Himma Firdaus
ABSTRACT
Smart logistics is a crucial aspect of constructing smart cities, which entails efficiently finding a solution to a problem using a fleet of vehicles to serve geographically dispersed clients. It comprises the capacitated vehicle routing problem (CVRP), a well-known NP-hard complex optimization problem that a genetic algorithm (GA) can solve even with some weaknesses. The weaknesses include time-consuming, difficult-to-achieve convergence, and easy-to-get premature convergence, resulting in infeasible and low-quality solutions in a limited population. Based on these weaknesses, the authors propose three improvements to GA to optimize the solution. The improvement strategies are enhancing the initial population with the nearest neighbor algorithm, improving the new mutated offspring with a 2-opt heuristic, and optimizing the route with a give-and-exchange operator. The test is undergone on 53 CVRP problem sets to evaluate the performance of our proposed algorithm. The result shows that the proposed algorithm successfully improves GA performance quality, reduces the execution time, reaches some optimum values, and obtains a better solution than the best-known value.
- Jerzy Korczak and Kinga Kijewska, 2019. Smart Logistics in the development of Smart Cities. Transportation Research Procedia 39, 201–211. DOI: 10.1016/j.trpro.2019.06.022.Google Scholar
Cross Ref
- Ji Zhu, 2022. Solving Capacitated Vehicle Routing Problem by an Improved Genetic Algorithm with Fuzzy C-Means Clustering. Scientific Programming, 2, 1-8. DOI: 10.1155/2022/8514660.Google Scholar
- Nikolaos A.Kyriakakis Ioannis Sevastopoulos, Magdalene Marinaki, and Yannis Marinakis, 2021. A hybrid Tabu search – Variable neighborhood descent algorithm for the cumulative capacitated vehicle routing problem with time windows in humanitarian applications. Computer and Industrial Engineering 164, (February, 2021). DOI: 10.1016/j.cie.2021.107868.Google ScholarDigital Library
- İlhan İLHAN, 2021. An improved simulated annealing algorithm with crossover operator for capacitated vehicle routing problem. Swarm Evolutionary Computation 64, (July, 2021). DOI: 10.1016/j.swevo.2021.100911.Google ScholarCross Ref
- Md. Anisul Islam, Yuvraj Gajpal, and Tarek Y. ElMekkawy, 2021. Hybrid particle swarm optimization algorithm for solving the clustered vehicle routing problem. Applied Soft Computing 110, (October, 2021), DOI:10.1016/j.asoc.2021.107655.Google ScholarDigital Library
- Yi Zhou, Weidong Li, Xiaomao Wang, Yimin Qiu, and Weiming Shen, 2022. Adaptive gradient descent enabled ant colony optimization for routing problems. Swarm Evolutionary Computation 70, (April 2022). DOI: 10.1016/j.swevo.2022.101046.Google ScholarCross Ref
- Tarek El-mihoub, Adrian Alan Hopgood, and Lars Nolle, 2006. Hybrid Genetic Algorithms: A Review. Engineering Letters 13, 11 (August, 2006), 124-137.Google Scholar
- Pradnya A. Vikhar, 2017. Evolutionary algorithms: A critical review and its future prospects. In Proceeding of 2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), IEEE, Jalgaon, India, 261- 265, DOI: 10.1109/ICGTSPICC.2016.7955308.Google Scholar
- John H. Holland, 1992. Complex Adaptive Systems. Deadalus 121, 1, 17-30.Google Scholar
- Yong Deng, Yang Liu, and Deyun Zhou, 2015. An Improved Genetic Algorithm with Initial Population Strategy for Symmetric TSP. Mathematical Problems in Engineering, 1-6. DOI: 10.1155/2015/212794.Google Scholar
- Ph. Preux and E.-G. Talbi, 1999. Towards hybrid evolutionary algorithms. International Transactions in Operational Research 6, 6 (November, 1999), 557–570. DOI: 10.1111/j.1475-3995.1999.tb00173.x.Google ScholarCross Ref
- Stephanie Forrest, and Melanie Mitchell, 1993. What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation. Machine Learning 13, 2 (November, 1993), 285–319. DOI:10.1023/A:1022626114466.Google ScholarCross Ref
- Zbigniew Michalewicz, 1997. Genetic algorithms + Data Structures = Evolution Programs (3rd ed.). Springer-Verlag Berlin Heidelberg, Berlin.Google ScholarDigital Library
