Robust hub network design problem

This paper presents a robust formulation for the uncapacitated single and multiple allocation hub location problem where demand is uncertain and its distribution is not fully specified. The proposed robust model is formulated as a mixed integer nonlinear program and then transformed into a mixed integer conic quadratic program. An efficient linear relaxation strategy is proposed which is found to deliver the optimal solutions for all the cases considered in this paper. Numerical experiments suggest location of more number of hubs when accounting for demand uncertainty using robust optimization compared to the deterministic setting.     

Planning and optimization of intermodal hub-and-spoke network under mixed uncertainty

This paper addresses the planning and optimization of intermodal hub-and-spoke (IH&S) network considering mixed uncertainties in both transportation cost and travel time. Different from previous studies, this paper develops a novel modeling framework for the IH&S network design problem to jointly minimize the expected value of total transportation costs and the maximum travel time requirement in term of critical value. A new hybrid methodology by combining fuzzy random simulation (FRS) technique and multi-start simulated annealing (MSA) algorithm is designed to solve the proposed model. Numerical experiments are implemented to verify the effectiveness of the proposed model and solution approach.     

Decomposition approach for integrated intermodal logistics network design

The integrated intermodal logistics network design problem consists of determining terminal locations and selecting regular routes and transportation modes for loads. This problem was formulated using a path-based formulation and a decomposition-based search algorithm has been proposed for its solution. Computational results show that this approach is able to obtain optimal solutions for non-trivial problem instances of up to 150 nodes in reasonable computational times. Previous studies have only been able to obtain approximate solutions for network problems of this size. A few general insights about the effects of design parameters on solution characteristics were also obtained.     

Fleet deployment, network design and hub location of liner shipping companies

A mixed integer linear programming formulation is proposed for the simultaneous design of network and fleet deployment of a deep-sea liner service provider. The underlying network design problem is based on a 4-index (5-index by considering capacity type) formulation of the hub location problem which are known for their tightness. The demand is elastic in the sense that the service provider can accept any fraction of the origin–destination demand. We then propose a primal decomposition method to solve instances of the problem to optimality. Numerical results confirm superiority of our approach in comparison with a general-purpose mixed integer programming solver.     

A supply chain network design model for biomass co-firing in coal-fired power plants

We propose a framework for designing the supply chain network for biomass co-firing in coal-fired power plants. This framework is inspired by existing practices with products with similar physical characteristics to biomass. We present a hub-and-spoke supply chain network design model for long-haul delivery of biomass. This model is a mixed integer linear program solved using benders decomposition algorithm. Numerical analysis indicates that 100 million tons of biomass are located within 75 miles from a coal plant and could be delivered at $8.53/dry-ton; 60 million tons of biomass are located beyond 75 miles and could be delivered at $36/dry-ton.     

Measuring the perceived container leasing prices in liner shipping network design with empty container repositioning

This paper aims to measure the perceived container leasing prices at different ports by presenting a two-stage optimization method. In stage I, we propose a practical liner shipping network design problem with empty container repositioning. The proposed problem further considers the use of foldable containers and allows the mutual substitution between empty containers to decrease the number of empty containers to be repositioned. In stage II, the inverse optimization technique is used to determine the perceived container leasing prices at different ports, based on the solution obtained in stage I. Based on a set of candidate liner shipping service routes, a mixed-integer nonlinear programming model is built for the proposed problem in stage I. The nonlinear terms are linearized by introducing the auxiliary variables. Numerical experiments based on a realistic Asia-Europe-Oceania liner shipping network are carried out to account for the effectiveness of our two-stage optimization method.