Pengfei He, University of Angers

Abstract

Hybrid genetic algorithms have proven successful in solving various routing problems, with the design of highly effective crossover operators being a crucial factor. In this talk, we will present recent advances of the edge assembly crossover operator (EAX) to solve several routing problems, including the split-delivery vehicle routing problem (SDVRP), the orienteering problem (OP), the prize-collecting traveling salesman problem (PCTSP), the minmax multiple traveling salesman problem (minmax mTSP), and the Hamiltonian-P median problem (HpMP). We show that by leveraging the strengths of the EAX operator, we can achieve remarkable improvements in the quality of solutions and computational efficiency in these areas. We will also show how the EAX operator can be extended to handle rich (multi-attribute) routing problems. By adapting the EAX operator to these rich routing problems, we hope to enable researchers and practitioners to tackle a broader range of real-world routing problems.

[Video]