Strategy

We address the Joint Replenishment Problem (JRP) where, in the presence of joint setup costs, dynamic lot sizing schedules need to be determined for m items over a planning horizon of N periods, with general time-varying cost and demand parameters. We develop a new, so-called, partitioning heuristic for this problem, which partitions the complete horizon of N periods into several relatively small intervals, specifies an associated joint replenishment problem for each of these, and solves them via a new, efficient branch-and-bound method.

Why do some new ventures succeed while others fail? What is the essence of entrepreneurship? Who is most likely to become a successful entrepreneur and why? How do entrepreneurs make decisions? What market, regulatory, and organizational environments foster the most successful entrepreneurial activities? Entrepreneurship research is plagued by these and other fundamental unanswered questions, for which there does not exist a cohesive explanatory, predictive, or normative theory.

In this paper we develop a model for a capacitated production/distribution network of general (but acyclic) topology with a general bill of materials, as considered in MRP (Material Requirement Planning) or DRP (Distribution Requirement Planning) systems. This model assumes stationary, deterministic demand rates and a standard stationary cost structure; it is a generalization of the uncapacitated model treated in the seminal papers of Maxwell and Muckstadt (1985) and Roundy (1986).

This paper extends the analysis of transactions cost models of vertical integration to multilateral settings. Its main focus is on supply assurance concerns which arise when several downstream firms are competing for inputs in limited supply. Integration reduces supply assurance concerns for an integrating firm but it may increase them for others. Therefore, to explain the scope of any firm, one must consider the overall network of production and distribution relations.

Edited by John R. White.

In this chapter we discuss planning models for multi-echelon systems which allow for uncertain and nonstationary demand and lead time processes. We confine ourselves to so-called PUSH systems with a central decision maker, who possesses continuously or periodically updated information about all inventories of all products at all relevant facilities and production stages; all replenishment decisions in the system are determined centrally on the basis of this information.

We develop a simple O(n log n) solution method for the standard lot-sizing model with backlogging and a study horizon of n periods. Production costs are fixed plus linear and holding and backlogging costs are linear with general time-dependent parameters. The algorithm has linear [O(n)] time complexity for several important subclasses of the general model. We show how a slight adaptation of the algorithm can be used for the detection of a minimal forecast horizon and associated planning horizon.

We consider an inventory system with compound Poisson demands replenished by discrete production of units on a single-server facility. This facility may start a vacation at any production completion epoch; at the completion of a vacation the inventory level is inspected to decide whether or not to resume production. Unit production and vacation times are independent and identically distributed with general distributions.

We consider distribution systems with a single depot and many retailers each of which faces external demands for a single item that occurs at a specific deterministic demand rate. All stock enters the systems through the depot where it can be stored and then picked up and distributed to the retailers by a fleet of vehicles, combining deliveries into efficient routes. We extend earlier methods for obtaining low complexity lower bounds and heuristics for systems without central stock.