Advanced Multi-start Methods

R. Martí (), J. Marcos Moreno-Vega () and A. Duarte ()
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R. Martí: Universidad de Valencia
J. Marcos Moreno-Vega: Universidad de La Laguna, La Laguna Santa Cruz de Tenerife
A. Duarte: Universidad Rey Juan Carlos

Chapter Chapter 9 in Handbook of Metaheuristics, 2010, pp 265-281 from Springer

Abstract: Abstract Heuristic search procedures that aspire to find 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. In this chapter we describe the best known multi-start methods for solving optimization problems. 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 solving the maximum diversity problem in terms of solution quality and diversification power.

Keywords: Multi-start Method; Maximum Diversity Problem (MDP); Greedy Adaptive Search Procedure (GRASP); Persistent Attractiveness; Tabu Search Framework (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1007/978-1-4419-1665-5_9

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