R. C. Baker

A multi-phase mathematical programming approach for effective supply chain design

Abstract A supply chain is an alliance of independent business processes, such as supplier, manufacturing, and distribution processes that perform the critical functions in the order fulfillment process. Effective design and management of supply chains assists in production and delivery of a variety of products at low cost, high quality, and short lead times. Although the importance of supply chain design is emphasized in the literature, few formal decision models have been proposed for this purpose. This paper presents a multi-phase mathematical programming approach for effective supply chain design. More specifically, the methodology develops and applies a combination of multi-criteria efficiency models, based on game theory concepts, and linear and integer programming methods. Model application and insights are detailed through numerical illustrations.

A framework for designing efficient value chain networks

Strategic interorganizational networks aid organizations in gaining competitive advantages and improving production efficiencies. Network organizations, virtual corporations, and value-adding partnerships are envisioned by many experts as the epitome of interorganizational networks for the 21st century. These multi-organizational structures are viewed as a solution for rapid introduction of products while maintaining high quality and minimal costs. One common key issue in designing these new forms of organizations is the partner selection process. The business processes, owned by organizational partners, must be efficient both individually and as a collective group. This paper proposes a two-phase quantitative framework to aid the decision making process in effectively selecting an efficient and a compatible set of partners. Phase 1 identifies efficient candidates for each type of business process (e.g. design, manufacturing, distribution, etc.) utilizing data envelopment analysis. Phase 2 involves the execution of an integer goal programming model to determine the best portfolio of efficient partners based on a number of compatibility objectives. Model application and insights are evident through an illustrative example.

Optimal ordering and pricing policies in a single-period environment with multivariate demand and markdowns

This paper investigates a single-period inventory model in which the demand of the product is a deterministic, multivariate function of price, time, and level of inventory. Models are formulated for the basic pricing case and the case with a price markdown during the season. Solution methodologies are presented for each case when the pricing decisions are predetermined and when they are decision variables. Comments on the practical use of this model are presented, and sensitivity analysis is conducted on the decision variables and demand parameters.

Deterministic fixed order-level inventory models: An application for replenishment of radioactive source material for irradiation sterilizers

Abstract This paper investigates the timing of the replenishment of radioactive cobalt used in irradiation sterilizers. It is found that this model can be expressed as the continuous, deterministic case of a fixed order-level inventory model in which the demand rate is dependent on the level of inventory. The decision variable (the order point) can be determined using a univariable search technique. For certain values of the shape parameter of the demand function, the first derivative of the average profit function can be expressed as a polynomial from which the optimal order point can be determined. A numerical example is presented as well as an analysis of the sensitivity to changes in the solution and model parameters.