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Firefly Algorithm with Tabu Search to Solve the Vehicle Routing Problem with Minimized Fuel Emissions: Case Study of Canned Fruits Transport

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Foroozesh, N., Karimi, B. & Mousavi, S.M. (2022). Green-resilient supply chain network design for perishable products considering route risk and horizontal collaboration under robust interval-valued type-2 fuzzy uncertainty: A case study in food industry. Journal of Environmental Management 307, 114470. DOI: 10.1016/j.jenvman.2022.114470. Search in Google Scholar

Dantzig, G. & Ramser, J. (1959). The Truck Dispatching Problem. Management Science, 6, 80–91. DOI: 10.1287/mnsc.6.1.80. Search in Google Scholar

Li, D., Cao, Q., Zuo, M. & Xu, F. (2020). Optimization of green fresh food logistics with heterogeneous fleet vehicle route problem by improved genetic algorithm. Sustainability (Switzerland) 12(5). DOI: 10.3390/su12051946. Search in Google Scholar

Zulvia, F.E., Kuo, R.J. & Nugroho, D.Y. (2020). A many-objective gradient evolution algorithm for solving a green vehicle routing problem with time windows and time dependency for perishable products. Journal of Cleaner Production 242, 118428. DOI: 10.1016/j.jclepro.2019.118428. Search in Google Scholar

Asgharizadeh, E., Jooybar, S., Mahdiraji, H.A. & Garza-Reyes, J.A. (2022). A Novel Travel Time Estimation Model for Modeling a Green Time-Dependent Vehicle Routing Problem in Food Supply Chain. Sustainability (Switzerland) 14(14). DOI: 10.3390/su14148633. Search in Google Scholar

Pratap, S., Jauhar, S.K., Paul, S.K. & Zhou, F. (2022). Stochastic optimization approach for green routing and planning in perishable food production. Journal of Cleaner Production 333, 130063. DOI: 10.1016/j.jclepro.2021.130063. Search in Google Scholar

Yang, X.-S. (2008). Natural-Inspired Metaheuristics Algorithms. Luniver Press. Search in Google Scholar

Li, J., Wei, X., Li, B. & Zeng, Z. (2022). A survey on firefly algorithms. Neurocomputing 500, 662–678. DOI: 10.1016/j.neucom.2022.05.100. Search in Google Scholar

Rahman, M.A., Sokkalingam, R., Othman, M., Biswas, K., Abdullah, L. & Kadir, E.A. (2021). Nature-inspired metaheuristic techniques for combinatorial optimization problems: Overview and recent advances. Mathematics 9(20), 1–32. DOI: 10.3390/math9202633. Search in Google Scholar

Goel, R. & Maini, R. (2018). A hybrid of ant colony and firefly algorithms (HAFA) for solving vehicle routing problems. Journal of Computational Science 25, 28–37. DOI: 10.1016/j.jocs.2017.12.012. Search in Google Scholar

Goel, R. & Maini, R. (2019). Evolutionary ant colony algorithm using firefly based transition for solving vehicle routing problems: EAFA for VRPs. International Journal of Swarm Intelligence Research 10(3), 46–60. DOI: 10.4018/IJSIR.2019070103. Search in Google Scholar

Saraei, M. & Ghaheri, A. (2017). An Effective Hybrid Algorithm for Vehicle Routing Problem by Indicating Capacity using Genetic and Firefly Algorithms. International Journal of Engineering Education, 9(2). Search in Google Scholar

Aydilek, İ.B. (2018). A hybrid firefly and particle swarm optimization algorithm for computationally expensive numerical problems. Applied Soft Computing Journal 66, 232–249. DOI: 10.1016/j.asoc.2018.02.025. Search in Google Scholar

Xia, X., Gui, L., He, G., Xie, C., Wei, B., Xing, Y., Wu, R. & Tang, Y. (2018). A hybrid optimizer based on firefly algorithm and particle swarm optimization algorithm. Journal of Computational Science 26, 488–500. DOI: 10.1016/j.jocs.2017.07.009. Search in Google Scholar

Rohaninejad, M., Kheirkhah, A.S., Nouri, B.V. & Fattahi, P. (2015). Two hybrid tabu search– firefly algorithms for the capacitated job shop scheduling problem with sequence-dependent setup cost. International Journal of Computer Integrated Manufacturing 28(5), 470–487. DOI: 10.1080/0951192X.2014.880808. Search in Google Scholar

Ghasemi, M., Mohammadi, S. kadkhoda, Zare, M., Mirjalili, S., Gil, M. & Hemmati, R. (2022). A new firefly algorithm with improved global exploration and convergence with application to engineering optimization. Decision Analytics Journal 5(August), 100125. DOI: 10.1016/j.dajour.2022.100125. Search in Google Scholar

Peng, H., Xiao, W., Han, Y., Jiang, A., Xu, Z., Li, M. & Wu, Z. (2022). Multi-strategy firefly algorithm with selective ensemble for complex engineering optimization problems. Applied Soft Computing 120, 108634. DOI: 10.1016/j.asoc.2022.108634. Search in Google Scholar

