- Tytuł:
- Multi-objective geometric programming problem under uncertainty
- Autorzy:
-
Mandal, W. A.
Islam, S. - Powiązania:
- https://bibliotekanauki.pl/articles/406405.pdf
- Data publikacji:
- 2017
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
uncertainty theory
uncertain variable
linear
normal
zigzag
uncertainty distribution
multiobjective geometric programming - Opis:
- Multiobjective geometric programming (MOGP) is a powerful optimization technique widely used for solving a variety of nonlinear optimization problems and engineering problems. Generally, the parameters of a multiobjective geometric programming (MOGP) models are assumed to be deterministic and fixed. However, the values observed for the parameters in real-world MOGP problems are often imprecise and subject to fluctuations. Therefore, we use MOGP within an uncertainty based framework and propose a MOGP model whose coefficients are uncertain in nature. We assume the uncertain variables (UVs) to have linear, normal or zigzag uncertainty distributions and show that the corresponding uncertain chance-constrained multiobjective geometric programming (UCCMOGP) problems can be transformed into conventional MOGP problems to calculate the objective values. The paper develops a procedure to solve a UCCMOGP problem using an MOGP technique based on a weighted-sum method. The efficacy of this procedure is demonstrated by some numerical examples.
- Źródło:
-
Operations Research and Decisions; 2017, 27, 4; 85-109
2081-8858
2391-6060 - Pojawia się w:
- Operations Research and Decisions
- Dostawca treści:
- Biblioteka Nauki
Artykuł