Innovative hybrid algorithm for efficient routing of limited capacity vehicles
This study addresses the critical challenges posed by the capacitated vehicle routing problem (CVRP), particularly in the logistics of cement transportation under capacity constraints. Existing algorithms, including grey wolf optimizer (GWO) and whale optimization algorithm (WOA), exhibit significan...
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| Language: | English |
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Elsevier
2025-03-01
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| Series: | Intelligent Systems with Applications |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2667305325000171 |
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| author | Vu Hong Son Pham Van Nam Nguyen Nghiep Trinh Nguyen Dang |
| author_facet | Vu Hong Son Pham Van Nam Nguyen Nghiep Trinh Nguyen Dang |
| author_sort | Vu Hong Son Pham |
| collection | DOAJ |
| description | This study addresses the critical challenges posed by the capacitated vehicle routing problem (CVRP), particularly in the logistics of cement transportation under capacity constraints. Existing algorithms, including grey wolf optimizer (GWO) and whale optimization algorithm (WOA), exhibit significant limitations such as imbalanced exploration and exploitation, inefficiency in refining solutions, and inadequate adaptability to dynamic routing conditions. These limitations hinder their ability to provide comprehensive solutions that optimize time, cost, and environmental sustainability. To address these critical challenges, this research proposes an enhanced hybrid metaheuristic algorithm, mGWOA, designed to overcome the limitations of existing approaches by combining the GWO's strong exploitation capabilities and the WOA's exploratory strengths. By integrating opposition-based learning (OBL) to expand the search space and mutation techniques to escape local optima, the mGWOA is tailored to provide more flexible, adaptive, and efficient solutions for the complex and dynamic requirements of the CVRP. The mGWOA framework leverages the exploratory advantages of WOA, the exploitative strengths of GWO, and the diversity-promoting features of OBL and mutation to address the complexities of CVRP. Through computational evaluations in various scenarios, including five case studies ranging from small to large, the algorithm demonstrates its superior ability to generate high-quality solutions, especially as the customer base expands. The results underscore the potential of mGWOA as a robust and adaptive approach to solving CVRP, minimizing time and cost, and contributing to sustainable logistics operations. By bridging existing knowledge gaps, this research provides an innovative global optimization framework, offering practical applications for CVRP and other engineering challenges. |
| format | Article |
| id | doaj-art-45d283caa7d24d71bff2b2a25bab8d5b |
| institution | DOAJ |
| issn | 2667-3053 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Intelligent Systems with Applications |
| spelling | doaj-art-45d283caa7d24d71bff2b2a25bab8d5b2025-08-20T02:45:27ZengElsevierIntelligent Systems with Applications2667-30532025-03-012520049110.1016/j.iswa.2025.200491Innovative hybrid algorithm for efficient routing of limited capacity vehiclesVu Hong Son Pham0Van Nam Nguyen1Nghiep Trinh Nguyen Dang2Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, VietnamFaculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam; Corresponding author at: Department of Construction Engineering and Management, Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM), Ho Chi Minh City, Vietnam.Faculty of Civil Engineering, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City (VNU-HCM), Linh Trung Ward, Thu Duc District, Ho Chi Minh City, VietnamThis study addresses the critical challenges posed by the capacitated vehicle routing problem (CVRP), particularly in the logistics of cement transportation under capacity constraints. Existing algorithms, including grey wolf optimizer (GWO) and whale optimization algorithm (WOA), exhibit significant limitations such as imbalanced exploration and exploitation, inefficiency in refining solutions, and inadequate adaptability to dynamic routing conditions. These limitations hinder their ability to provide comprehensive solutions that optimize time, cost, and environmental sustainability. To address these critical challenges, this research proposes an enhanced hybrid metaheuristic algorithm, mGWOA, designed to overcome the limitations of existing approaches by combining the GWO's strong exploitation capabilities and the WOA's exploratory strengths. By integrating opposition-based learning (OBL) to expand the search space and mutation techniques to escape local optima, the mGWOA is tailored to provide more flexible, adaptive, and efficient solutions for the complex and dynamic requirements of the CVRP. The mGWOA framework leverages the exploratory advantages of WOA, the exploitative strengths of GWO, and the diversity-promoting features of OBL and mutation to address the complexities of CVRP. Through computational evaluations in various scenarios, including five case studies ranging from small to large, the algorithm demonstrates its superior ability to generate high-quality solutions, especially as the customer base expands. The results underscore the potential of mGWOA as a robust and adaptive approach to solving CVRP, minimizing time and cost, and contributing to sustainable logistics operations. By bridging existing knowledge gaps, this research provides an innovative global optimization framework, offering practical applications for CVRP and other engineering challenges.http://www.sciencedirect.com/science/article/pii/S2667305325000171Capacitated vehicle routing problem (CVRP)Modified whale optimization algorithm (mGWOA)Optimizing transportation |
| spellingShingle | Vu Hong Son Pham Van Nam Nguyen Nghiep Trinh Nguyen Dang Innovative hybrid algorithm for efficient routing of limited capacity vehicles Intelligent Systems with Applications Capacitated vehicle routing problem (CVRP) Modified whale optimization algorithm (mGWOA) Optimizing transportation |
| title | Innovative hybrid algorithm for efficient routing of limited capacity vehicles |
| title_full | Innovative hybrid algorithm for efficient routing of limited capacity vehicles |
| title_fullStr | Innovative hybrid algorithm for efficient routing of limited capacity vehicles |
| title_full_unstemmed | Innovative hybrid algorithm for efficient routing of limited capacity vehicles |
| title_short | Innovative hybrid algorithm for efficient routing of limited capacity vehicles |
| title_sort | innovative hybrid algorithm for efficient routing of limited capacity vehicles |
| topic | Capacitated vehicle routing problem (CVRP) Modified whale optimization algorithm (mGWOA) Optimizing transportation |
| url | http://www.sciencedirect.com/science/article/pii/S2667305325000171 |
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