Dynamic production planning models with start-up costs

Abstract

This thesis considers four different dynamic production planning models with start-up cost. The first model is concerned with a dynamic production planning subject for a single-facility single-product problem where backlogging is not allowed. The model involves inventory holding cost and two kinds of fixed costs $-$ a start-up cost incurred whenever the machine (production facility) is switched from "off" to "on", and a reservation cost incurred in any production period. A forward algorithm for finding an optimal solution over a finite horizon is presented and a planning horizon theorem is derived. In a rolling-horizon environment, two procedures for selecting the run length of the first production-block and the production amounts in the first production-block are developed. Computational results from a set of simulation experiments designed to investigate the cost effectiveness of the procedure demonstrate its effectiveness. The second model is concerned with a dynamic production planning subject for a single-facility single-product problem where capacity restrictions are imposed on production, and backlogging is not allowed. The model includes inventory holding cost and two kinds of fixed costs $-$ a start-up cost incurred whenever the machine (production facility) is switched from "off" to "on", and a reservation cost incurred in any production period. In the analysis, the property of the optimal solution is characterized and then used to construct an efficient forward algorithm for the case of having equal production capacity in every period. The algorithm is illustrated with a numerical problem. The third model analyzes a subject of reducing start-up cost in a single-facility single-product multiple finite production rate problem where production in a period is restricted to a value taken from the set {O,P,…,mP} with a given constant P and a positive integer m. The model assumes that start-up cost is charged only when production changes from zero to any ...