Disruption Management Of Vehicle Routing Problem With Fuzzy Time Windows

Logistics distribution vehicle routing problem with time windows belongs to a typical NP-Hard problem and is difficult to solve the optimal plan. Besides, in the midst of operation the logistics distribution system also suffers many unexpected disruptions such as the changes of customers' location, demand, service time window, new requests by new customer and so on. Then if the vehicles still travel as scheduled, it will reduce the customers' satisfaction level and even lead to the failure of distribution task. Therefore, a rescue plan must be made quickly depending on the current state of the system to minimize the negative impact of disruptions on the whole work of the logistics scheduling under the premise of trade-off the benefits of all participants.Based on disruption management thought, this paper mainly researches vehicle routing problem with customers' dynamic requests. And its objectives are to minimize the impact on the whole system and maximize the customers' satisfaction level. The fuzzy processing of time window could reflect the customers' requirements well and truly. The main researches in this paper are as follows:(1) By analyzing the customers' requirements characteristics and the disadvantage of rigid time window, the fuzzy processing of time window is developed, and a fuzzy membership function is used to describe the customers' satisfaction level. Besides, through the introduction of dummy customers, a reposition strategy is proposed.(2) According to the disruption management thought, disruptions of customers' dynamic requests are identified; the method of disruptions measure which considers synthetically the customers, logistics service providers and divers is presented. A disruption recovery model for the problems is put forward based on the reposition strategy.(3) To solve this multi-objective model, a genetic algorithm which can optimize fuzzy information fleetly is developed. The insertion heuristic and genetic algorithm were combined which solved the problem of low probability of feasible solution in initialization. In this algorithm, a fuzzy optimization procedure is applied to decide the optimal starting service time for each customer. (4) Computational experiments are carried out to examine the model and algorithm, using (I) vehicle routing problem with fuzzy time windows, and (II) disruption management of vehicle routing problem with fuzzy time windows.The proposed disruption management model for vehicle routing problem with fuzzy time windows can reduce the disturbance on the original plan and satisfy the customers' requests mostly. Moreover, the research provides references for other disruptions of logistics distribution in future.