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Thus, it is not possible to reduce the problem to a single-objective optimization, and a set of efficient (nondominated) solutions, a so-called Pareto front, must be found. Moreover, in manufacturing environments, disruptive changes usually emerge in scheduling problems, such as machine breakdowns or the arrival of new jobs, causing a need for fast schedule adaptation. In this paper, a mathematical model for this type of problem is proposed and a restarted iterated Pareto greedy (RIPG) metaheuristic is used to find the optimal Pareto front. To demonstrate the appropriateness of this approach, the algorithm is applied to a benchmark specifically designed in this study, considering three objective functions (makespan, total weighted tardiness, and steadiness) and three classes of disruptions (appearance of new jobs, machine faults, and changes in operational times). Experimental studies indicate the proposed approach can effectively solve rescheduling tasks in a multiobjective environment.<\/jats:p>","DOI":"10.1155\/2020\/2862186","type":"journal-article","created":{"date-parts":[[2020,7,24]],"date-time":"2020-07-24T23:32:07Z","timestamp":1595633527000},"page":"1-17","source":"Crossref","is-referenced-by-count":9,"title":["Modelling and Solving Rescheduling Problems in Dynamic Permutation Flow Shop Environments"],"prefix":"10.1155","volume":"2020","author":[{"given":"Pablo","family":"Valledor","sequence":"first","affiliation":[{"name":"ArcelorMittal Inc., Global R&D Asturias, Gij\u00f3n, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3570-4043","authenticated-orcid":true,"given":"Alberto","family":"Gomez","sequence":"additional","affiliation":[{"name":"University of Oviedo, Department of Business Administration, Polytechnic School of Engineering, 33203 Gij\u00f3n, 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