Journal of Software Engineering and Applications, 2016, 9, 208-214 Published Online May 2016 in SciRes. http://www.scirp.org/journal/jsea http://dx.doi.org/10.4236/jsea.2016.95017 How to cite this paper: Jorapur, V.S., Puranik, V.S., Deshpande, A.S. and Sharma, M. (2016) A Promising Initial Population Based Genetic Algorithm for Job Shop Scheduling Problem. Journal of Software Engineering and Applications, 9, 208-214. http://dx.doi.org/10.4236/jsea.2016.95017 A Promising Initial Population Based Genetic Algorithm for Job Shop Scheduling Problem Vedavyasrao S. Jorapur 1 , Vinod S. Puranik 2 , Anand S. Deshpande 3 , Mahesh Sharma 4 1 Department of Industrial and Production Engineering, Basaveshwar Engineering College, Bagalkot, India 2 Basaveshwar Engineering College, Bagalkot, India 3 Gogte Institute of Technology, Belagavi, India 4 Fr. Conceicao Rodrigues College of Engineering, Bandra, West Mumbai, India Received 29 September 2015; accepted 24 May 2016; published 27 May 2016 Copyright © 2016 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract Job shop scheduling problem is typically a NP-Hard problem. In the recent past efforts put by re- searchers were to provide the most generic genetic algorithm to solve efficiently the job shop scheduling problems. Less attention has been paid to initial population aspects in genetic algo- rithms and much attention to recombination operators. Therefore authors are of the opinion that by proper design of all the aspects in genetic algorithms starting from initial population may pro- vide better and promising solutions. Hence this paper attempts to enhance the effectiveness of genetic algorithm by providing a new look to initial population. This new technique along with job based representation has been used to obtain the optimal or near optimal solutions of 66 bench- mark instances which comprise of varying degree of complexity. Keywords Job Shop Scheduling, Job Based Representation, NP-Hard, Recombination Operators etc. 1. Introduction Scheduling is one of the most critical issues in planning and managing of manufacturing activities. Mathemati- cally it is treated as NP-Hard problem. An optimal schedule for a given problem (a manufacturing industry) de- pends on so many factors like shop floor condition, constraints with which each process is carried out and so on.