Fuzzy Optimal Allocation Model for Task–Resource Assignment Problem in a Collaborative Logistics Network

Abstract

Obtaining a multiresource allocation scheme for multitask influenced by uncertain factors is a critical problem in a collaborative logistics network. This paper presents an optimal allocation model of fuzzy resources for multistage random logistics tasks based on the six-point trapezoidal fuzzy number and the membership function. Besides, considering task demands and resource constraints, a new cost–time–quality multiobjective programming of N–N task–resource assignment is introduced, which can be divided into minimize total logistics cost and execution time, maximize total service quality. Furthermore, by setting the different simulation scenarios, the results show that if the decision maker has a higher risk preference and pursues the optimization of single or multiobjective, the higher degree membership and satisfaction function values can be obtained with a larger compensation coefficient. The allocation scheme of task–resource assignment generated by proposed model has a high global level of utilization efficiency, which can effectively utilize fuzzy resources in collaborative logistics network, and avoid resource shortage caused by the excessive occupation of local resources.