The results of a study of the coordination effect in stocking and promotional markdown policies for a supply chain consisting of a retailer and a discount outlet (DCO) are reported here. We assume that the product is sold in two consecutive periods: the Normal Sales Period (NSP) and the subsequent Promotional Markdown Sales Period (PSP). We first study an integrated supply chain in which managers in the two periods design a common system so as to jointly decide the stocking quantities, markdown time schedule, and markdown price to maximize mutual profit. Next, we consider a decentralized supply chain. An uncoordinated contract is designed in which decisions are decentralized to optimize the individual party's objective function. Here, three sources of system inefficiencies cause the decentralized system to earn a lower expected system profit than that in the integrated supply chain. The three sources are as follows: in the decentralized system the retailer tends to (1) stock less, and (2) keep a longer sales period, and the DCO tends to (3) stock fewer leftovers inventories and charge a higher markdown price. Finally, a numerical experiment is provided to compare the coordinated model with the uncoordinated model to explore factors that make coordination an effective approach.

Firms often collaborate on building an infrastructure, which benefits all the firms in the industry, although in unequal magnitudes. Then a difficult and tricky issue is concerned with 'free riding.' Should there be only 'common, i.e., industry-wide' benefits in such collaboration, the literature indicated that the free rider problem is unavoidable, In this paper, however, we suggest that while collaborating, the firm also learns firm-specific knowledge, experience, and know-how, which can be directly utilized for its own internal improvement. That is, the collaboration between firms provides them with not only 'industry-wide,' but also 'firm-specific' benefits, Our analysis shows that if there indeed exist two types of benefits simultaneously, depending on the balance between the two, the free rider problem can be mitigated or even eliminated.

We consider the graph disconnection problem, which is to find a set of edges such that the total cost of destroying the edges is no more than a given budget and the weight of nodes disconnected from a designated source by destroying the edges is maximized. The problem is known to be NP-hard. We present an integer programming formulation for the problem and develop an algorithm that includes a preprocessing procedure for reducing the problem size, a heuristic for providing a lower bound, and a cutting plane algorithm for obtaining an upper bound. Computational results for evaluating the performance of the proposed algorithm are also presented.

Disassembly scheduling is the problem of determining the ordering and disassembly schedules of used or end-of-life products while satisfying the demand of their parts or components over a certain planning horizon. This paper considers the case of the assembly product structure for the cost-based objective of minimizing the sum of purchase, setup, inventory holding, and disassembly operation costs. To represent and solve the problem optimally, this paper presents an integer programming model, which is a reversed form of the multi-level lot sizing formulation. Computational experiments on an example derived from the literature and a number of randomly generated test problems are done and the results are reported.