Variable neighborhood search-based methods for integrated hybrid flow shop scheduling with distribution

Shijin Wang (1) , Ruochen Wu (1) , Feng Chu (2, 3) , Jianbo Yu (4)

1 School of Economics & Management
2 IBISC - Informatique, BioInformatique, Systèmes Complexes
3 School of Economics and Management
4 School of Mechanical Engineering

With the rapid development of make-to-order pattern including E-commerce and takeout and catering service in restaurants, the study of integrated scheduling and distribution receives more and more attentions. Based on a practical order picking and distribution system, a three-stage hybrid flow shop scheduling problem with distribution is studied. Each order is processed on the hybrid flow shop which consists of identical parallel machines with sequence-dependent setup times at stage 1, identical parallel machines at stage 2 and dedicated machines at stage 3, followed by a multi-trip traveling salesman problem with capacitated vehicles for customers of different destination areas. A mixed-integer linear programming model is formulated to minimize the maximum delivery completion time. A variable neighborhood search (VNS)-based method, a four-layered constructive heuristic method (denoted by CHVNS) and a hybrid heuristic method (denoted by CONSVNS) which combines the VNS method and the CHVNS method are developed to solve the problems with practical size. Computational experiments show the effectiveness and efficiency of the proposed methods.

Mots clés: Parallel machinesTraveling salesman problem; Hybrid flow shop; Variable neighborhood search; Constructive heuristic

Domaines: Recherche opérationnelle [math.OC]

Shijin Wang, Ruochen Wu, Feng Chu, Jianbo Yu. Variable neighborhood search-based methods for integrated hybrid flow shop scheduling with distribution. Soft Computing, 2019, ⟨10.1007/s00500-019-04420-6⟩. ⟨hal-02365198⟩