Multi-objective Windy Postman Problem in a Fuzzy Transportation Network

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 freq...

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Main Authors: Debosree PAL, Haresh Kumar SHARMA, Olegas PRENTKOVSKIS, Falguni CHAKRABORTY, Lijana MASKELIŪNAITĖ
Format: Article
Language:English
Published: University of Zagreb, Faculty of Transport and Traffic Sciences 2025-07-01
Series:Promet (Zagreb)
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Online Access:https://traffic2.fpz.hr/index.php/PROMTT/article/view/1134
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author Debosree PAL
Haresh Kumar SHARMA
Olegas PRENTKOVSKIS
Falguni CHAKRABORTY
Lijana MASKELIŪNAITĖ
author_facet Debosree PAL
Haresh Kumar SHARMA
Olegas PRENTKOVSKIS
Falguni CHAKRABORTY
Lijana MASKELIŪNAITĖ
author_sort Debosree PAL
collection DOAJ
description 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.
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spelling doaj-art-c975a3ac029842e0a690df5b13103dbc2025-08-20T03:25:26ZengUniversity of Zagreb, Faculty of Transport and Traffic SciencesPromet (Zagreb)0353-53201848-40692025-07-0137485387310.7307/ptt.v37i4.11341134Multi-objective Windy Postman Problem in a Fuzzy Transportation NetworkDebosree PAL0Haresh Kumar SHARMA1Olegas PRENTKOVSKIS2Falguni CHAKRABORTY3Lijana MASKELIŪNAITĖ4Boinchee Binapani Balika Vidyalaya, Pandua ; Department of Mathematics, Indian Institute of Technology Madras, ChennaiArea of Operations and Decision Sciences, Birla Institute of Management Technology, Greater NoidaDepartment of Mobile Machinery and Railway Transport, Vilnius Gediminas Technical University, VilniusDepartment of Masters of Computer Applications, Dr. B.C. Roy Engineering College, DurgapurDepartment of Mobile Machinery and Railway Transport, Vilnius Gediminas Technical University, VilniusResearchers 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.https://traffic2.fpz.hr/index.php/PROMTT/article/view/1134transportationwindy postman problemepsilon constraint methodmulti-objective genetic algorithmsperformance metrics
spellingShingle Debosree PAL
Haresh Kumar SHARMA
Olegas PRENTKOVSKIS
Falguni CHAKRABORTY
Lijana MASKELIŪNAITĖ
Multi-objective Windy Postman Problem in a Fuzzy Transportation Network
Promet (Zagreb)
transportation
windy postman problem
epsilon constraint method
multi-objective genetic algorithms
performance metrics
title Multi-objective Windy Postman Problem in a Fuzzy Transportation Network
title_full Multi-objective Windy Postman Problem in a Fuzzy Transportation Network
title_fullStr Multi-objective Windy Postman Problem in a Fuzzy Transportation Network
title_full_unstemmed Multi-objective Windy Postman Problem in a Fuzzy Transportation Network
title_short Multi-objective Windy Postman Problem in a Fuzzy Transportation Network
title_sort multi objective windy postman problem in a fuzzy transportation network
topic transportation
windy postman problem
epsilon constraint method
multi-objective genetic algorithms
performance metrics
url https://traffic2.fpz.hr/index.php/PROMTT/article/view/1134
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AT olegasprentkovskis multiobjectivewindypostmanprobleminafuzzytransportationnetwork
AT falgunichakraborty multiobjectivewindypostmanprobleminafuzzytransportationnetwork
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