Hybridizations of Metaheuristics With Branch & Bound Derivates

Abstract

An important branch of hybrid metaheuristics concerns the hybridization with branch & bound derivatives. In this chapter we present examples for two different types of hybridization. The first one concerns the use of branch & bound features within construction-based metaheuristics in order to increase their efficiancy. The second example deals with the use of a metaheuristic, in our case a memetic algorithm, in order to increase the efficiancy of branch & bound, respectively branch & bound derivatives such as beam search. The quality of the resulting hybrid techniques is demonstrated by means of the application to classical string problems: the longest common subsequence problem and the shortest common supersequence problem.

Hybrid metaheuristics in combinatorial optimization: A survey

“…Further examples are the works by Gallardo et al [118] and Blum et al [119], in which the control flows of beam search and a memetic algorithm are intertwined, i.e., phases of beam search and the memetic algorithm alternate. Beam search purges its queue of open partial solutions by excluding those whose upper bounds are worse than the value of the best solution found by the memetic algorithm.…”

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“…It has shown very high performance for problems such as open shop scheduling [20] and assembly line balancing [21]. More details on beam-ACO and similar hybrid algorithms can be found in [22]. A combination of a GRASP algorithm with a branch-and-bound algorithm is described in [44] for an application to the JSP.…”

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