Hande OztopM. Fatih TasgetirenD. T. EliiyiQuanke PanD. Huang , K. Han , A. Hussain , M.M. Gromiha2025-10-0620189789819698936, 9789819698042, 9789819698110, 9789819698905, 9789819512324, 9783032026019, 9783032008909, 9783031915802, 9789819698141, 978303198413616113349, 0302974310.1007/978-3-319-95957-3_79https://www.scopus.com/inward/record.uri?eid=2-s2.0-85051847462&doi=10.1007%2F978-3-319-95957-3_79&partnerID=40&md5=7a7a1a40ae14709f9a6a68b8150e218dhttps://gcris.yasar.edu.tr/handle/123456789/9618Permutation flow shop scheduling problem (PFSP) is a well-known problem in the scheduling literature. Even though many multi-objective PFSPs are presented in the literature with the objectives related to production efficiency and customer satisfaction studies considering energy consumption and environmental effects in scheduling is very seldom. In this paper the trade-off between total energy consumption (TEC) and total flow time is investigated in a PFSP environment where the machines are assumed to operate at varying speed levels. A multi-objective mixed integer linear programming model is proposed based on a speed-scaling strategy. Due to the NP-complete nature of the problem an efficient multi-objective iterated greedy (IG<inf>ALL</inf>) algorithm is also developed. The performance of IG<inf>ALL</inf> is compared with model performance in terms of quality and cardinality of the solutions. © 2018 Elsevier B.V. All rights reserved.EnglishEnergy Efficient Scheduling, Heuristic Optimization, Iterated Greedy Algorithm, Multi-objective Optimization, Permutation Flowshop Scheduling, Customer Satisfaction, Economic And Social Effects, Energy Utilization, Integer Programming, Intelligent Computing, Multiobjective Optimization, Scheduling, Energy-efficient Scheduling, Heuristic Optimization, Iterated Greedy Algorithm, Mixed Integer Linear Programming Model, Model Performance, Permutation Flow-shop Scheduling, Production Efficiency, Total Energy Consumption (tec), Energy EfficiencyCustomer satisfaction, Economic and social effects, Energy utilization, Integer programming, Intelligent computing, Multiobjective optimization, Scheduling, Energy-Efficient Scheduling, Heuristic optimization, Iterated greedy algorithm, Mixed integer linear programming model, Model performance, Permutation flow-shop scheduling, Production efficiency, Total energy consumption (TEC), Energy efficiencyConference Object