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Abstract. Consumers may incur deliberation costs in learning about their valuations for new products. When the deliberation cost is not trivial, the retailer may set a low price to inhibit [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2008.11.033 Byline: Yanzhi Li (a), Yi Tao (b), Fan Wang (b) Keywords: Cargo loading problem; Large-scale neighborhood search; Heuristics; Decision support systems Abstract: Cost effectiveness is central to the air freight forwarders. In this work, we study how an air freight forwarder should plan its cargo loading in order to minimize the total freight cost given a limited number of rented containers. To solve the problem efficiently for practical implementation, we propose a new large-scale neighborhood search heuristic. The proposed large-scale neighborhood relaxes the subset-disjoint restriction made in the existing literature; the relaxation risks a possibility of infeasible exchanges while at the same time it avoids the potentially large amount of checking effort required to enforce the subset-disjoint restriction. An efficient procedure is then used to search for improvement in the neighborhood. We have also proposed a subproblem to address the difficulties caused by the fixed charges. The compromised large-scale neighborhood (CLSN) search heuristic has shown stably superior performance when compared with the traditional large-scale neighborhood search and the mixed integer programming model. Author Affiliation: (a) Department of Management Sciences, City University of Hong Kong, Hong Kong (b) School of Business, Sun Yat-sen University, Guangzhou, PR China Article History: Received 24 April 2008; Accepted 18 November 2008

We consider the problem of allocating demand that originates from multiple sources among multiple inventory locations. Demand from each source arrives dynamically according to an independent Poisson process. The cost [...]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2007.03.004 Byline: Yunsong Guo (a), Yanzhi Li (b), Andrew Lim (c), Brian Rodrigues (d) Keywords: Production sourcing; Tariffs; Heuristics Abstract: In this paper, we study a multi-stage production sourcing problem where tariff concessions can be exploited at the firm level using free trade agreements between countries. To solve the problem, an algorithm which embeds a very large-scale neighborhood (VSLN) search into a simulated annealing framework is developed. A numerical study is conducted to verify the effectiveness of the solution approach. Author Affiliation: (a) Department of Computer Science, Cornell University, Ithaca, NY 14853, USA (b) Department of Management Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong (c) Department of IELM, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong (d) Lee Kong Chian School of Business, Singapore Management University, 50 Stamford Road, Singapore 178899, Singapore Article History: Received 14 September 2005; Accepted 21 March 2007

Trade globalization has brought a surge in Free Trade Agreements (FTAs). Although trade agreements have been studied extensively from the economic point of view, there is very little operations management literature on the effect of FTAs at the firm level. In this work, we present a material sourcing model which can be used by companies. The model addresses local content or value-added requirements for trade concessions, and is motivated by the Japan-Singapore Economic Partnership Agreement FTA. We provide solution techniques for realistic problem sizes for the model which can be used by manufaturers located in any FTA country. Keywords: Global sourcing, free trade agreement, local content, tariff, 1. Introduction The global economy has recently seen a surge in Free Trade Agreements (FTAs) (Ju and Krishna, 2005), which have reduced or eliminated trade barriers and transformed the way [...]

The recent article by Bandyopadhyay and Paul [Bandyopadhyay S, Paul AA (2010) Equilibrium returns policies in the presence of supplier competition. Marketing Sci. 29(5):846-857] searched for an explanation for the [...]