecting elite solutions obtained by heuristic methods such as scatter search, tabu search, and GRASP. We describe its mechanics, implementation issues, randomization, the use of pools of highquality solutions to hybridize pathrelinking with other heuristic methods, and evolutionary pathrelinking. We also describe the hybridization of pathrelinking with genetic algorithms to implement a progressive crossover operator. Some successful applications of scatter search and of pathrelinking are also reported.
GRASP: Basic components and enhancements
 Telecommunication Systems
, 2011
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Restart strategies for GRASP with pathrelinking heuristics
 Optimization Letters
"... Abstract. GRASP with pathrelinking is a hybrid metaheuristic, or stochastic local search (Monte Carlo) method, for combinatorial optimization. A restart strategy in GRASP with pathrelinking heuristics is a set of iterations {i1, i2, . . .} on which the heuristic is restarted from scratch using a ..."
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Abstract. GRASP with pathrelinking is a hybrid metaheuristic, or stochastic local search (Monte Carlo) method, for combinatorial optimization. A restart strategy in GRASP with pathrelinking heuristics is a set of iterations {i1, i2, . . .} on which the heuristic is restarted from scratch using a new seed for the random number generator. Restart strategies have been shown to speed up stochastic local search algorithms. In this paper, we propose a new restart strategy for GRASP with pathrelinking heuristics. We illustrate the speedup obtained with our restart strategy on GRASP with pathrelinking heuristics for the maximum cut problem, the maximum weighted satisfiability problem, and the private virtual circuit routing problem.
Grasp: Greedy randomized adaptive search procedures
 in Search Methodologies
, 2014
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A hybrid genetic algorithm for the target visitation problem. Naval Research Logistics, submitted, 2007
 0.051 42 5.739 100 380 10 36 11.506 41 0.02 37 3.866 100 380 15 35 6.198 40 0.39 36 3.034 125 240 5 29 7.951 37 0.251 31 1.472 125 240 10 24 9.984 29 0.07 24 1.993 125 240 15 22 5.888 26 0.18 22 9.233 150 290 5 31 7.981 40 0.421 30 5.798 150 290 10 26 4.9
"... ABSTRACT. In this paper we consider the problem of determining an optimal path for an unmanned aerial vehicle which needs to visit multiple targets. The objective is to minimize the travel distance while maximizing the utility of the visitation order. This is known as the TARGET VISITATION PROBLEM a ..."
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ABSTRACT. In this paper we consider the problem of determining an optimal path for an unmanned aerial vehicle which needs to visit multiple targets. The objective is to minimize the travel distance while maximizing the utility of the visitation order. This is known as the TARGET VISITATION PROBLEM and has several applications including combat search and rescue, environmental assessment, and disaster relief. First, we provide a mathematical model based on integer linear programming and prove that the problem is N Pcomplete. Then we describe the implementation of a genetic algorithm for finding approximate solutions. The heuristic is then hybridized by the implementation of a local search procedure. Numerical results are presented demonstrating the effectiveness of the proposed procedure. 1.
Community detection by modularity maximization using GRASP with pathrelinking
 Computers & Operations Research
, 2011
"... Abstract. Detection of community structure in graphs remains up to this date a computationally challenging problem despite the efforts of many researchers from various scientific fields in the past few years. The modularity value of a set of vertex clusters in a graph is a widely used quality measur ..."
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Abstract. Detection of community structure in graphs remains up to this date a computationally challenging problem despite the efforts of many researchers from various scientific fields in the past few years. The modularity value of a set of vertex clusters in a graph is a widely used quality measure for community structure, and the relating problem of finding a partition of the vertices into clusters such that the corresponding modularity is maximized is an NPHard problem. A Greedy Randomized Adaptive Search Procedure (GRASP) with path relinking is presented in this paper, for modularity maximization in undirected graphs. A new class of {0,1} matrices is introduced which characterizes the family of clusterings in a graph, and a distance function is given which enables us to define an lneighborhood local search which generalizes most of the related local search methods that have appeared in the literature. Computational experiments comparing the proposed algorithmwithotherheuristicsfromtheliteratureinasetofsomewellknown benchmark instances, indicate that our implementation of GRASP with path relinking consistently produces better quality solutions.