Wang, Z., Shen, L., Li, X. & Gao, L. (2023). An improved multi-objective firefly algorithm for energy-efficient hybrid flowshop rescheduling problem. Journal of Cleaner Production 385, 135738. DOI: 10.1016/j.jclepro.2022.135738. Search in Google Scholar

Thang, T.B. & Binh, H.T.T. (2022). A hybrid multifactorial evolutionary algorithm and firefly algorithm for the clustered minimum routing cost tree problem. Knowledge-Based Systems 241, 108225. DOI: 10.1016/j.knosys.2022.108225. Search in Google Scholar

Altabeeb, A.M., Mohsen, A.M., Abualigah, L. & Ghallab, A. (2021). Solving capacitated vehicle routing problem using cooperative firefly algorithm. Applied Soft Computing 108, 107403. DOI: 10.1016/j.asoc.2021.107403. Search in Google Scholar

Ewees, A.A., Al-qaness, M.A.A. & Abd Elaziz, M. (2021). Enhanced salp swarm algorithm based on firefly algorithm for unrelated parallel machine scheduling with setup times. Applied Mathematical Modelling 94, 285–305. DOI: 10.1016/j.apm.2021.01.017. Search in Google Scholar

Zhang, H., Zhang, K., Chen, Y. & Ma, L. (2022). Multi-objective two-level medical facility location problem and tabu search algorithm. Information Sciences 608, 734–756. DOI: 10.1016/j.ins.2022.06.083. Search in Google Scholar

An, Y., Zhao, Z., Chen, X., Li, Y. & Gao, K. (2022). A Property-Based Hybrid Genetic Algorithm and Tabu Search for Solving Order Acceptance and Scheduling Problem with Trapezoidal Penalty Membership Function. SSRN Electronic Journal 218. DOI: 10.2139/ssrn.4215297. Search in Google Scholar

Liu, X., Chen, J., Wang, M., Wang, Y., Su, Z. & Lü, Z. (2022). A two-phase tabu search based evolutionary algorithm for the maximum diversity problem. Discrete Optimization 44, 100613. DOI: 10.1016/j.disopt.2020.100613. Search in Google Scholar

Hussain Ahmed, Z. & Yousefikhoshbakht, M. (2023). An improved tabu search algorithm for solving heterogeneous fixed fleet open vehicle routing problem with time windows. Alexandria Engineering Journal 64, 349–363. DOI: 10.1016/j.aej.2022.09.008. Search in Google Scholar

Kyriakakis, N.A., Sevastopoulos, I., Marinaki, M. & Marinakis, Y. (2022). A hybrid Tabu search – Variable neighborhood descent algorithm for the cumulative capacitated vehicle routing problem with time windows in humanitarian applications. Computers and Industrial Engineering 164(October 2021), 107868. DOI: 10.1016/j.cie.2021.107868. Search in Google Scholar

Xu, W., Hu, Y., Luo, W., Wang, L. & Wu, R. (2021). A multi-objective scheduling method for distributed and flexible job shop based on hybrid genetic algorithm and tabu search considering operation outsourcing and carbon emission. Computers and Industrial Engineering 157(September 2020), 107318. DOI: 10.1016/j.cie.2021.107318. Search in Google Scholar

Çiftçi, M.E. & Özkır, V. (2020). Optimising flight connection times in airline bank structure through Simulated Annealing and Tabu Search algorithms. Journal of Air Transport Management 87. DOI: 10.1016/j.jairtraman.2020.101858. Search in Google Scholar

Chaieb, M. & Ben Sassi, D. (2021). Measuring and evaluating the Home Health Care Scheduling Problem with Simultaneous Pick-up and Delivery with Time Window using a Tabu Search metaheuristic solution. Applied Soft Computing 113, 107957. DOI: 10.1016/j.asoc.2021.107957. Search in Google Scholar

Department of Land Transport. (1979). Road Traffic Act. Search in Google Scholar

Baños, R., Ortega, J., Gil, C., Fernández, A., & De Toro, F. (2013). A Simulated Annealing-based parallel multi-objective approach to vehicle routing problems with time windows. Expert Systems with Applications 40(5), 1696–1707. DOI: 10.1016/j.eswa.2012.09.012. Search in Google Scholar

IPCC. (2006). IPCC Guidelines for National Greenhouse Gas Inventories. Search in Google Scholar

Konečný, V. & Petro, F. (2017). Calculation of selected emissions from transport services in road public transport. MATEC Web of Conferences 134, 1–8. DOI: 10.1051/matecconf/201713400026. Search in Google Scholar

eISSN:
2336-3037
Lingua:
Inglese
Frequenza di pubblicazione:
Volume Open
Argomenti della rivista:
Business and Economics, Business Management, Industries, Transportation, Logistics, Air Traffic, Shipping