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Computers and Industrial Engineering 33(3-4) 793–796 (1997).[45] J´ozefowska J. Mika M. R´o˙zycki R. and Walig´ora G. Local Search Metaheuristics for DiscreteContinuous Scheduling Problems . European Journal of Operational Research 107 354–370 (1998).[46] Hindi K. and Mhlanga S. Scheduling Linearly Deteriorating Jobs on Parallel Machines: A Simulated Annealing Approach . Production Planning and Control 12(1) 76–80 (2001).[47] Kim D.-W. Kim K.-H. Jang W. and Chen F. Unrelated Parallel Machine Scheduling with Setup Times Using Simulated Annealing . Robotics and Computer Integrated Manufacturing 18(3-4) 223–231 (2002).2146-09572146-5703https://gcris.yasar.edu.tr/handle/123456789/11019https://search.trdizin.gov.tr/en/yayin/detay/240475This study focuses on identical parallel machine scheduling of jobs with deteriorating processing times and rate-modifying activities. We consider nonlinearly increasing processing times of jobs based on their position assignment. Rate modifying activities (RMAs) are also considered to recover the increase in processing times of jobs due to deterioration. We also propose heuristics algorithms that rely on ant colony optimization and simulated annealing algorithms to solve the problem with multiple RMAs in a reasonable amount of time. Finally we show that ant colony optimization algorithm generates close optimal solutions and superior results than simulated annealing algorithm.İngilizceinfo:eu-repo/semantics/openAccessMatematik-Bilgisayar Bilimleri- Teori ve MetotlarBilgisayar Bilimleri, Teori Ve MetotlarMatematikArticle