Optimum process plan selection via branch-and-bound algorithm in an automated manufacturing environment

Abstract

Due to the accessibility of alternative machines, tools, fixtures and other auxiliary devices, process plan selection problem (PPSP) is one of the most important decision-making problems in manufacturing environments. Many studies have recently attempted this issue and proposed some models for optimum PPSP. In this paper, first, PPSP is formulated as a non-linear mathematical programming model with binary variables. Then a proposed branch-and-bound (B&B) algorithm is developed to find a global optimum solution for this problem. The objective function of the proposed model is to minimise the sum of total cost associated with the processing times and processing steps and dissimilarity cost between the selected plans. The effectiveness of the proposed B&B algorithm is illustrated by comparing its performance with that of some published approaches and Lingo solutions, by using several randomly generated problems. The results show that the proposed algorithm obtains very promising solutions.