Path: Top -> Journal -> Jurnal Internasional -> Fuzzy Information and Engineering -> 2021 -> Volume 13, Issue 1

A Profit Maximisation Solid Transportation Problem Using Genetic Algorithm in Fuzzy Environment

Journal from gdlhub / 2021-09-02 19:58:43
Oleh : S. Samanta, A. Ojha, B. Das & S. K. Mondal, Fuzzy Information and Engineering
Dibuat : 2021-09-02, dengan 0 file

Keyword : All unit discount, genetic algorithm, profit maximisation solid transportation problem, fuzzy resource and demand
Url : http://www.tandfonline.com/doi/full/10.1080/16168658.2021.1915454
Sumber pengambilan dokumen : Web

In this paper, a solid transportation problem has been considered in which the transportation is accomplished in two stages – firstly, from the origin(s) to the near by station(s) of the destination(s) and secondly, from the near by station(s) to the exact destination(s). Here, a fuzzy AUD (all unit discount) policy has been introduced based upon the amount of transportation along with a fuzzy fixed charge. In addition, a budget constraint has been incorporated taking fuzzy unit transportation cost. Then the proposed model has been converted into a single objective optimisation problem using interval arithmetic method. To solve the model, Genetic Algorithm (GA) has been used depending on roulette wheel selection, crossover and mutation. Finally, a numerical example has been illustrated to study the feasibility of the model.

Deskripsi Alternatif :

In this paper, a solid transportation problem has been considered in which the transportation is accomplished in two stages – firstly, from the origin(s) to the near by station(s) of the destination(s) and secondly, from the near by station(s) to the exact destination(s). Here, a fuzzy AUD (all unit discount) policy has been introduced based upon the amount of transportation along with a fuzzy fixed charge. In addition, a budget constraint has been incorporated taking fuzzy unit transportation cost. Then the proposed model has been converted into a single objective optimisation problem using interval arithmetic method. To solve the model, Genetic Algorithm (GA) has been used depending on roulette wheel selection, crossover and mutation. Finally, a numerical example has been illustrated to study the feasibility of the model.

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