Abstract
This paper presents a hybrid Simulation based Optimization (SbO) approach to solve job shop scheduling problems. SbO structure for classical job shop scheduling introduced by [6] is extended for flexible job shop scheduling problem (FJSSP). Performance of SbO is bench-marked in terms of number of decision variables, constraints, objective value and computational time against various Mixed Integer Programming (MIP) based methods from literature. SbO outperforms for all the parameters and performs better with increasing problem size. Further, an hybrid solution architecture, Combined Simulation & Optimization (CSO) is introduced which integrates SbO and MIP to expedite the convergence to exact optimal solution. Results for CSO are also bench-marked against MIP based approaches, which shows that CSO performs better and converges faster.
Published Version
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