S. U. Mane

Work place: Department of Computer Science & Engineering, Rajarambapu Institute of Technology Sakharale, MS, India

E-mail: sandip.mane@ritindia.edu


Research Interests:


S. U. Mane is presently working as an Assistant Professor in Computer Science and Engineering at RIT, Sakhrale, MS, India. He has received his Bachelor of Engineering (BE) in Information Technology from BVCOE, Kolhapur, MS, India and his Master of Technology (M.Tech.) in Computer Science and Engineering (CSE) from BATU, Lonere, MS, India.

He has 7 years of teaching experience at UG and 3 years at PG. His research interests include High Performance Computing using GPGPU, Searching, Scheduling and Optimization Methods, Parallelization of Heuristic and Meta-Heuristic Methods, Constraint Satisfaction Problems and Scheduling Problems. He has published about 8 research papers in Conferences and Journals.

Author Articles
Hybrid Multi-Objective Particle Swarm Optimization for Flexible Job Shop Scheduling Problem

By S. V. Kamble S. U. Mane A. J. Umbarkar

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.

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