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Promet - Traffic&Transportation, Vol. 37 No. 4, 2025.

Original scientific paper

https://doi.org/10.7307/ptt.v37i4.1134

Multi-objective Windy Postman Problem in a Fuzzy Transportation Network

Debosree PAL orcid id orcid.org/0009-0009-5948-8323 ; Boinchee Binapani Balika Vidyalaya, Pandua, India; Department of Mathematics, Indian Institute of Technology Madras, Chennai, India
Haresh Kumar SHARMA ; Area of Operations and Decision Sciences, Birla Institute of Management Technology, Greater Noida, India
Olegas PRENTKOVSKIS orcid id orcid.org/0000-0003-0910-591X ; Department of Mobile Machinery and Railway Transport, Vilnius Gediminas Technical University, Vilnius, Lithuania *
Falguni CHAKRABORTY ; Department of Masters of Computer Applications, Dr. B.C. Roy Engineering College, Durgapur, India
Lijana MASKELIŪNAITĖ ; Department of Mobile Machinery and Railway Transport, Vilnius Gediminas Technical University, Vilnius, Lithuania

* Corresponding author.

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Abstract

Researchers have become increasingly captivated by the windy postman problem (WPP), a major combinatorial optimisation problem with several practical applications. It is crucial to take the experts’ belief levels into account when modelling such a real-world application since these applications frequently involve uncertain aspects. A fuzzy set is one of the tools that might be regarded as appropriate for modelling such human perspectives. Applying fuzzy set theory to a multi-objective windy postman problem is the focus of this study. Maximising the overall profit and minimising the transportable time of the route visited by a postman are the objectives of the problem. In an effort to solve the fuzzy multi-objective windy postman problem (FMWPP), we have developed a chance-constrained programming model (CCPM). Subsequently, the epsilon-constraint method, a classical multi-objective solution methodology, is used to solve the deterministic transformation of the relevant CCPM. Moreover, the model is solved using two multi-objective genetic algorithms (MOGAs): fast Pareto genetic algorithm (FastPGA) and nondominated sorting genetic algorithm II (NSGAII). To demonstrate the proposed model, a numerical example is presented. We conclude by comparing the performance of the MOGAs on four randomly generated FMWPP instances.

Keywords

transportation; windy postman problem; epsilon constraint method; multi-objective genetic algorithms; performance metrics

Hrčak ID:

333684

URI

https://hrcak.srce.hr/333684

Publication date:

14.7.2025.

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