6533b854fe1ef96bd12afc6c
RESEARCH PRODUCT
Advanced Multi-start Methods
Rafael MartíJ. Marcos Moreno-vegaAbraham Duartesubject
Mathematical optimizationOptimization problemDegree (graph theory)media_common.quotation_subjectCombinatorial optimization problemQuality (business)Diversification (marketing strategy)Mathematicsmedia_commondescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2010-01-01 |