Abstract

The minmax multiple traveling salesman problem with single depot (the minmax mTSP) or multiple depots (the minmax multidepot mTSP) aims to minimize the longest tour among a set of tours. These two minmax problems are useful for a variety of real-life applications and typically studied separately in the literature. We propose a unified memetic approach to solving both cases of the minmax mTSP and the minmax multidepot mTSP. The proposed algorithm features a generalized edge assembly crossover to generate offspring solutions, an efficient variable neighborhood descent to ensure local optimization as well as an aggressive post-optimization for additional solution improvement. Extensive experimental results on 77 minmax mTSP benchmark instances and 43 minmax multidepot mTSP instances commonly used in the literature indicate a high performance of the algorithm compared to the leading algorithms. Additional experimental investigations are conducted to shed light on the rationality of the key algorithmic ingredients.

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