An oracle penalty and modified augmented Lagrangian methods with firefly algorithm for constrained optimization problems

Umesh Balande () and Deepti Shrimankar ()
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Umesh Balande: VNIT
Deepti Shrimankar: VNIT

Operational Research, 2020, vol. 20, issue 2, No 21, 985-1010

Abstract: Abstract Almost all engineering optimization problems in the real world are constrained in nature. Swarm intelligence is a bio-inspired technique based on studying and observing fireflies, ants, birds and fish in nature. Firefly algorithm (FA) is the most prominent swarm based metaheuristic algorithm used for solving a global optimization problem. This paper presents two new constrained optimization algorithms: (1) firefly algorithm with extended oracle penalty method (FA-EOPM) and (2) modified augmented Lagrangian with firefly algorithm (MAL-FA). These proposed algorithms are applied for solving classic thirteen benchmark constraint problems as well as a few good engineering problem designs. The efficiency, effectiveness, and performance of MAL-FA and FA-EOPM algorithms are estimated on the basis of statistical analysis such as best optimal value, worst value, mean value, p value and standard deviation value against the existing methods. The experimental results show that the proposed MAL-FA algorithm offers better outcomes for most of the cases in terms of the number of function evaluations compared to various optimization algorithms.

Keywords: Constrained optimization; Oracle penalty method; Augmented Lagrangian method; Firefly algorithm (FA); Evolutionary algorithms (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s12351-017-0346-1

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