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 local search. Path-relinking is an intensification strategy that explores trajectories that connect high quality solutions. We analyze two parallel strategies for GRASP with path-relinking and propose a criterion … Read more
This document contains references related to GRASP (greedy randomized adaptive search procedure) that have either appeared in the literature or as technical reports. If you are aware of any uncited reference, incorrectly cited reference, or update to a cited reference, please contact Mauricio G. C. Resende at the address given at the end of this … Read more
A phylogeny is a tree that relates taxonomic units, based on their similarity over a set of characters. The phylogeny problem consists in finding a phylogeny with the minimum number of evolutionary steps. We propose a new neighborhood structure for the phylogeny problem. A GRASP heuristic based on this neighborhood structure and using VND for … Read more
A phylogeny is a tree that relates taxonomic units, based on their similarity over a set of characters. The problem of finding a phylogeny with the minimum number of evolutionary steps (the so-called parsimony criterion) is one of the main problems in comparative biology. In this work, we study different heuristic approaches to the phylogeny … Read more
A greedy randomized adaptive search procedure (GRASP) is a multi-start metaheuristic which applies local search to starting solutions generated by a greedy randomized construction procedure. Until recently, most implementations of GRASP assumed independence of its iterations, thus making no use of memory structures. Path-relinking is an intensification strategy which explores trajectories between elite solutions. Using … Read more
Given N customers and a set F of M potential facilities, the P-median problem consists in finding a subset of F with P facilities such that the cost of serving all customers is minimized. This is a well-known NP-complete problem with important applications in location science and classification (clustering). We present a multistart hybrid heuristic … Read more
In this paper, we describe a methodology for the analysis of greedy randomized adaptive search procedures (GRASP). GRASP is a metaheuristic for combinatorial optimization. It usually consists of a construction procedure based on a greedy randomized algorithm and a local search. Hybrid approaches of GRASP with path-relinking developed for the 3-index assignment problem (AP3) and … Read more
This paper addresses recent advances and application of hybridizations of greedy randomized adaptive search procedures (GRASP) and path-relinking. We present a template for implementing path-relinking as an intensification procedure for GRASP. Enhancements to the procedure, recently described in the literature, are reviewed. The effectiveness of the procedure is illustrated experimentally. Citation AT&T Labs Research Technical … Read more
Given N customers and a set F of M potential facilities, the P-median problem consists in finding a subset of F with P facilities such that the cost of serving all customers is minimized. This is a well-known NP-complete problem with important applications in location science and classification (clustering). We present here a GRASP (Greedy … Read more
Given an undirected graph with edge weights, the MAX-CUT 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. It is a well-known NP-hard problem with applications in several fields, including VLSI design and statistical physics. … Read more