Analyzing the Performance Measures of Multi-Objective Water Cycle Algorithm for Multi-Objective Linear Fractional Programming Problem

This paper proposes a metaheuristic approach called as Multi Objective Water Cycle Algorithm (MOWCA) for Fuzzy Multi Objective Non-Linear Programming Problem (FMONLPP). The suggested approach initially defines a fuzzy goal for each objective function with hyperbolic membership function. Further, the...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	2018 Second International Conference on Intelligent Computing and Control Systems (ICICCS) s. 297 - 306
Hlavní autoři:	Veeramani, C., Sharanya, S.
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.06.2018
Témata:	Conferences Control systems Fractional Programming Problem Linear programming Multi-objective optimization Pareto optimization Programming Rivers Water cycle algorithm
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	This paper proposes a metaheuristic approach called as Multi Objective Water Cycle Algorithm (MOWCA) for Fuzzy Multi Objective Non-Linear Programming Problem (FMONLPP). The suggested approach initially defines a fuzzy goal for each objective function with hyperbolic membership function. Further, the converted Fuzzy Multi-Objective Linear Fractional Programming Problem (FMOLFPP) is changed into Fuzzy Multi Objective Non-Linear Programming Problem (MONLPP) and to find pareto solutions by the proposed metaheuristic approach. Generally, the efficiency of the metaheuristic algorithm is evaluated through various performance measures. In the present study, the following performance measures Generational Distance (GD), Reversed Generational Distance (RGD), Maximum spread (MS), Metric of spacing (S) and Delta Metric (\Delta) are used to show the efficiency of the proposed algorithm. Finally, the comparative study is carried out with other existing metaheuristic approaches.
DOI:	10.1109/ICCONS.2018.8662923