A fuzzy bi-objective flexible cell scheduling optimization model under green and energy-efficient strategy using Pareto-based algorithms: SATPSPGA, SANRGA, and NSGA-II

Far, Mohammad Hemmati; Haleh, Hassan; Saghaei, Abbas

doi:10.1007/s00170-019-03797-w

Cited by 11 publications

(2 citation statements)

References 52 publications

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“…Far et al [73] propose a bi-objective flexible cell scheduling problem under time-of-use electricity tariffs in both deterministic and fuzzy environments with two objectives: total cost of production system and total delivery tardiness of jobs. To create a form of green and energy-conscious strategy, cost of produced emission and consumed power and some limitations are respected.…”

Section: Editorial Overview Of This Special Issue Papers and Their Comentioning

confidence: 99%

Design and management of digital manufacturing and assembly systems in the Industry 4.0 era

Cohen

Faccio

Pilati

et al. 2019

Int J Adv Manuf Technol

134

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The advances in Industry 4.0 provide both challenges and opportunities for digital manufacturing and assembly systems. This paper first addresses the state-of-the-art readiness for Industry 4.0 concerning assembly and manufacturing systems through a literature review of the relevant papers recently published. Then it assesses the challenges faced nowadays by assembly and manufacturing systems. Third, it focuses on the most promising future developments and evolution of such production systems as well as their digitalisation. Finally, this manuscript illustrates the content of the papers selected for this special issue. Through the study presented in this special issue, valuable contributions to both theory and application in this area have been achieved, and a useful reference for future research is given.

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Section: Editorial Overview Of This Special Issue Papers and Their Comentioning

confidence: 99%

Design and management of digital manufacturing and assembly systems in the Industry 4.0 era

Cohen

Faccio

Pilati

et al. 2019

Int J Adv Manuf Technol

134

View full text Add to dashboard Cite

show abstract

“…They established an electricity cost model with ToU pricing by dividing the energetic status of machines into waiting, setup and process, and proposed a parallel gene expression programming approach to minimize the total production cost. Far et al [6] extended some limitations on entire energy consumption, total manufactured emission and part defect percentage, and presented a self-adaptive two-phase subpopulation genetic algorithm to find a near-optimum solution of total cost and total delivery tardiness. Moon and Park [7], Hadera et al [8] and Hadera et al [9] presented FJSPs with generators and energy storage systems under ToU pricing.…”

Section: Introductionmentioning

confidence: 99%

A GAPN Approach for the Flexible Job-Shop Scheduling Problem with Indirect Energy and Time-of-Use Electricity Pricing

Guo

Luo²,

Peng

et al. 2022

Processes

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The flexible job-shop scheduling problem with indirect energy and time-of-use (ToU) electricity pricing (FJSP-IT) is investigated. Considering the production cost, which includes the indirect energy cost, direct energy cost and time cost, the cost evaluation model under ToU pricing is built. To minimize the total production cost of the FJSP-IT, an approach based on a genetic algorithm and Petri nets (GAPN) is presented. Under this approach, indirect energy and direct energy are modeled with Petri net (PN) nodes, the operation time is evaluated through PN simulation, and resource allocation is fine-tuned through genetic operations. A group of heuristic operation time policies, especially the exhausting subsection policy and two mixed policies, are presented to adapt to the FJSP-IT with vague cost components. Experiments were performed on a data set generated from the banburying shop of a rubber tire plant, and the results show that the proposed GAPN approach has good convergence. Using the proposed operation time policies makes it possible to save 10.81% on the production cost compared to using the single off-peak first or passive delay policy, and considering indirect energy makes it possible to save at least 2.09% on the production cost compared to ignoring indirect energy.

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Robust parallel-batching scheduling with fuzzy deteriorating processing time and variable delivery time in smart manufacturing

Pei

Liu

et al. 2020

Fuzzy Optim Decis Making

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A fuzzy bi-objective flexible cell scheduling optimization model under green and energy-efficient strategy using Pareto-based algorithms: SATPSPGA, SANRGA, and NSGA-II

Cited by 11 publications

References 52 publications

Design and management of digital manufacturing and assembly systems in the Industry 4.0 era

Design and management of digital manufacturing and assembly systems in the Industry 4.0 era

A GAPN Approach for the Flexible Job-Shop Scheduling Problem with Indirect Energy and Time-of-Use Electricity Pricing

Robust parallel-batching scheduling with fuzzy deteriorating processing time and variable delivery time in smart manufacturing

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