No-Idle Flowshop Scheduling for Energy-Efficient Production: An Improved Optimization Framework

Production environment in modern industries, like integrated circuits manufacturing, fiberglass processing, steelmaking, and ceramic frit, is characterized by zero idle-time between inbound and outbound jobs on every machine; this technical requirement improves energy efficiency, hence, has implications for cleaner production in other production situations. An exhaustive review of literature is first conducted to shed light on the development of no-idle flowshops. Considering the intractable nature of the problem, this research also develops an extended solution method for optimizing the Bi-objective No-Idle Permutation Flowshop Scheduling Problem (BNIPFSP). Extensive numerical tests and statistical analysis are conducted to evaluate the developed method, comparing it with the best-performing algorithm developed to solve the BNIPFSP. Overall, the proposed extension outperforms in terms of solution quality at the expense of a longer computational time. This research is concluded by providing suggestions for the future development of this understudied scheduling extension.

[1]  Yi-Ming Wei,et al.  The differences of carbon intensity reduction rate across 89 countries in recent three decades , 2014 .

[2]  M. F. Tasgetiren,et al.  A differential evolution algorithm for the no-idle flowshop scheduling problem with total tardiness criterion , 2011 .

[3]  Fuqing Zhao,et al.  A cooperative water wave optimization algorithm with reinforcement learning for the distributed assembly no-idle flowshop scheduling problem , 2021, Comput. Ind. Eng..

[4]  Cheng Wu,et al.  New block properties for flowshop scheduling with blocking and their application in an iterated greedy algorithm , 2016 .

[5]  Tsai C. Kuo,et al.  Environmentally conscious design and manufacturing: A state-of-the-art survey , 1997 .

[6]  Marcelo Seido Nagano,et al.  Heuristics for the mixed no-idle flowshop with sequence-dependent setup times and total flowtime criterion , 2019, Expert Syst. Appl..

[7]  Jose M. Framiñan,et al.  Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective , 2010, Comput. Oper. Res..

[8]  Kate Smith-Miles,et al.  The impact of various carbon reduction policies on green flowshop scheduling , 2019, Applied Energy.

[9]  Thomas Stützle,et al.  Automatic design of hybrid stochastic local search algorithms for permutation flowshop problems with additional constraints , 2021 .

[10]  Marcelo Seido Nagano,et al.  Heuristics for the mixed no-idle flowshop with sequence-dependent setup times , 2019, J. Oper. Res. Soc..

[11]  Joseph Y.-T. Leung,et al.  Parallel machine scheduling problems in green manufacturing industry , 2016 .

[12]  Raymond Chiong,et al.  A Distributionally Robust Scheduling Approach for Uncertain Steelmaking and Continuous Casting Processes , 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[13]  Tolga Bektaş,et al.  Benders decomposition for the mixed no-idle permutation flowshop scheduling problem , 2020, J. Sched..

[14]  Kuan Yew Wong,et al.  Minimizing total carbon footprint and total late work criterion in flexible job shop scheduling by using an improved multi-objective genetic algorithm , 2018 .

[15]  Chen Peng,et al.  Minimising Non-Processing Energy Consumption and Tardiness Fines in a Mixed-Flow Shop , 2018, Energies.

[16]  Jatinder N. D. Gupta,et al.  A comprehensive review of flowshop group scheduling literature , 2016, Comput. Oper. Res..

[17]  Pourya Pourhejazy,et al.  A Practical Review of Green Supply Chain Management: Disciplines and Best Practices , 2016 .

[18]  Xiao-Long Zheng,et al.  A Collaborative Multiobjective Fruit Fly Optimization Algorithm for the Resource Constrained Unrelated Parallel Machine Green Scheduling Problem , 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[19]  Rubén Ruiz,et al.  Scheduling in Flowshops with No-Idle Machines , 2009 .

[20]  Fuqing Zhao,et al.  A hybrid discrete water wave optimization algorithm for the no-idle flowshop scheduling problem with total tardiness criterion , 2020, Expert Syst. Appl..

[21]  Xinyu Li,et al.  A multiobjective evolutionary algorithm based on decomposition for hybrid flowshop green scheduling problem , 2019, Comput. Ind. Eng..