HYBRID METAHEURISTICS FOR THE FAR FROM MOST STRING PROBLEM
, 2013
"... Abstract. Among the sequence selection and comparison problems, the Far From Most String Problem (FFMSP) is one of the computationally hardest with applications in several fields, including molecular biology where one is interested in creating diagnostic probes for bacterial infections or in discove ..."
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Abstract. Among the sequence selection and comparison problems, the Far From Most String Problem (FFMSP) is one of the computationally hardest with applications in several fields, including molecular biology where one is interested in creating diagnostic probes for bacterial infections or in discovering potential drug targets. In this article, several hybrid metaheuristics are described and tested. Extensive comparative experiments on a large set of randomly generated test instances indicate that these randomized hybrid techniques are both effective and efficient. 1. The Far From Most String Problem (FFMSP) The FFMSP is one of the so called string selection and comparison problems, that belong to the more general class of problems known as sequences consensus, where a finite set of sequences is given and one is interested in finding their consensus, i.e. a new sequence that agrees as much as possible with all the given sequences. In other words, the objective is to determine a sequence called consensus, because
SOLVING THE WEIGHTED MAX2SAT PROBLEM WITH ITERATED TABU SOLVING THE WEIGHTED MAX2SAT SEARCH PROBLEM WITH ITERATED TABU SEARCH
"... Abstract. Given a CNF formula in which each clause is of length at most two and has an associated positive weight, the weighted Max2SAT problem asks to find a truth assignment to the Boolean variables that maximizes the total weight of the satisfied clauses. We develop an iterated tabu search (ITS ..."
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Abstract. Given a CNF formula in which each clause is of length at most two and has an associated positive weight, the weighted Max2SAT problem asks to find a truth assignment to the Boolean variables that maximizes the total weight of the satisfied clauses. We develop an iterated tabu search (ITS) algorithm for solving this problem. We report computational results on Max2SAT instances of size up to 3000 variables and provide comparisons of ITS to stateoftheart heuristic methods from the literature, which demonstrate the competitiveness of our approach. Key words: artificial intelligence, satisfiability, MaxSAT, combinatorial optimization, metaheuristics, tabu search. 1.
GRASP with pathrelinking for the cooperative communication problem on adhoc networks
 SIAM Journal on Control and Optimization
, 2006
"... Abstract. Adhoc networks are a new paradigm for communications systems in which wireless nodes can freely connect to each other without the need of a prespecified structure. Difficult combinatorial optimization problems are associated with the design and operation of these networks. In this paper, ..."
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Abstract. Adhoc networks are a new paradigm for communications systems in which wireless nodes can freely connect to each other without the need of a prespecified structure. Difficult combinatorial optimization problems are associated with the design and operation of these networks. In this paper, we consider the problem of maximizing the connection time between a set of mobile agents in an adhoc network. Given a network and a set of wireless agents with starting nodes and target nodes, the objective is to find a set of trajectories for the agents that maximizes connectivity during their operation. This problem, referred to as the COOPERATIVE COMMUNICATION ON ADHOC NETWORKS is known to be NPhard. We look for heuristic algorithms that are able to efficiently compute high quality solutions to instances of large size. We propose the use of a greedy randomized adaptive search procedure (GRASP) to compute solutions for this problem. The GRASP is enhanced by applying a pathrelinking intensification procedure. Extensive experimental results are presented, demonstrating that the proposed strategy provides near optimal solutions for the 900 instances tested. Key words. Cooperative communication, ad hoc networks, metaheuristics, GRASP, pathrelinking. AMS subject classifications. 68T20, 90B18, 90B06. 1. Introduction. Cooperative