A fuzzy multiobjective team decision model for CODP and supplier selection in customized logistics service supply chain

Abstract

To address information vagueness and uncertainty of the order demand, the logistics service provider (LSP) service capacity and the target preference caused by emergency events, a multiobjective team optimization model is developed for the customer order decoupling point (CODP) decision, supplier selection and order quantity allocation problems in customized logistics service supply chain. Three important techniques are described: (1) Fuzzy objective coefficients due to the uncertainty of the order and objective weights. (2) Fuzzy constraint parameters due to LSP service capacity and order demand variations. (3) A fuzzy single objective weighting technique with acceptance coefficient of constraint and fuzzy parameters that reflects decision-maker preferences. The acceptance coefficients of the constraints are integrated into the single objective model, which reflects the satisfaction level of the logistics service integrator (LSI) for feasible solutions. Then, we perform fuzzy decision and feasible solution design based on the center of gravity method defuzzification and maximum membership degree principle. To optimize decisions for decision-makers, the effects of some important fuzzy objective coefficients and fuzzy constraint parameters on the CODP decision and the acceptance coefficient of constraint was explored through sensitivity analysis. Numerical experiments show that the scale effect coefficient and objective function threshold have greater effects on the CODP decision.