Kapalı devre tedarik zincirleri için bir karma tamsayılı lokasyon, envanter ve fiyatlandırma modeli

Designing an appropriate closed loop supply chain is crucial not only due to the economicvalue that can be gained from used products but also due to the environmental concernsraising in popularity in last couple decades. In this paper, we address an inventory-locationand pricing problem for a closed-loop supply chain with the purpose of collection of theused products and distribution of the newly produced ones simultaneously with the decisionof price and incentive. We present a mixed integer nonlinear facility location allocationmodel with inventory considerations to decide both optimal location of these collectionand distribution centers (CDC) and optimal values of price and incentive oered for newand used products, respectively, in order to maximize the prot. To solve this NP-hardproblem, three dierent hybridized heuristic approaches are proposed throughout the paper.The heuristics correspond to applications of Simulated Annealing, Tabu Search andGenetic Algorithms which all are hybridized with Variable Neighborhood Search. Dierentneighborhood structures are embedded in these heuristics to obtain better results. The performancesof the proposed algorithms are analyzed on extensive set of test instances up to200 customers and 200 possible locations, and we compared it with the upper bound foundby a linearization technique. Finally, we compare the three proposed metaheuristics witheach other. In all comparisons, we report optimality gaps calculated with respect to theupper bound. The results of our computational study show that the Tabu Search algorithmhybridized with VNS(TSVNS) gives better results compared to solutions given by the othertwo metaheuristics. The success of the TSVNS algorithm highly depends on its memorystructure while providing an eective diversication mechanism.