- Haifeng Du, Jiarui Fan, Xiaochen He, and Marcus W. Feldman, 2018. A Genetic Simulated Annealing Algorithm to Optimize the Small-World Network Generating Process. Complexity, 1-12. DOI: 10.1155/2018/1453898.Google Scholar
- Coşkun Hamzaçebi, 2008. Improving genetic algorithms' performance by local search for continuous function optimization. Applied Mathematics and Computation 196, 1 (February, 2008), 309–317. DOI: 10.1016/j.amc.2007.05.068.Google ScholarCross Ref
- Wen Wan, and Jeffrey B. Birch, 2013. An improved hybrid genetic algorithm with a new local search procedure. Journal of Applied Mathematics, 14–19. DOI: 10.1155/2013/103591.Google Scholar
- G. B. Dantzig, and J. H. Ramser, 1959. The Truck Dispatching Problem. Management Science 6, 1 (October, 1959), 80–91. DOI: 10.1287/mnsc.6.1.80.Google ScholarDigital Library
- J. F. Cordeau, M. Gendreau, G. Laporte, J. Y. Potvin, and F. Semet, 2002. A guide to vehicle routing heuristics. Journal of the Operational Research 53, 5 (December, 2017), 512–522. DOI: 10.1057/palgrave.jors.2601319.Google Scholar
- Jens Lysgaard, Adam N. Letchford, and Richard W. Eglese, 2004. A new branch-and-cut algorithm for the capacitated vehicle routing problem. Mathematical Programming 100, 423 – 445. DOI:10.1007/s10107-003-0481-8.Google ScholarCross Ref
- Hadeer Awad, Raafat Elshaera, Adel AbdElmo'ez, and Gamal Nawara, 2018. An effective genetic algorithm for capacitated vehicle routing problem. In Proceedings of the International Conference on Industrial Engineering and Operations Management. IEOM Society International, Bandung, Indonesia, 374-384.Google Scholar
- Nitin Bhatia, and Vandana, 2010. Survey of Nearest Neighbor Techniques. International Journal of Computer Science and Information Security 8, 2, 302 - 305. DOI: https://doi.org/10.48550/arXiv.1007.0085.Google Scholar
- Kenan Karagül, Erdal Aydemir, and Sezai Tokat, 2016. Using 2-Opt based evolution strategy for travelling salesman problem. An International Journal of Optimization and Control Theories & Applications 6, 2 (July, 2006), 103–113. DOI:10.11121/ijocta.01.2016.00268.Google Scholar
- Stefan Hougardy, Fabian Zaiser, and Xianghui Zhong, 2020. The approximation ratio of the 2-Opt Heuristic for the metric Traveling Salesman Problem. Operations Research Letters 48, 4 (July, 2020), 401–404. DOI:10.1016/j.orl.2020.05.007.Google ScholarCross Ref
- Stanley Jefferson de Araujo Lima, Sidnei Alves de Araújo, and Pedro Schimit, 2018. A hybrid approach based on genetic algorithm and nearest neighbor heuristic for solving the capacitated vehicle routing problem. Acta Scientiarum Technology 40, (April 2018), 1-14. DOI:10.4025/actascitechnol.v40i1.36708.Google Scholar
- Mohammad Sajid, Jagendra Singh, Raza Abbas Haidri,Mukesh Prasad, Vijayakumar Varadarajan, Ketan Kotecha, and Deepak Garg, 2021. A Novel Algorithm for Capacitated Vehicle Routing Problem for Smart Cities. Symmetry 13, 10 (October, 2021), 1-23. DOI:10.3390/sym13101923.Google ScholarCross Ref
Recommendations
An effective genetic algorithm for solving the capacitated vehicle routing problem with two-dimensional loading constraint
In this article, we focus on the symmetric capacitated vehicle routing problem where customer demand is composed of two-dimensional weighted items. The objective consists in designing a set of trips, starting and terminating at a central depot, that ...
Improvement of Genetic Algorithm for Vehicle Routing Problems with Time Windows
ISDEA '13: Proceedings of the 2013 Third International Conference on Intelligent System Design and Engineering ApplicationsVehicle routing problem with time windows (VRPTW) is of crucial importance in today's industries, especially in logistics distribution. Improvement of genetic algorithm (GA) using an optimized crossover operator is proposed by a complete undirected ...
A hybrid genetic algorithm that optimizes capacitated vehicle routing problems
This study primarily focuses on solving a capacitated vehicle routing problem (CVRP) by applying a novel hybrid genetic algorithm (HGA) capable of practical use for manufacturers. The proposed HGA has three stages. First, the nearest addition method (...
Comments