خلاصة:
Recently, much attention has been given to Stochastic demand due to uncertainty in the real -world. In the literature, decision-making models and suppliers' selection do not often consider inventory management as part of shopping problems. On the other hand, the environmental sustainability of a supply chain depends on the shopping strategy of the supply chain members. The supplier selection plays an important role in the green chain. In this paper, a multi-objective nonlinear integer programming model for selecting a set of suppliers considering Stochastic demand is proposed. while the cost of purchasing including the total cost, holding and stock out costs, rejected units, units that have been delivered sooner, and total green house gas emissions are minimized, while the obtained total score from the supplier assessment process is maximized. It is assumed that the purchaser provides multiple products from the number of predetermined supplier to a Stochastic demand and the uniform probability distribution function. The product price depends on the order quantity for each product line that is intended. Multi-objective models using known methods, such as Lp-metric have become an objective function and then using genetic algorithms and simulated annealing meta-heuristic is solved.
ملخص الجهاز:
"In this study, we propose a multi-objective model to minimize the cost of purchase, returned units, delivered late units and the overall reduction of the greenhouse gas emissions as well as maximizing the process of evaluating suppliers.
3. Presentation and Discussion of the proposed model In this study, a multi-objective model is proposed, in which it is attemped to minimize the cost of purchase, returned units and units delivered late and greenhouse gas emissions and bring the total score of the supplier evaluation form to maximum.
The proposed model has five different objective functions: minimizing the total operating cost of the purchase including purchase costs, maintenance costs and the costs of inventory shortages, to minimize the number of returned units, to minimize the total units delivered late, to minimize greenhouse gas emissions, while the five functions are intended to maximize the total score of the supplier evaluation.
In order to solve multi-objective supplier selection problem in this study, use of LP-metric ∗ ∗ ∗ ∗ ∗ method for p is equal to one which implies that the late optimized (1 , 2 , 3 , 4 , 5 ) of the model, and then to combine the min to the single objective function in equation (14) are listed.
Conclusions and Recommendations In this paper, the multi-objective integer linear programming model for supplier selection problem is presented considering the purchase under stochastic demand with a uniform probability distribution and to reduce greenhouse gas emissions."