According to the operational characteristics of the logistics networks for the third party logistics supplier （3PLS）, the forward and reverse logistics networks together for 3PLS under the uncertain environment are designed. First, a fuzzy model is proposed by taking multiple customers, multiple commodities, capacitated facility location and integrated logistics facility layout into account. In the model, the fuzzy customer demands and transportation rates are illustrated by triangular fuzzy numbers. Secondly, the fuzzy model is converted into a crisp model by applying fuzzy chance constrained theory and possibility theory, and one hybrid genetic algorithm is designed for the crisp model. Finally, two different examples are designed to illustrate that the model and solution discussed are valid.
A new type of vehicle routing problem （VRP）, multiple vehicle routing problem integrated reverse logistics （MVRPRL）, is studied. In this problem, there is delivery or pickup （or both） and uncertain features in the demands of the clients. The deliveries of every client as uncertain parameters are expressed as triangular fuzzy numbers. In order to describe MVRPRL, a multi-objective fuzzy programming model with credibility measure theory is constructed. Then the simulationbased tabu search algorithm combining inter-route and intra-route neighborhoods and embedded restarts are designed to solve it. Computational results show that the tabu search algorithm developed is superior to sweep algorithms and that compared with handling each on separate routes, the transportation costs can be reduced by 43% through combining pickups with deliveries.
