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Abstract:

Neighbourhood search optimisation techniques that are based upon steepest or first-ascent hillclimbers, such as tabu search, often use some form of a candidate list strategy which examines a subset of the available moves. This paper presents and evaluates a directed candidate list strategy which is an analogue with the ‘directed mutation ’ strategy used in evolutionary algorithms, and evaluates its performance on the flowshop sequencing problem by seeing whether this approach can exploit idle-time knowledge based on a previously published move selection heuristic for stochastic optimisers. 1

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