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Author: search.filters.author.Vasant, PandianSubject: search.filters.subject.Optimization

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    Review on recent implementations of multiobjective and multilevel optimization in sustainable energy economics
    (2022)
    Ganesan, Timothy
    ;
    Litvinchev, Igor
    ;
    Marmolejo Saucedo, José Antonio
    ;
    Thomas, J. Joshua
    ;
    Vasant, Pandian
    Rapid progress is currently being made globally in the sustainable energy industry. This trend has been seen to concentrate on specific focus areas in the global energy ecosystem. The integration of sustainability ideas into the existing energy ecosystem has given rise to various complexities, e.g., multilevel and multiobjective (MO) scenarios. This in return has generated various avenues for the implementation of mathematical optimization as well as state-of-the-art operations research methodologies on such real-world systems. This chapter aims to provide a concise review on recent implementations of MO and multilevel optimization on sustainable energy economic systems. Three key industrial areas are given emphasis—economic load/emission dispatch, bioenergy supply chains, and sustainable capacity planning. © 2022 Elsevier Inc. All rights reserved.
    Scopus© Citations 1  18  1
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    Quantum-behaved bat algorithm for solving the economic load dispatch problem considering a valve-point effect
    (2020)
    Vasant, Pandian
    ;
    Parvez Mahdi, Fahad
    ;
    Marmolejo Saucedo, José Antonio
    ;
    Litvinchev, Igor
    ;
    Rodríguez Aguilar, Román  
    Quantum computing-inspired metaheuristic algorithms have emerged as a powerful computational tool to solve nonlinear optimization problems. In this paper, a quantum-behaved bat algorithm (QBA) is implemented to solve a nonlinear economic load dispatch (ELD) problem. The objective of ELD is to find an optimal combination of power generating units in order to minimize total fuel cost of the system, while satisfying all other constraints. To make the system more applicable to the real-world problem, a valve-point effect is considered here with the ELD problem. QBA is applied in 3-unit, 10-unit, and 40-unit power generation systems for different load demands. The obtained result is then presented and compared with some well-known methods from the literature such as different versions of evolutionary programming (EP) and particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE), simulated annealing (SA) and hybrid ABC_PSO. The comparison of results shows that QBA performs better than the above-mentioned methods in terms of solution quality, convergence characteristics and computational efficiency. Thus, QBA proves to be an effective and a robust technique to solve such nonlinear optimization problem.
    Scopus© Citations 7  16  2