Part selection and tool allocation in discrete parts manufacturing

Abstract

A recurrent problem in discrete parts manufacturing is to select the optimal mix of parts and to allocate the necessary tools on a machine's carousel in order to maximize net profit. We formulate the problem as an integer program and compute an upper bound for the optimal solution. We then develop a greedy type heuristic to obtain a lower bound on the value of the optimal solution. Further, we show that the worst case relative error of the proposed heuristic approaches 1y2. Finally, we demonstrate via extensive computational experimentation that the greedy heuristic produces near optimal solutions for a variety of problem instances.