Ant Colony Optimization (ACO) is based on swarm intelligence and it is a constructive meta-heuristic which was first presented in 1991. Job Shop Scheduling Problem (JSSP) is very important problem of the manufacturing industry. JSSP is a combinatorial optimization problem which is NP-hard. The exact solution of NP-hard problem is very difficult to find. Therefore heuristics approach is the best approach for such problems. This paper shall overview the application of ant colony optimization on JSSP and Flexible Job Shop Scheduling problems (FJSSP). This paper shalll cover the major areas in which researchers have worked and it shall also recommend the future area of research in the light of this overview. This paper will also cover the quantitative analysis of the research papers which are considered in this survey. Based upon this survey some conclusions are drawn in the end.The significance of this paper is that it has covered all the efforts and major researches in the area of ACO application on JSSP and FJSSP through the inception of ACO metaheuristics. This enables the researchers and scheduling experts to overview chronologically the development of ACO on JSSP and FJSSP.
An Improved Ant Colony Optimization for Flexible Job Shop Scheduling Problem