NEW OPTIMIZATION APPROACH FOR SCHEDULING THE BATCH HEAT TREATMENT PROCESS WITH SEQUENCE DEPENDENT SETUP TIMES

摘要

The Shaking Optimization Algorithm is among the newlyrndeveloped optimization algorithms that belong to thernEvolutionary Computations Algorithms. It combinesrnheuristics with randomness in the evolution process ratherrnthan just apply operators e.g., mutation, recombination,rnand/or selection rules. It has been used successfully tornsolve the classic Job Shop Scheduling Problem, thernCutting Stock Problem, and the UnconstrainedrnEngineering Optimization Problems, and the results showrnthat the algorithm is a good competitive to otherrnevolutionary computation algorithms e.g., the GeneticrnAlgorithm and the Particle Swarm Optimization regardingrnsolution time, efficiency, and complicity. This paper usesrnthe SOA algorithm to solve the scheduling problem of thernBatch Annealing Process with Sequence-Dependent SetuprnTimes in the heat treatment of steel coils as one ofrncomplex scheduling problems. The objective is torndetermine the movement schedule of shared equipmentrnamong parallel bases that gives minimum makespan forrnprocessing a given batch size. The bell-type batchrnannealing process is used here for the comparative study.rnThe results show that the proposed approach is able tornsolve this class of problems as well in a reasonable timernand gives competitive results to other algorithms.