A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimization. GRASP heuristics are multistart procedures which apply local search to a set of starting solutions generated with a randomized greedy algorithm or semi-greedy method. The best local optimum found over the iterations is returned as the heuristic solution. Path-relinking is a search … Read more
The Capacitated Arc Routing Problem (CARP) stands among the hardest combinatorial problems to solve or to find high quality solutions. This becomes even more true when dealing with large instances. This paper investigates methods to improve on lower and upper bounds of instances on graphs with over two hundred vertices and three hundred edges, dimensions … Read more
The document describes COIN-OR METSlib, a C++ framework for local search based metaheuristics. METSlib has been used to implement a massively parallel VRP algorithm, a state of the art Vertex Coloring Problem solver, a Timetabling software, and in many other projects. Article Download View COIN-OR METSlib: a Metaheuristics Framework in Modern C++.
Computational molecular biology has emerged as one of the most exciting interdisciplinary fields. It has currently benefited from concepts and theoretical results obtained by different scientific research communities, including genetics, biochemistry, and computer science. In the past few years it has been shown that a large number of molecular biology problems can be formulated as … Read more
This paper surveys several applications of biased random-key genetic algorithms (BRKGA) in optimization problems that arise in telecommunications. We first review the basic concepts of BRKGA. This is followed by a description of BRKGA-based heuristics for routing in IP networks, design of survivable IP networks, redundant server location for content distribution, regenerator location in optical … Read more
The set multicovering or set K-covering problem is an extension of the classical set covering problem, in which each object is required to be covered at least K times. The problem finds applications in the design of communication networks and in computational biology. We describe a GRASP with path-relinking heuristic for the set K-covering problem, … Read more
We present a biased random-key genetic algorithm (BRKGA) for finding small covers of computationally difficult set covering problems that arise in computing the 1-width of incidence matrices of Steiner triple systems. Using a parallel implementation of the BRKGA, we compute improved covers for the two largest instances in a standard set of test problems used … Read more
Telecommunication systems make use of optical signals to transmit information. The strength of a signal in an optical network deteriorates and loses power as it gets farther from the source, mainly due to attenuation. Therefore, to enable the signal to arrive at its intended destination with good quality, it is necessary to regenerate it periodically … Read more
Path-relinking 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 … Read more
GRASP with path-relinking (GRASP+PR) is a metaheuristic for finding optimal or near-optimal solutions of combinatorial optimization problems. This paper proposes a new automatic parameter tuning procedure for GRASP+PR heuristics based on a biased random-key genetic algorithm (BRKGA). Given a GRASP+PR heuristic with N input parameters, the tuning procedure makes use of a BRKGA in a … Read more