Work place: Department of Computer Science & Engineering, Rajarambapu Institute of Technology Sakharale, MS, India
S. V. Kamble is presently working as an Assistant Professor in Information Technology at DKTE’s Textile and Engineering Institute, Ichalkaranji, MS, India. He has received his Bachelor of Engineering (BE) in Information Technology from TKIET, Warananagar, MS, India and his Master of Technology (M.Tech.) in Computer Science and Engineering (CSE) from RIT, Sakhrale, MS, India.
He has 9 years of teaching experience. His research interests include Scheduling and Optimizations. He has published about 06 research papers in Conferences and Journals.
DOI: https://doi.org/10.5815/ijisa.2015.04.08, Pub. Date: 8 Mar. 2015
Hybrid algorithm based on Particle Swarm Optimization (PSO) and Simulated annealing (SA) is proposed, to solve Flexible Job Shop Scheduling with five objectives to be minimized simultaneously: makespan, maximal machine workload, total workload, machine idle time & total tardiness. Rescheduling strategy used to shuffle workload once the machine breakdown takes place in proposed algorithm. The hybrid algorithm combines the high global search efficiency of PSO with the powerful ability to avoid being trapped in local minimum of SA. A hybrid multi-objective PSO (MPSO) and SA algorithm is proposed to identify an approximation of the pareto front for Flexible job shop scheduling (FJSSP). Pareto front and crowding distance is used for identify the fitness of particle. MPSO is significant to global search and SA used to local search. The proposed MPSO algorithm is experimentally applied on two benchmark data set. The result shows that the proposed algorithm is better in term quality of non-dominated solution compared to the other algorithms in the literature.[...] Read more.
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