Model for cost estimation in a finite-capacity environment

Abstract

Cost estimation is a practical problem that has attracted the attention of many researchers. Past research has focused mainly on cost estimation in an unlimited capacity environment. This paper presents a mixed-integer-programming model (MIP) for estimating cost under finite capacity. It proposes an iterative heuristic model based on a marginal analysis where the total cost without the new order is subtracted from the total cost with the new order. The proposed heuristic's efficiency and effectiveness are examined with respect to the optimal solution for small instances of the problem and compared with a partial enumeration solution for larger problem instances. Lower bounds obtained from the partial Branch-and-Bound procedure are also used for comparison. A computational study is performed to test how different factors affect the advantage of using the proposed heuristic over a conventional method for cost estimation.

Acknowledgement

This work was supported by the Hal and Inga Marcus Fund.