Green closed-loop supply chain network design: a novel bi-objective chance-constraint approach

In this paper, a novel chance-constrained programming model has been proposed for handling uncertainties in green closed loop supply chain network design. addition to locating the facilities and establishing flow between them, also determines transportation mode facilities. The objective functions are applied minimize expected value variance of total cost CO 2 released is controlled by providing chance-constraint including stochastic upper bound emission capacity. To solve mathematical using General Algebraic Modeling System (GAMS) software, four multi-objective decision-making (MODM) methods were applied. methodology was subjected various numerical experiments. solutions provided different compared terms cost, CPU time Pareto-based analysis optimality-based analysis. analysis, set preferable presented Pareto front; then optimization chosen as best method Simple Additive Weighting (SAW) method. Experimental experiments sensitivity demonstrated that performance goal attainment 13% 24% better global criteria methods, respectively.