Simulated annealing for the multi-vehicle cyclic inventory routing problem
This paper studies the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) as the extension of the Single-Vehicle CIRP (SV-CIRP). The objective is to minimize both distribution and inventory costs at the customers and to maximize the collected rewards simultaneously. The problem is treated as a...
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| Main Authors: | , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2019
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/6021 https://ink.library.smu.edu.sg/context/sis_research/article/7024/viewcontent/Simulated_Annealing_for_the_Multi_Vehicle_Cyclic_Inventory_Routing_accepted.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | This paper studies the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) as the extension of the Single-Vehicle CIRP (SV-CIRP). The objective is to minimize both distribution and inventory costs at the customers and to maximize the collected rewards simultaneously. The problem is treated as a single objective optimization problem. A subset of customers is selected for each vehicle including the quantity to be delivered to each customer. For each vehicle, a cyclic distribution plan is developed. We construct a mathematical programming model and propose a simulated annealing (SA) metaheuristic for solving both SV-CIRP and MV-CIRP. For SV-CIRP, experimental results on benchmark instances show that SA is comparable to the state-of-the-art algorithms and it is able to improve 12 best known solutions. For the MV-CIRP, the results show that SA performs better than an Iterated Local Search algorithm. |
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