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T he Internet's computational power and flexibility have made auctions a widespread and integral part of both consumer and business markets. Though online auctions are a multibillion dollar annual activity, with a growing variety of sophisticated trading mechanisms, scientific research on them is at an early stage. This paper analyzes the current state of management science research on online auctions. It develops a broad research agenda for issues such as the behavior of online auction participants, the optimal design of online auctions, the integration of auctions into the ongoing operation of firms, and the use of the data generated by online auctions to inform future trading mechanisms. These research areas will draw from applied and theoretical work spanning management science, economics, and information systems. (Auctions; Internet)

We consider an n job, one machine scheduling problem in which all jobs have a common due date. The objective is to determine the optimal value of this due date and an optimal sequence to minimize a total penalty function. This penalty function is based on the due date value and on the earliness or the lateness of each job in the selected sequence. We present a polynomial bound scheduling algorithm for the solution of this problem along with the proof of optimality, a numerical example and discuss some extensions.

Economic lot sizing and batching models often assume reliable manufacturing facilities. In this research, we focus on the effects of machine breakdowns and corrective maintenance on the economic lot sizing decisions. Two production control policies are proposed for coping with these stochastic interferences. The first policy assumes that production of the interrupted lots is not resumed after a breakdown. Instead, the on-hand inventory is depleted before a new cycle is initiated. Under the second policy studied here, production is immediately resumed after a breakdown, if the current on-hand inventory is below a certain threshold level. It is shown that this control structure is optimal among all stationary policies. We show that under both policies the optimal lot sizes will always be bigger than the ones in a corresponding deterministic case, and that the optimal lot size increases with the failure rate. We also provide exact optimal and closed form approximate lot sizing formulas and derive tight bounds on the average cost per unit time for the approximations. In addition, we present various structural properties for these policies and operational insights relevant to such management decisions as machine replacement or maintenance schedules.production planning, lot sizing, machine breakdowns