%0 Journal Article %T Shipper collaboration in forward and reverse logistics %+ Laboratoire d'Optimisation des Systèmes Industriels (LOSI) %+ School of Management %A Lyu, Xiaohui %A Wang, Nengmin %A Yang, Zhen %A Chen, Haoxun %< avec comité de lecture %@ 1553-166X %J Journal of Industrial & Management Optimization %V 13 %N 5 %P 1-37 %8 2017 %D 2017 %R 10.3934/jimo.2018173 %K meta-heuristics %K vehicle routing %K forward and reverse logistics %K shipper collaboration %K less than truckload transportation %K Collaborative transportation planning %Z Engineering Sciences [physics] %Z Computer Science [cs]/Operations Research [cs.RO]Journal articles %X In less than truckload transportation, shippers collaborate to reduce their logistics costs by consolidating their transportation requests in the procurement of transportation services from a carrier for serving the requests. In this paper, we study shipper collaboration in forward and reverse logistics, in which multiple shippers with forward or/and reverse logistics operations consolidate their transportation requests. In the forward and reverse logistics, manufacturers deliver new products to their customers and used products are collected from customers and transported to remanufacturers for repair or reproduction. This gives rise to a new vehicle routing problem with pickup and delivery requests and three different types of depots (product depots, vehicle depots and recycle depots). A hybrid approach combining greedy randomized adaptive search procedure (GRASP) and iterated local search (ILS) is proposed to find a near optimal solution of the problem. Numerical experiments on a large set of randomly generated instances with different problem sizes demonstrate that shipper collaboration in forward and reverse logistics can realize significant cost savings compared with the isolated operation of each shipper without cooperation, and the proposed approach is effective in the sense that it can find a high quality solution in a reasonable computation time. %G English %L hal-02470437 %U https://utt.hal.science/hal-02470437 %~ CNRS %~ UNIV-TROYES %~ UTT %~ LOSI