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Eco-friendly multi-skilled worker assignment and assembly line balancing problem
Workforce assignment and energy consumption impact greatly on the manufacturing performance. In this work, we study a multi-skilled worker assignment and assembly line balancing problem with the consideration of energy consumption. The problem consists of scheduling products and assigning workers to...
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Published in: | Computers & industrial engineering 2021-01, Vol.151, p.106944, Article 106944 |
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creator | Liu, Rongfan Liu, Ming Chu, Feng Zheng, Feifeng Chu, Chengbin |
description | Workforce assignment and energy consumption impact greatly on the manufacturing performance. In this work, we study a multi-skilled worker assignment and assembly line balancing problem with the consideration of energy consumption. The problem consists of scheduling products and assigning workers to workstations appropriately under a given cycle time. Two objectives are minimized simultaneously, i.e., (1) the total costs including the processing cost and the fixed cost induced by employing workers, and (2) the energy consumption. A bi-objective mixed-integer linear programming model is formulated and an ϵ-constraint method is adopted to obtain the Pareto front for small-scale problems. For solving large-size problems, a processing time and energy consumption sorted-first rule (PT-EC SFR), a multi-objective genetic algorithm (NSGA-II) and a multi-objective simulated annealing method (MOSA) are developed. Numerical experiments are conducted and computational results show that the designed PT-EC SFR outperforms the other two algorithms in terms of computational time and quality of solutions.
•A multi-skilled workforce assignment problem is studied.•A bi-objective mixed-integer linear programming model is proposed for the investigated problem.•A fast and efficient constructive heuristic approach is designed to solve large-scale problems. |
doi_str_mv | 10.1016/j.cie.2020.106944 |
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•A multi-skilled workforce assignment problem is studied.•A bi-objective mixed-integer linear programming model is proposed for the investigated problem.•A fast and efficient constructive heuristic approach is designed to solve large-scale problems.</description><subject>Assembly line</subject><subject>Bi-objective optimization</subject><subject>Computer Science</subject><subject>Energy consumption</subject><subject>Operations Research</subject><subject>Workforce assignment</subject><issn>0360-8352</issn><issn>1879-0550</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMoWD9-gLe9etg6SfYTT6VUKxT0oOeQTSY1bTZbkrXSf-8uKx49De_wPAPzEnJHYU6BFg-7ubI4Z8DGXNRZdkZmtCrrFPIczskMeAFpxXN2Sa5i3AFAltd0Rt5WqktNsOi1OyXtl-ttGvfWOdTJdxf2GBIZo936Fn2fSK_HiG0zwM56TBrppFfWb5ND6BqH7Q25MNJFvP2d1-TjafW-XKeb1-eX5WKTKs5pn2ZaV0o2hmIja224Ziw3oDSVmTGlamhVgypKirypKg0SOa8zkLysGWWSN_ya3E93P6UTh2BbGU6ik1asFxsx7oADzSvKjnRg6cSq0MUY0PwJFMRYn9iJoT4x1iem-gbncXJweOJoMYg4IF6htgFVL3Rn_7F_ADSceKY</recordid><startdate>202101</startdate><enddate>202101</enddate><creator>Liu, Rongfan</creator><creator>Liu, Ming</creator><creator>Chu, Feng</creator><creator>Zheng, Feifeng</creator><creator>Chu, Chengbin</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0002-1603-4163</orcidid><orcidid>https://orcid.org/0000-0003-3190-5008</orcidid><orcidid>https://orcid.org/0000-0002-0895-7558</orcidid><orcidid>https://orcid.org/0000-0003-1225-8319</orcidid></search><sort><creationdate>202101</creationdate><title>Eco-friendly multi-skilled worker assignment and assembly line balancing problem</title><author>Liu, Rongfan ; Liu, Ming ; Chu, Feng ; Zheng, Feifeng ; Chu, Chengbin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-4dd8cabf1eba9df3d225f0cd1a4ff7cb1890c671e3b88d0ae33940a379212a3b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Assembly line</topic><topic>Bi-objective optimization</topic><topic>Computer Science</topic><topic>Energy consumption</topic><topic>Operations Research</topic><topic>Workforce assignment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Rongfan</creatorcontrib><creatorcontrib>Liu, Ming</creatorcontrib><creatorcontrib>Chu, Feng</creatorcontrib><creatorcontrib>Zheng, Feifeng</creatorcontrib><creatorcontrib>Chu, Chengbin</creatorcontrib><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Computers & industrial engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Rongfan</au><au>Liu, Ming</au><au>Chu, Feng</au><au>Zheng, Feifeng</au><au>Chu, Chengbin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Eco-friendly multi-skilled worker assignment and assembly line balancing problem</atitle><jtitle>Computers & industrial engineering</jtitle><date>2021-01</date><risdate>2021</risdate><volume>151</volume><spage>106944</spage><pages>106944-</pages><artnum>106944</artnum><issn>0360-8352</issn><eissn>1879-0550</eissn><abstract>Workforce assignment and energy consumption impact greatly on the manufacturing performance. In this work, we study a multi-skilled worker assignment and assembly line balancing problem with the consideration of energy consumption. The problem consists of scheduling products and assigning workers to workstations appropriately under a given cycle time. Two objectives are minimized simultaneously, i.e., (1) the total costs including the processing cost and the fixed cost induced by employing workers, and (2) the energy consumption. A bi-objective mixed-integer linear programming model is formulated and an ϵ-constraint method is adopted to obtain the Pareto front for small-scale problems. For solving large-size problems, a processing time and energy consumption sorted-first rule (PT-EC SFR), a multi-objective genetic algorithm (NSGA-II) and a multi-objective simulated annealing method (MOSA) are developed. Numerical experiments are conducted and computational results show that the designed PT-EC SFR outperforms the other two algorithms in terms of computational time and quality of solutions.
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subjects | Assembly line Bi-objective optimization Computer Science Energy consumption Operations Research Workforce assignment |
title | Eco-friendly multi-skilled worker assignment and assembly line balancing problem |
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