Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores
Utilizing local brick-and-mortar stores for same-day order fulfillment is becoming prominent in omni-channel retailing. Efficient in-store order picking is critical to providing timely value-added omni-channel delivery services. Despite numerous studies on order picking in traditional logistics ware...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-04-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/10/9/1484 |
| _version_ | 1797503904421773312 |
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| author | Shandong Mou |
| author_facet | Shandong Mou |
| author_sort | Shandong Mou |
| collection | DOAJ |
| description | Utilizing local brick-and-mortar stores for same-day order fulfillment is becoming prominent in omni-channel retailing. Efficient in-store order picking is critical to providing timely value-added omni-channel delivery services. Despite numerous studies on order picking in traditional logistics warehouses and distribution centers, there is scant research focusing on in-store order fulfillment with the multi-skilled workforce in omni-channel retail stores. We studied the integrated Order Picking and Heterogeneous Picker Scheduling Problem (OPPSP-Het) in omni-channel retail stores. We characterized the OPPSP-Het in a mixed-integer linear optimization model with the objective of the minimization of total tardiness of all customer orders. A hybrid heuristic combining the genetic algorithm and variable neighborhood descent was designed to obtain effective solutions. Extensive experiments were conducted to validate the performance of the proposed approach relative to existing algorithms in recent literature. We further numerically showed the effects of order size and heterogeneous workforce on order fulfillment performance. We lastly emphasized the importance of workforce flexibility as a cost-effective approach to improving in-store order fulfillment performance. |
| first_indexed | 2024-03-10T03:57:02Z |
| format | Article |
| id | doaj.art-e46f79c1dbfe4855a5a9de2097e199f7 |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T03:57:02Z |
| publishDate | 2022-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-e46f79c1dbfe4855a5a9de2097e199f72023-11-23T08:45:03ZengMDPI AGMathematics2227-73902022-04-01109148410.3390/math10091484Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail StoresShandong Mou0Department of Supply Chain and Operations Management, Business School, Central University of Finance and Economics, Beijing 100081, ChinaUtilizing local brick-and-mortar stores for same-day order fulfillment is becoming prominent in omni-channel retailing. Efficient in-store order picking is critical to providing timely value-added omni-channel delivery services. Despite numerous studies on order picking in traditional logistics warehouses and distribution centers, there is scant research focusing on in-store order fulfillment with the multi-skilled workforce in omni-channel retail stores. We studied the integrated Order Picking and Heterogeneous Picker Scheduling Problem (OPPSP-Het) in omni-channel retail stores. We characterized the OPPSP-Het in a mixed-integer linear optimization model with the objective of the minimization of total tardiness of all customer orders. A hybrid heuristic combining the genetic algorithm and variable neighborhood descent was designed to obtain effective solutions. Extensive experiments were conducted to validate the performance of the proposed approach relative to existing algorithms in recent literature. We further numerically showed the effects of order size and heterogeneous workforce on order fulfillment performance. We lastly emphasized the importance of workforce flexibility as a cost-effective approach to improving in-store order fulfillment performance.https://www.mdpi.com/2227-7390/10/9/1484multi-skilled workforceorder pickingomni-channel retail storesworkforce flexibilityheuristic algorithm |
| spellingShingle | Shandong Mou Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores Mathematics multi-skilled workforce order picking omni-channel retail stores workforce flexibility heuristic algorithm |
| title | Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores |
| title_full | Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores |
| title_fullStr | Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores |
| title_full_unstemmed | Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores |
| title_short | Integrated Order Picking and Multi-Skilled Picker Scheduling in Omni-Channel Retail Stores |
| title_sort | integrated order picking and multi skilled picker scheduling in omni channel retail stores |
| topic | multi-skilled workforce order picking omni-channel retail stores workforce flexibility heuristic algorithm |
| url | https://www.mdpi.com/2227-7390/10/9/1484 |
| work_keys_str_mv | AT shandongmou integratedorderpickingandmultiskilledpickerschedulinginomnichannelretailstores |