Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms
The problem we consider in this study is Time Dependent Vehicle Routing Problem (TDVRP) which has been categorized as non-classical VRP. It is motivated by the fact that multinational companies are currently not only manufacturing the demanded products but also distributing them to the customer loca...
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| Format: | Conference or Workshop Item |
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2015
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| _version_ | 1796860719276228608 |
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| author | Johar, Farhana Potts, Chris Bennell, Julia |
| author_facet | Johar, Farhana Potts, Chris Bennell, Julia |
| author_sort | Johar, Farhana |
| collection | ePrints |
| description | The problem we consider in this study is Time Dependent Vehicle Routing Problem (TDVRP) which has been categorized as non-classical VRP. It is motivated by the fact that multinational companies are currently not only manufacturing the demanded products but also distributing them to the customer location. This implies an efficient synchronization of production and distribution activities. Hence, this study will look into the routing of vehicles which departs from the depot at varies time due to the variation in manufacturing process. We consider a single production line where demanded products are being process one at a time once orders have been received from the customers. It is assumed that order released from the production line will be loaded into scheduled vehicle which ready to be delivered. However, the delivery could only be done once all orders scheduled in the vehicle have been released from the production line. Therefore, there could be lateness on the delivery process from awaiting all customers’ order of the route to be released. Our objective is to determine a schedule for vehicle routing that minimizes the solution cost including the travelling and tardiness cost. A mathematical formulation is developed to represent the problem and will be solved by two metaheuristics; Variable Neighborhood Search (VNS) and Tabu Search (TS). These algorithms will be coded in C++ programming and run using 56’s Solomon instances with some modification. The outcome of this experiment can be interpreted as the quality criteria of the different approximation methods. The comparison done shown that VNS gave the better results while consuming reasonable computational efforts. |
| first_indexed | 2024-03-05T19:45:30Z |
| format | Conference or Workshop Item |
| id | utm.eprints-59480 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:45:30Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | utm.eprints-594802021-08-04T06:37:26Z http://eprints.utm.my/59480/ Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms Johar, Farhana Potts, Chris Bennell, Julia QA Mathematics The problem we consider in this study is Time Dependent Vehicle Routing Problem (TDVRP) which has been categorized as non-classical VRP. It is motivated by the fact that multinational companies are currently not only manufacturing the demanded products but also distributing them to the customer location. This implies an efficient synchronization of production and distribution activities. Hence, this study will look into the routing of vehicles which departs from the depot at varies time due to the variation in manufacturing process. We consider a single production line where demanded products are being process one at a time once orders have been received from the customers. It is assumed that order released from the production line will be loaded into scheduled vehicle which ready to be delivered. However, the delivery could only be done once all orders scheduled in the vehicle have been released from the production line. Therefore, there could be lateness on the delivery process from awaiting all customers’ order of the route to be released. Our objective is to determine a schedule for vehicle routing that minimizes the solution cost including the travelling and tardiness cost. A mathematical formulation is developed to represent the problem and will be solved by two metaheuristics; Variable Neighborhood Search (VNS) and Tabu Search (TS). These algorithms will be coded in C++ programming and run using 56’s Solomon instances with some modification. The outcome of this experiment can be interpreted as the quality criteria of the different approximation methods. The comparison done shown that VNS gave the better results while consuming reasonable computational efforts. 2015 Conference or Workshop Item PeerReviewed Johar, Farhana and Potts, Chris and Bennell, Julia (2015) Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms. In: 2nd ISM International Statistical Conference 2014: Empowering the Applications of Statistical and Mathematical Sciences, ISM 2014, 12-14 Aug 2014, Kuantan, Pahang. http://dx.doi.org/10.1063/1.4907523 |
| spellingShingle | QA Mathematics Johar, Farhana Potts, Chris Bennell, Julia Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms |
| title | Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms |
| title_full | Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms |
| title_fullStr | Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms |
| title_full_unstemmed | Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms |
| title_short | Solving the Time Dependent Vehicle Routing Problem by Metaheuristic Algorithms |
| title_sort | solving the time dependent vehicle routing problem by metaheuristic algorithms |
| topic | QA Mathematics |
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