6533b85efe1ef96bd12bfb68
RESEARCH PRODUCT
Multi-Start Methods
Rafael Martísubject
Mathematical optimizationOptimization problemDegree (graph theory)Computer sciencemedia_common.quotation_subjectCombinatorial optimization problemQuality (business)Diversification (marketing strategy)Linear orderingGlobal optimalmedia_commondescription
Heuristic search procedures that aspire to find global 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 linear ordering problem in terms of solution quality and diversification power.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2006-02-02 |