Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony

This study examined the flexible assembly job-shop scheduling problem with lot streaming (FAJSP-LS), common in multivariety and small-batch production, such as household electrical appliances. In FAJSP-LS, an assembly stage is appended to the flexible job shop, and jobs in the first stage are proces...
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Autor*in:	Xiulin Li [verfasserIn] Jiansha Lu [verfasserIn] Chenxi Yang [verfasserIn] Jiale Wang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	flexible assembly job shop batch splitting batch scheduling lot streaming consistent size unequal size

Übergeordnetes Werk:	In: Frontiers in Bioengineering and Biotechnology - Frontiers Media S.A., 2014, 10(2022)
Übergeordnetes Werk:	volume:10 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fbioe.2022.909548

Katalog-ID:	DOAJ015512002

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language	English
source	In Frontiers in Bioengineering and Biotechnology 10(2022) volume:10 year:2022
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topic_facet	flexible assembly job shop batch splitting batch scheduling lot streaming consistent size unequal size Biotechnology
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container_title	Frontiers in Bioengineering and Biotechnology
authorswithroles_txt_mv	Xiulin Li @@aut@@ Jiansha Lu @@aut@@ Chenxi Yang @@aut@@ Jiale Wang @@aut@@
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callnumber-first	T - Technology
author	Xiulin Li
spellingShingle	Xiulin Li misc TP248.13-248.65 misc flexible assembly job shop misc batch splitting misc batch scheduling misc lot streaming misc consistent size misc unequal size misc Biotechnology Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony
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topic_title	TP248.13-248.65 Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony flexible assembly job shop batch splitting batch scheduling lot streaming consistent size unequal size
topic	misc TP248.13-248.65 misc flexible assembly job shop misc batch splitting misc batch scheduling misc lot streaming misc consistent size misc unequal size misc Biotechnology
topic_unstemmed	misc TP248.13-248.65 misc flexible assembly job shop misc batch splitting misc batch scheduling misc lot streaming misc consistent size misc unequal size misc Biotechnology
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title	Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony
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title_full	Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony
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title_sort	research of flexible assembly job-shop batch–scheduling problem based on improved artificial bee colony
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title_auth	Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony
abstract	This study examined the flexible assembly job-shop scheduling problem with lot streaming (FAJSP-LS), common in multivariety and small-batch production, such as household electrical appliances. In FAJSP-LS, an assembly stage is appended to the flexible job shop, and jobs in the first stage are processed in a large batch to reduce switching costs, while leading to more waiting time, especially during the assembly stage. This article considered splitting the batch into a few sub-batches of unequal and consistent sizes to allow jobs to efficiently pass the two-stage system. With this objective, the problem was modeled as a mixed-integer linear program comprising the following two subproblems: batch splitting and batch scheduling. As the integrated problem is NP-hard, the improved bioinspired algorithm based on an artificial bee colony was proposed, including a four-layer chromosome–encoding structure to describe the solution, as well as an optimization strategy utilizing different bee colonies to synchronously solve this two-stage problem. To examine the algorithm’s efficiency, a benchmark case was used to show that better solutions can be acquired with the improved algorithm regardless of whether the batch was split into equal or unequal sizes. To promote practical implementation, the algorithm was applied to a real case refrigerator workshop and showed better performance on time efficiency when jobs were split into unequal sizes compared to jobs without splitting or splitting into equal sizes.
abstractGer	This study examined the flexible assembly job-shop scheduling problem with lot streaming (FAJSP-LS), common in multivariety and small-batch production, such as household electrical appliances. In FAJSP-LS, an assembly stage is appended to the flexible job shop, and jobs in the first stage are processed in a large batch to reduce switching costs, while leading to more waiting time, especially during the assembly stage. This article considered splitting the batch into a few sub-batches of unequal and consistent sizes to allow jobs to efficiently pass the two-stage system. With this objective, the problem was modeled as a mixed-integer linear program comprising the following two subproblems: batch splitting and batch scheduling. As the integrated problem is NP-hard, the improved bioinspired algorithm based on an artificial bee colony was proposed, including a four-layer chromosome–encoding structure to describe the solution, as well as an optimization strategy utilizing different bee colonies to synchronously solve this two-stage problem. To examine the algorithm’s efficiency, a benchmark case was used to show that better solutions can be acquired with the improved algorithm regardless of whether the batch was split into equal or unequal sizes. To promote practical implementation, the algorithm was applied to a real case refrigerator workshop and showed better performance on time efficiency when jobs were split into unequal sizes compared to jobs without splitting or splitting into equal sizes.
abstract_unstemmed	This study examined the flexible assembly job-shop scheduling problem with lot streaming (FAJSP-LS), common in multivariety and small-batch production, such as household electrical appliances. In FAJSP-LS, an assembly stage is appended to the flexible job shop, and jobs in the first stage are processed in a large batch to reduce switching costs, while leading to more waiting time, especially during the assembly stage. This article considered splitting the batch into a few sub-batches of unequal and consistent sizes to allow jobs to efficiently pass the two-stage system. With this objective, the problem was modeled as a mixed-integer linear program comprising the following two subproblems: batch splitting and batch scheduling. As the integrated problem is NP-hard, the improved bioinspired algorithm based on an artificial bee colony was proposed, including a four-layer chromosome–encoding structure to describe the solution, as well as an optimization strategy utilizing different bee colonies to synchronously solve this two-stage problem. To examine the algorithm’s efficiency, a benchmark case was used to show that better solutions can be acquired with the improved algorithm regardless of whether the batch was split into equal or unequal sizes. To promote practical implementation, the algorithm was applied to a real case refrigerator workshop and showed better performance on time efficiency when jobs were split into unequal sizes compared to jobs without splitting or splitting into equal sizes.
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title_short	Research of Flexible Assembly Job-Shop Batch–Scheduling Problem Based on Improved Artificial Bee Colony
url	https://doi.org/10.3389/fbioe.2022.909548 https://doaj.org/article/7d19c2a454a14941b165931af8b6f4b5 https://www.frontiersin.org/articles/10.3389/fbioe.2022.909548/full https://doaj.org/toc/2296-4185
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