ANT COLONY OPTIMISATION APPLIED TO MULTI-OBJECTIVE OPERATION SEQUENCING PROBLEM

Abstract

A computer-aided process planning system should ideally generate and optimize process plans to ensure the application of good manufacturing practices and maintain the consistency of the desired functional specifications of a part during its production processes. Crucial processes, such as selecting machining resources, determining set-up plans, determining cutting tool and sequencing operations of a part should be considered simultaneously to achieve global optimal solutions. In this paper, these processes are integrated as `Multi Objective Operation Sequencing Problem' and `Ant Colony Optimization (ACO)' is proposed to solve it effectively. Multi objective operation sequencing problem is solved by considering these objectives namely, minimization of total manufacturing time, maximization of safety. Based on above mentioned objectives an Operation Relationship Matrix (ORM) is formed for each criterion and inputted to ant colony optimization algorithm. In general, the problem has combinatorial characteristics and complex precedence relations, which makes the problem difficult to solve. Ant Colony Optimization (ACO) is the most successful and widely recognized algorithm technique to solve combinational optimization problems by using principles of communicative behavior occurring in ant colonies. ACO in operation sequencing works similar to that in Traveling salesman problem. The ORM matrix gives the relationship between the pair of operations. Artificial ant is put to every station. The algorithm works to complete the sequence of operations or stations such that it covers all the operations and no operation is repeated in the sequence. ACO is aimed at minimizing the objective function in case of both total manufacturing time and safety, so as to generate optimal sequence of operations