Production Scheduling considering Outsourcing Options and Carrier Costs
We consider a single-machine scheduling problem with outsourcing options in an environment where the cost information of the downstream is available via some information sharing technologies. The due date is assigned to the position differently from the traditional due date. Each job can be processe...
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Online Access: | http://dx.doi.org/10.1155/2020/7069291 |
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doaj-7fd63d3bde7340939a743554559a9dcc2020-11-25T02:56:05ZengHindawi-WileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/70692917069291Production Scheduling considering Outsourcing Options and Carrier CostsByung-Cheon Choi0Yunhong Min1Myoung-Ju Park2Kyung Min Kim3Department of Business Administration, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Republic of KoreaGraduate School of Logistics, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Republic of KoreaDepartment of Industrial and Management Systems Engineering, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do 17104, Republic of KoreaDepartment of Industrial Management and Engineering, Myongji University, 116 MyongJi-ro, Choein-gu, Yongin-si, Gyeonggi-do 17058, Republic of KoreaWe consider a single-machine scheduling problem with outsourcing options in an environment where the cost information of the downstream is available via some information sharing technologies. The due date is assigned to the position differently from the traditional due date. Each job can be processed in-house or outsourced. Note that, for cost saving, as many due dates as the number of outsourced jobs should be canceled. An in-house job incurs a stepwise penalty cost for tardiness, and an outsourced job incurs an outsourcing cost. Thus, the objective is to minimize the total penalty and outsourcing cost minus the total profit from cost savings. We show that the problem is weakly NP-hard and investigate some polynomially solvable cases. Due to the high complexity of the dynamic programming, we developed heuristics and verified their performance through numerical experiments.http://dx.doi.org/10.1155/2020/7069291 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Byung-Cheon Choi Yunhong Min Myoung-Ju Park Kyung Min Kim |
spellingShingle |
Byung-Cheon Choi Yunhong Min Myoung-Ju Park Kyung Min Kim Production Scheduling considering Outsourcing Options and Carrier Costs Journal of Advanced Transportation |
author_facet |
Byung-Cheon Choi Yunhong Min Myoung-Ju Park Kyung Min Kim |
author_sort |
Byung-Cheon Choi |
title |
Production Scheduling considering Outsourcing Options and Carrier Costs |
title_short |
Production Scheduling considering Outsourcing Options and Carrier Costs |
title_full |
Production Scheduling considering Outsourcing Options and Carrier Costs |
title_fullStr |
Production Scheduling considering Outsourcing Options and Carrier Costs |
title_full_unstemmed |
Production Scheduling considering Outsourcing Options and Carrier Costs |
title_sort |
production scheduling considering outsourcing options and carrier costs |
publisher |
Hindawi-Wiley |
series |
Journal of Advanced Transportation |
issn |
0197-6729 2042-3195 |
publishDate |
2020-01-01 |
description |
We consider a single-machine scheduling problem with outsourcing options in an environment where the cost information of the downstream is available via some information sharing technologies. The due date is assigned to the position differently from the traditional due date. Each job can be processed in-house or outsourced. Note that, for cost saving, as many due dates as the number of outsourced jobs should be canceled. An in-house job incurs a stepwise penalty cost for tardiness, and an outsourced job incurs an outsourcing cost. Thus, the objective is to minimize the total penalty and outsourcing cost minus the total profit from cost savings. We show that the problem is weakly NP-hard and investigate some polynomially solvable cases. Due to the high complexity of the dynamic programming, we developed heuristics and verified their performance through numerical experiments. |
url |
http://dx.doi.org/10.1155/2020/7069291 |
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