Jia Shu

Warehouse-Retailer Network Design Problem

In this paper, we study the distribution network design problem integrating transportation and infinite horizon multiechelon inventory cost function. We consider the trade-off between inventory cost, direct shipment cost, and facility location cost in such a system. The problem is to determine how many warehouses to set up, where to locate them, how to serve the retailers using these warehouses, and to determine the optimal inventory policies for the warehouses and retailers. The objective is to minimize the total multiechelon inventory, transportation, and facility location costs. To the best of our knowledge, none of the papers in the area of distribution network design has explicitly addressed the issues of the 2-echelon inventory cost function arising from coordination of replenishment activities between the warehouses and the retailers. We structure this problem as a set-partitioning integer-programming model and solve it using column generation. The pricing subproblem that arises from the column generation algorithm gives rise to a new class of the submodular function minimization problem. We show that this pricing subproblem can be solved inO( n?log? n) time, wheren is the number of retailers. Computational results show that the moderate size distribution network design problem can be solved efficiently via this approach.

Models for Effective Deployment and Redistribution of Bicycles Within Public Bicycle-Sharing Systems

We develop practical operations research models to support decision making in the design and management of public bicycle-sharing systems. We develop a network flow model with proportionality constraints to estimate the flow of bicycles within the network and the number of trips supported, given an initial allocation of bicycles at each station. We also examine the effectiveness of periodic redistribution of bicycles in the network to support greater flow, and the impact on the number of docks needed.We conduct our numerical analysis using transit data from train operators in Singapore. Given that a substantial proportion of passengers in the train system commute a short distance---more than 16% of passengers alight within two stops from the origin---this forms a latent segment of demand for a bicycle-sharing program. We argue that for a bicycle-sharing system to be most effective for this customer segment, the system must deploy the right number of bicycles at the right places, because this affects the utilization rate of the bicycles and how bicycles circulate within the system. We also identify the appropriate operational environments in which periodic redistribution of bicycles will be most effective for improving system performance.

Inventory placement in acyclic supply chain networks

By adding a set of redundant constraints, and by iteratively refining the approximation, we show that a commercial solver is able to routinely solve moderate-size strategic safety stock placement problems to optimality. The speed-up arises because the solver automatically generates strong flow cover cuts using the redundant constraints.

Approximation Algorithms for Integrated Distribution Network Design Problems

In this paper, we study approximation algorithms for two supply chain network design problems, namely, the warehouse-retailer network design problem WRND and the stochastic transportation-inventory network design problem STIND. These two problems generalize the classical uncapacitated facility location problem by incorporating, respectively, the warehouse-retailer echelon inventory cost and the warehouse cycle inventory together with the safety stock costs. The WRND and the STIND were initially studied, respectively, by Teo and Shu Teo CP, Shu J 2004 Warehouse-retailer network design problem. Oper. Res. 523:396--408 and Shu et al. Shu J, Teo CP, Shen ZJM 2005 Stochastic transportation-inventory network design problem. Oper. Res. 531:48--60, where they are formulated as set-covering problems, and column-generation algorithms were used to solve their linear programming relaxations. Both problems can be regarded as special cases of the so-called facility location with submodular facility costs proposed by Svitkina and Tardos Svitkina Z, Tardos E 2010 Facility location with hierarchical facility costs. ACM Trans. Algorithms 62, Article No. 37, for which only a logarithmic-factor approximation algorithm is known. Our main contribution is to obtain efficient constant-factor approximation algorithms for the WRND and the STIND, which are capable of solving large-scale instances of these problems efficiently.

Dynamic Container Deployment: Two-Stage Robust Model, Complexity, and Computational Results

Containers are widely used in the shipping industry mainly because of their capability to facilitate multimodal transportation. How to effectively reposition the nonrevenue empty containers is the key to reduce the cost and improve the service in the liner shipping industry. In this paper, we propose a two-stage robust optimization model that takes into account the laden containers routing as well as the empty container repositioning, and define the robustness for this model with uncertainties in the supply and demand of the empty containers. Based on this definition, we present the robust formulations for the uncertainty sets corresponding to the (l-script) p -norm, where p = 1, 2, and (infinity), and analyze the computational complexities for all of these formulations. The only polynomial-time solvable case corresponds to the (l-script) 1 -norm, which we use to conduct the numerical study. We compare our approach with both the deterministic model and the stochastic model for the same problem in the rolling horizon simulation environment. The computational results establish the potential practical usefulness of the proposed approach.

A cross-monotonic cost-sharing scheme for the concave facility location game

In this paper, we present a cost-sharing scheme for the concave facility location game by exploring the concavity structure. We show that it is cross-monotonic and competitive, and recovers 1/3 fraction of the total cost.

Multisourcing Supply Network Design: Two-Stage Chance-Constrained Model, Tractable Approximations, and Computational Results

In this paper, we study a multisourcing supply network design problem, in which each retailer faces uncertain demand and can source products from more than one distribution center (DC). The decisions to be simultaneously optimized include DC locations and inventory levels, which set of DCs serves each retailer, and the amount of shipments from DCs to retailers. We propose a nonlinear mixed integer programming model with a joint chance constraint describing a certain service level. Two approaches—set-wise approximation and linear decision rule-based approximation—are constructed to robustly approximate the service level chance constraint with incomplete demand information. Both approaches yield sparse multisourcing distribution networks that effectively match uncertain demand using on-hand inventory, and hence successfully reach a high service level. We show through extensive numerical experiments that our approaches outperform other commonly adopted approximations of the chance constraint.