[22]  Yuan-Yuan Lu,et al.  Research on no-idle permutation flowshop scheduling with time-dependent learning effect and deteriorating jobs , 2016 .

[23]  Raymond Chiong,et al.  A new iterated greedy algorithm for no-idle permutation flowshop scheduling with the total tardiness criterion , 2020, Comput. Oper. Res..

[24]  Xinyu Li,et al.  A Variable Iterated Local Search Algorithm for Energy-Efficient No-idle Flowshop Scheduling Problem , 2019, Procedia Manufacturing.

[25]  Chen-Yang Cheng,et al.  Unsupervised Learning-based Artificial Bee Colony for minimizing non-value-adding operations , 2021, Appl. Soft Comput..

[26]  Milan Vlach,et al.  Minimizing total completion time in a two-machine no-idle flowshop , 1998 .

[27]  Thomas Stützle,et al.  A simple and effective iterated greedy algorithm for the permutation flowshop scheduling problem , 2007, Eur. J. Oper. Res..

[28]  Tax Carbon Emissions and Credit Removal , 2019, Joule.

[29]  S. Afshin Mansouri,et al.  Green scheduling of a two-machine flowshop: Trade-off between makespan and energy consumption , 2016, Eur. J. Oper. Res..

[30]  Mehmet Fatih Tasgetiren,et al.  A variable iterated greedy algorithm with differential evolution for the no-idle permutation flowshop scheduling problem , 2013, Comput. Oper. Res..

[31]  Han Hong-yan Tabu search algorithm for no-idle flowshop scheduling problems , 2010 .

[32]  Quan-Ke Pan,et al.  A discrete artificial bee colony algorithm for the no-idle permutation flowshop scheduling problem with the total tardiness criterion , 2013 .

[33]  Milan Vlach,et al.  Note: On the two-machine no-idle flowshop problem , 2000 .

[34]  Marcelo Seido Nagano,et al.  Heuristics and metaheuristics for the mixed no-idle flowshop with sequence-dependent setup times and total tardiness minimisation , 2020, Swarm Evol. Comput..

[35]  Fengshan Bai,et al.  No-wait flexible flowshop scheduling with no-idle machines , 2005, Oper. Res. Lett..

[36]  Xiuli Wu,et al.  A green scheduling algorithm for flexible job shop with energy-saving measures , 2018 .

[37]  Inyong Ham,et al.  A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem , 1983 .

[38]  Éric D. Taillard,et al.  Benchmarks for basic scheduling problems , 1993 .

[39]  Frederico G. Guimarães,et al.  Bi-criteria formulation for green scheduling with unrelated parallel machines with sequence-dependent setup times , 2021, Int. Trans. Oper. Res..

[40]  P. C. Bagga,et al.  Flowshop/no-idle scheduling to minimise the mean flowtime , 2005, The ANZIAM Journal.

[41]  Marcelo Seido Nagano,et al.  High-performing heuristics to minimize flowtime in no-idle permutation flowshop , 2019 .

[42]  Seyed Taghi Akhavan Niaki,et al.  Bi-objective green scheduling in uniform parallel machine environments , 2019, Journal of Cleaner Production.

[43]  Quan-Ke Pan,et al.  An effective iterated greedy algorithm for the mixed no-idle permutation flowshop scheduling problem , 2014 .

[44]  Alice Yalaoui,et al.  Complexity analysis of energy-efficient single machine scheduling problems , 2019, Operations Research Perspectives.

[45]  Pourya Pourhejazy,et al.  Integrating Sustainability into the Optimization of Fuel Logistics Networks , 2019, KSCE Journal of Civil Engineering.

[46]  Chao Zhang,et al.  Green Job Shop Scheduling Problem With Discrete Whale Optimization Algorithm , 2019, IEEE Access.

[47]  Hande Öztop,et al.  A Novel General Variable Neighborhood Search through Q-Learning for No-Idle Flowshop Scheduling , 2020, 2020 IEEE Congress on Evolutionary Computation (CEC).

[48]  E.L. Lawler,et al.  Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey , 1977 .

[49]  I. Osman,et al.  Simulated annealing for permutation flow-shop scheduling , 1989 .