Zhaowei Miao

A Survey on Reviewer Assignment Problem

Research into Reviewer Assignment Problem (RAP) is still in its early stage but there is great world-wide interest, as the foregoing process of peer-review which is the brickwork of science authentication. The RAP approach can be divided into three phases: identifying assignment procedure, computing the matching degree between manuscripts and reviewers, and optimizing the assignment so as to achieve the given objectives. Methodologies for addressing the above three phases have been developed from a variety of research disciplines, including information retrieval, artificial intelligent, operations research, etc. This survey is not only to cover variations of RAP that have appeared in the literature, but also to identify the practical challenge and current progress for developing intelligent RAP systems.

Transshipment service through crossdocks with both soft and hard time windows

Recently, crossdocking techniques have been successfully applied in responsive supply chain management. However, most researches focused on physical layout of a crossdock, or scheduling operations within a crossdock. In this paper, we study a multi-crossdock transshipment service problem with both soft and hard time windows. The flows from suppliers to customers via the crossdocks are constrained by fixed transportation schedules. Cargos can be delayed and consolidated in crossdocks, and both suppliers and customers have specific hard time windows. In addition to hard time windows, customers also have less-restrictive time windows, called soft time windows. The problem to minimize the total cost of the multi-crossdock distribution network, including transportation cost, inventory handling cost and penalty cost, can be proved to be NP-hard in the strong sense and hence efficient heuristics are desired. We propose two types of meta-heuristic algorithms, called Adaptive Tabu Search and Adaptive Genetic Algorithm, respectively, to solve the problem efficiently. We conduct extensive experiments and the results show that both of them outperform CPLEX solver and provide fairly good solutions within realistic timescales. We also perform sensitivity analysis and obtain a number of managerial insights.

Remanufacturing with trade-ins under carbon regulations

Abstract Observing prevalent concerns about the influence of carbon emissions on climate change, we address the problem of remanufacturing with trade-ins under carbon regulations. We analyze the optimal pricing and production decisions of the manufacturer under the carbon tax policy and the cap and trade program. The results show that the introduction of carbon regulations can promote sales of remanufactured products while reducing the demands of new products. However, the implementation of carbon regulations has negative impacts on the manufacturers profits. Nevertheless, the manufacturers profits can be improved through deliberately designed government subsidy schemes. We also demonstrate that the government has the incentive to propose such subsidy schemes because the total emissions can be reduced under well-designed regulations, but not at the cost of the manufacturers profits.

Meta-heuristic Algorithm for the Transshipment Problem with Fixed Transportation Schedules

In this work, we develop an efficient meta-heuristic genetic algorithm for a different type of transshipment problem with supplier and customer time windows, where flow through the crossdock (a kind of transshipment center) is constrained by fixed transportation schedules and crossdocks capacities, and which was proved to be NP -complete in the strong sense. And computational experiments are conducted to show the proposed heuristic outperforms CPLEX.

Newsvendor with multiple options of expediting

We consider a manufacturer facing single period inventory planning problem with uncertain demand and multiple options of expediting. The demand comes at a certain time in the future. The manufacturer may order the product in advance with a relatively low cost. She can order additional amount by expediting after the demand is realized. There are a number of expediting options, each of which corresponds to a certain delivery lead time and a unit procurement price. The unit procurement price is decreasing over delivery lead time. The selling price is also decreasing over time. In this paper, we assume that the manufacturer must deliver all products to the customer in a single shipment. The problem can be formulated as a profit maximization problem. We develop structural properties and show how the optimal solution can be identified efficiently. In addition, we compare our model with the classical newsvendor model and obtain a number of managerial insights.

On Planar Medianoid Competitive Location Problems With Manhattan Distance

A medianoid problem is a competitive location problem that determines the locations of a number of new service facilities that are competing with existing facilities for service to customers. This paper studies the medianoid problem on the plane with Manhattan distance. For the medianoid problem with binary customer preferences, i.e., a case where customers choose the closest facility to satisfy their entire demand, we show that the general problem is NP-hard and present solution methods to solve various special cases in polynomial time. We also show that the problem with partially binary customer preferences can be solved with a similar approach we develop for the model with binary customer preferences.

Transshipment problem with penalty in crossdocking distribution networks

In this paper we study a new type of transshipment problem, the flows through the crossdock are constrained by fixed transportation schedules and any cargos delayed at the last moment of the time horizon of the problem will incur relative high inventory penalty cost. The problem is known to be NP-complete in the strong sense. We therefore focus on developing efficient heuristics. Based on the problem structure, we propose a Genetic Algorithm to solve the problem efficiently. Computational experiments under different scenarios show that GA outperforms CPLEX solver.

Achieving supply chain agility through inter-organization knowledge sharing: A research-in-progress

With the rapid development of knowledge economy, knowledge sharing increasingly becomes one of the key factors in enabling agility of the supply chain. This study proposes that inter-organization knowledge sharing, including explicit and tacit knowledge sharing, will affect supply chain agility positively. Further, key antecedents of knowledge sharing are also identified in this research. Specifically, we suggest that partnership uncertainty, interdependence of supply chain partners, trust and commitment of supply chain partner are associated with these two kinds of knowledge sharing. A large scale mail survey was designed and will be conducted in China to test our research model.

The returns disposition problem with outsourcing in reverse supply chains

Quick disposition of returns is the most important part in a successful reverse supply chain, if returns can be disposed in time and processed quickly, more profit we can get from them, and also service level can be increased. In this paper, we study the returns disposition problem with outsourcing by developing markov decision model. By theoretical proof, we give out optimal structure for this model which can help us with decision-making in the real world.

Exploring key antecedents of supply chain agility: An empirical study

The importance of supply chain agility has been widely recognized by researchers and practitioners, especially with the increasing turbulence of the global economy in recent years. This research aims at clarifying the concept of agility in supply chain research and identifying key antecedents of supply chain agility. In particular, we propose responsiveness, flexibility, and quickness as key dimensions of overall supply chain agility, and identify process integration, information integration, market sensitivity as enablers of the three dimensions of supply chain agility.