Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights
This paper studies single-machine due-window assignment scheduling problems with truncated learning effect and resource allocation simultaneously. Linear and convex resource allocation functions under common due-window (CONW) assignment are considered. The goal is to find the optimal due-window star...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2020/9260479 |
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| _version_ | 1832550857710764032 |
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| author | Shan-Shan Lin |
| author_facet | Shan-Shan Lin |
| author_sort | Shan-Shan Lin |
| collection | DOAJ |
| description | This paper studies single-machine due-window assignment scheduling problems with truncated learning effect and resource allocation simultaneously. Linear and convex resource allocation functions under common due-window (CONW) assignment are considered. The goal is to find the optimal due-window starting (finishing) time, resource allocations and job sequence that minimize a weighted sum function of earliness and tardiness, due window starting time, due window size, and total resource consumption cost, where the weight is position-dependent weight. Optimality properties and polynomial time algorithms are proposed to solve these problems. |
| format | Article |
| id | doaj-art-b48eb33aedef4c088b6f52a03ecfa507 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-b48eb33aedef4c088b6f52a03ecfa5072025-02-03T06:05:39ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/92604799260479Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent WeightsShan-Shan Lin0School of Business and Management, Fujian Jiangxia University, Fuzhou 350108, ChinaThis paper studies single-machine due-window assignment scheduling problems with truncated learning effect and resource allocation simultaneously. Linear and convex resource allocation functions under common due-window (CONW) assignment are considered. The goal is to find the optimal due-window starting (finishing) time, resource allocations and job sequence that minimize a weighted sum function of earliness and tardiness, due window starting time, due window size, and total resource consumption cost, where the weight is position-dependent weight. Optimality properties and polynomial time algorithms are proposed to solve these problems.http://dx.doi.org/10.1155/2020/9260479 |
| spellingShingle | Shan-Shan Lin Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights Discrete Dynamics in Nature and Society |
| title | Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights |
| title_full | Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights |
| title_fullStr | Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights |
| title_full_unstemmed | Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights |
| title_short | Due-Window Assignment and Resource Allocation Scheduling with Truncated Learning Effect and Position-Dependent Weights |
| title_sort | due window assignment and resource allocation scheduling with truncated learning effect and position dependent weights |
| url | http://dx.doi.org/10.1155/2020/9260479 |
| work_keys_str_mv | AT shanshanlin duewindowassignmentandresourceallocationschedulingwithtruncatedlearningeffectandpositiondependentweights |