Application of Metaheuristics in Scheduling Continuous/ Semi-continuous Process Industries and a Case Study

dc.contributor.advisorDefersha, Fantahun
dc.contributor.authorJalalian, Mohammad Moein of Engineeringen_US of Guelphen_US of Applied Scienceen_US
dc.description.abstractIn today's competitive industry, scheduling plays a significant role in improving the efficiency of manufacturing systems. Hence, many scholars and practitioners have been researching to enhance the quality of scheduling methods. In this research, the focus is on solving a real-world scheduling problem in the food industry which was previously dealt with a very time-consuming manual method without high-quality solutions. The problem is to find the best schedule for producing multiple products on multiple machines in a semi-continuous manufacturing system. Having a continuous section in the system makes scheduling too complicated than the manual method could deal with properly. So, similar to many scheduling problems, in this thesis, metaheuristics (GA and MPSA) are applied to the problem in order to address the defects of the manual method. Selected methods show promising results and performance against the manual method used before. Statistical analysis shows better performance of the genetic algorithm while the other method is more robust to the selected parameters.en_US
dc.publisherUniversity of Guelphen_US
dc.rights.licenseAll items in the Atrium are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectGenetic Algorithmen_US
dc.subjectSimulated Annealingen_US
dc.subjectProcess Industryen_US
dc.subjectContinuous Productionen_US
dc.subjectSemi-continuous Productionen_US
dc.subjectFood processingen_US
dc.titleApplication of Metaheuristics in Scheduling Continuous/ Semi-continuous Process Industries and a Case Studyen_US


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