Transportation network design problem (NDP) is inherently multi-objective in nature, because it involves a number of stakeholders with different needs. In addition, the decision-making process sometimes has to be made under uncertainty where certain inputs are not known exactly. In this paper, we develop three stochastic multi-objective models for designing transportation network under demand u...

This paper considers a single-sourcing network design problem for a three-level supply chain. For the first time, a novel mathematical model is presented considering risk-pooling, the inventory existence at distribution centers (DCs) under demand uncertainty, the existence of several alternatives to transport the product between facilities, and routing of vehicles from distribution centers to c...

In some countries, regional authorities may attempt to rebalance the allocation of national facilities in benefit their own region which, turn, cause disturbances central government’s decision-making proces. Regarding hierarchical nature these types decisions, classical optimization models are not effective and use multi-level programming can increase efficiency planning. Our paper aims address...

We describe a hybrid bi-level decomposition scheme that addresses the challenge of solving a large-scale two-stage stochastic programming problem with mixed-integer recourse, which results from a multi-scale capacity planning problem as described in part I of this paper series. The decomposition scheme combines bi-level decomposition with Benders decomposition, and relies on additional strength...

Simulation is generally used to study non-deterministic problems in industry. When a simulation process finds the solution to an NP-hard problem, its efficiency is lowered, and computational costs increase. This paper proposes a stochastic dynamic lot-sizing problem with asymmetric deteriorating commodity, in which the optimal unit cost of material and unit holding cost would be determined. Thi...