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Cited by 18Scheduling and Optimization AlgorithmsAdvanced Manufacturing and Logistics OptimizationHealthcare Operations and Scheduling Optimization

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Integrating sustainability into production scheduling in hybrid flow-shop environments

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Mokhtari-Moghadam, Ali, Pourhejazy, Pourya, Gupta, Deepak·2023·Environmental Science and Pollution Research
DOI 10.1007/s11356-023-26986-3
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Abstract

Global energy consumption is projected to grow by nearly 50% as of 2018, reaching a peak of 910.7 quadrillion BTU in 2050. The industrial sector accounts for the largest share of the energy consumed, making energy awareness on the shop floors imperative for promoting industrial sustainable development. Considering a growing awareness of the importance of sustainability, production planning and control require the incorporation of time-of-use electricity pricing models into scheduling problems for well-informed energy-saving decisions. Besides, modern manufacturing emphasizes the role of human factors in production processes. This study proposes a new approach for optimizing the hybrid flow-shop scheduling problems (HFSP) considering time-of-use electricity pricing, workers’ flexibility, and sequence-dependent setup time (SDST). Novelties of this study are twofold: to extend a new mathematical formulation and to develop an improved multi-objective optimization algorithm. Extensive numerical experiments are conducted to evaluate the performance of the developed solution method, the adjusted multi-objective genetic algorithm (AMOGA), comparing it with the state-of-the-art, i.e., strength Pareto evolutionary algorithm (SPEA2), and Pareto envelop-based selection algorithm (PESA2). It is shown that AMOGA performs better than the benchmarks considering the mean ideal distance, inverted generational distance, diversification, and quality metrics, providing more versatile and better solutions for production and energy efficiency.

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Metadata

Authors
Mokhtari-Moghadam, A., Pourhejazy, P., & Gupta, D.
Affiliations
  • UiT The Arctic University of Norway (NO)
  • Wichita State University (US)
Corresponding author
Pourhejazy, Pourya
ORCID
Pourhejazy, Pourya
Venue
Environmental Science and Pollution Research
Publisher
Springer Science and Business Media LLC
Published
2023-04-24
ISSN
  • 0944-1344 (ISSN-L)
  • 1614-7499
DOI
10.1007/s11356-023-26986-3
OpenAlex
W4366816593
Cited by
18
References
0
Citations by year
2026: 2 · 2025: 5 · 2024: 9 · 2023: 2
FWCI
2.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Environmental Science and Pollution Research (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Holmes Museum Of Anthropology (Wichita State University) (submittedVersion)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
Funders
UiT The Arctic University of Norway
Topics
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Scheduling and Optimization Algorithms
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Advanced Manufacturing and Logistics Optimization
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Healthcare Operations and Scheduling Optimization
Keywords
hybrid flow shop scheduling, sustainability, energy efficiency, time-of-use electricity pricing, worker flexibility, sequence-dependent setup times, multi-objective optimization, multi-objective genetic algorithm, production planning and control, industrial energy consumption

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CoChat. (2026). Citation check: Integrating sustainability into production scheduling in hybrid flow-shop environments. https://app.cochat.ai/papers/10.1007/s11356-023-26986-3
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Mokhtari-Moghadam, A., Pourhejazy, P., & Gupta, D. (2023). Integrating sustainability into production scheduling in hybrid flow-shop environments. Environmental Science and Pollution Research. https://doi.org/10.1007/s11356-023-26986-3