Hubs are centers for collection, rearrangement, and redistribution of commodities in transportation networks. In this paper, non-linear multi-objective formulations for single and multiple allocation hub maximal covering problems as well as the linearized versions are proposed. The formulations substantially mitigate complexity of the existing models due to the fewer number of constraints and v...

Vendor managed inventory is a continuous replenishment program that is designed to provide major cost saving benefits for both vendors and retailers. Previous research on this area mainly included single objective optimization models where the objective is to minimize the total supply chain costs or to maximize the total supply chain benefits. This paper presents a bi-objective mathematical mod...

Today, transportation of hazardous materials (i.e., hazmat) is a very important issue for researchers due to the risk of this transit, which should be considered for development of industries and transportation. Therefore, a model that is useful should consider the risk and damage to humanitarian and environmental issues due to transit of hazmat materials. By considering the related cost, the r...

data envelopment analysis (dea) is a managerial powerful tool for assess the performance of decision making units (dmus). nowadays, multi-objective dea models are an attractive technique for evaluation quantity and quality aspects of performance analysis. but these models are in static. in this paper, we want to present a proposed fuzzy dynamic multi-objective dea model in which data are changi...

This paper presents two new dynamic programming (DP) algorithms to find the exact Pareto frontier for the bi-objective integer knapsack problem. First, a property of the traditional DP algorithm for the multiobjective integer knapsack problem is identified. The first algorithm is developed by directly using the property. The second algorithm is a hybrid DP approach using the concept of the boun...

The article presents a proposed customized genetic algorithm (CGA) to find the Pareto frontier for bi-objective integer linear programming (ILP) model of routing in dynamic network, where number nodes and edge weights vary over time. Utilizing hybrid method, CGA combines with (DP); it is fast alternative an ILP solver finding efficient solutions, particularly large dimensions. A non-dominated s...