Temat: non-linear programming - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Application of fuzzy programming techniques to solve solid transportation problem with additional constraints
Autorzy:: Halder (Jana), Sharmistha
Jana, Biswapati
Powiązania:: https://bibliotekanauki.pl/articles/406403.pdf
Data publikacji:: 2020
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:: non-linear solid transportation problem
impurity constraints
fuzzy programming technique
Opis:: An innovative, real-life solid transportation problem is explained in a non-linear form. As in real life, the total transportation cost depends on the procurement process or type of the items and the distance of transportation. Besides, an impurity constraint is considered here. The proposed model is formed with fuzzy imprecise nature. Such an interesting model is optimised through two different fuzzy programming techniques and fractional programming methods, using LINGO-14.0 tools followed by the generalized gradient method. Finally, the model is discussed concerning these two different methods.
Źródło:: Operations Research and Decisions; 2020, 30, 1; 67-84
2081-8858
2391-6060
Pojawia się w:: Operations Research and Decisions
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: An adaptive method to solve multilevel multiobjective linear programming problems
Autorzy:: Kaci, Mustapha
Radjef, Sonia
Powiązania:: https://bibliotekanauki.pl/articles/27315332.pdf
Data publikacji:: 2023
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:: multilevel programming
multiobjective linear programming
adaptive method
sub-optimality estimate
nondominated solutions
non-dominated facets
Opis:: This paper is a follow-up to a previous work where we defined and generated the set of all possible compromises of multilevel multiobjective linear programming problems (ML-MOLPP). We introduce a new algorithm to solve ML-MOLPP in which the adaptive method of linear programming is nested. First, we start by generating the set of all possible compromises (set of all non-dominated solutions). After that, an algorithm based on the adaptive method of linear programming is developed to select the best compromise among all the possible settlements achieved. This method will allow us to transform the initial multilevel problem into an ML-MOLPP with bonded variables. Then, apply the adaptive method which is the most efficient to solve all the multiobjective linear programming problems involved in the resolution process instead of the simplex method. Finally, all the construction stages are carefully checked and illustrated with a numerical example.
Źródło:: Operations Research and Decisions; 2023, 33, 3; 29--44
2081-8858
2391-6060
Pojawia się w:: Operations Research and Decisions
Dostawca treści:: Biblioteka Nauki

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