Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation

We investigate parallel-machine scheduling with past-sequence-dependent (p-s-d) delivery times, DeJong’s learning effect, rate-modifying activity, and resource allocation. Each machine has a rate-modifying activity. We consider two versions of the problem to minimize the sum of the total completion...

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Main Authors: Li Sun, Bin Wu, Lei Ning
Format: Article
Language:English
Published: Wiley 2021-01-01
Series:Shock and Vibration
Online Access:http://dx.doi.org/10.1155/2021/6687525
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author Li Sun
Bin Wu
Lei Ning
author_facet Li Sun
Bin Wu
Lei Ning
author_sort Li Sun
collection DOAJ
description We investigate parallel-machine scheduling with past-sequence-dependent (p-s-d) delivery times, DeJong’s learning effect, rate-modifying activity, and resource allocation. Each machine has a rate-modifying activity. We consider two versions of the problem to minimize the sum of the total completion times, the total absolute deviation of job completion times, and the total resource allocation and the sum of the total waiting times, the total absolute deviation of job waiting times, and the total resource allocation, respectively. The problems under our present model can be solved in polynomial time.
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institution Kabale University
issn 1070-9622
1875-9203
language English
publishDate 2021-01-01
publisher Wiley
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series Shock and Vibration
spelling doaj-art-a717f0d481e04a36bec829b9bab64e7f2025-08-20T03:38:49ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/66875256687525Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource AllocationLi Sun0Bin Wu1Lei Ning2School of Business, Shanghai Dianji University, Shanghai 201306, ChinaSchool of Business, Shanghai Dianji University, Shanghai 201306, ChinaCollege of Engineering Science and Technology, Shanghai Ocean University, Shanghai 201306, ChinaWe investigate parallel-machine scheduling with past-sequence-dependent (p-s-d) delivery times, DeJong’s learning effect, rate-modifying activity, and resource allocation. Each machine has a rate-modifying activity. We consider two versions of the problem to minimize the sum of the total completion times, the total absolute deviation of job completion times, and the total resource allocation and the sum of the total waiting times, the total absolute deviation of job waiting times, and the total resource allocation, respectively. The problems under our present model can be solved in polynomial time.http://dx.doi.org/10.1155/2021/6687525
spellingShingle Li Sun
Bin Wu
Lei Ning
Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation
Shock and Vibration
title Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation
title_full Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation
title_fullStr Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation
title_full_unstemmed Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation
title_short Parallel-Machine Scheduling with DeJong’s Learning Effect, Delivery Times, Rate-Modifying Activity, and Resource Allocation
title_sort parallel machine scheduling with dejong s learning effect delivery times rate modifying activity and resource allocation
url http://dx.doi.org/10.1155/2021/6687525
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AT binwu parallelmachineschedulingwithdejongslearningeffectdeliverytimesratemodifyingactivityandresourceallocation
AT leining parallelmachineschedulingwithdejongslearningeffectdeliverytimesratemodifyingactivityandresourceallocation