a multi-period multi-objective routing-locating of heterogeneous vehicles (mpmorlhvp) planning model for two echelon supply chain with facility breakdown

Making decisions for allocating locations and determining the optimal route for vehicles will result in saving the number of transportation costs. in this paper, a multi-period multi-objective routing-locating of heterogeneous vehicles (mpmorlhvp) is proposed for determining the route and allocating the visit location for heterogeneous vehicles. the mpmorlhvp model can help optimize the routing and locating decisions for heterogeneous vehicles in a multi-period setting. it aims to find the most efficient and effective transportation plan, considering the specific context of a two-echelon supply chain and the possibility of facility breakdowns. therefore the main contribution of the current study is to provide a strategy for transporting heterogeneous vehicles over periods of time for handling and distribution in a sustainable supply chain. for this purpose, presented a multi-objective mixed integer linear programming (momip) that two objective functions formulated to improve efficiency and effectiveness. the first objective is to minimize the total cost per path. the second goal is to minimize the total repair time of vehicles to visit all areas. the epsilon constraint (ec) method has been used to solve the proposed model. the applicability of the proposed model is shown via a numerical problem. the results obtained from solving the proposed model are compared with the routing plan. based on the obtained results, the lowest allocation cost and duration of vehicle repairs have been calculated separately in each period. in the first period, the lowest and in the second period, the highest amount of cost has been calculated. in addition, in the second period, the lowest and in the third period, the maximum service time of vehicles has been determined. in addition, the results of this study can provide an advantage to decision-makers so that they consider appropriate strategies for disaster response.