Chaos-enhanced multi-objective tunicate swarm algorithm for economic-emission load dispatch problem

14Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Climate change and environmental protection have a significant impact on thermal plants. So, the main principles of combined economic-emission dispatch (CEED) problem are indeed to reduce greenhouse gas emissions and fuel costs. Many approaches have demonstrated their efficacy in addressing CEED problem. However, designing a robust algorithm capable of achieving the Pareto optimal solutions under its multimodality and non-convexity natures caused by valve ripple effects is a true challenge. In this paper, chaos-enhanced multi-objective tunicate swarm algorithm (CMOTSA) for CEED problem. To promote the exploration and exploitation abilities of the basic tunicate swarm algorithm (TSA), an exponential strategy based on chaotic logistic map (ESCL) is incorporated. Based on ESCL in CMOTSA, it can improve the possibility of diversification feature to search different areas within the solution space, and then, gradually with the progress of iterative process it converts to emphasize the intensification ability. The efficacy of CMOTSA is approved by applying it to some of multi-objective benchmarking functions which have different Pareto front characteristics including convex, discrete, and non-convex. The inverted generational distance (IGD) and generational distance (GD) are employed to assess the robustness and the good quality of CMOTSA against some successful algorithms. Additionally, the computational time is evaluated, the CMOTSA consumes less time for most functions. The CMOTSA is applied to one of the practical engineering problems such as combined economic and emission dispatch (CEED) with including the valve ripples. By using three different systems (IEEE 30-bus with 6 generators system, 10 units system and IEEE 118-bus with 14 generating units), the methodology validation is made. It can be stated for the large-scale case of 118-bus systems that the results of the CMOTSA are equal to 8741.3 $/h for the minimum cost and 2747.6 ton/h for the minimum emission which are very viable to others. It can be pointed out that the cropped results of the proposed CMOTSA based methodology as an efficient tool for CEED is proven.

References Powered by Scopus

Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems

4225Citations
N/AReaders
Get full text

Tunicate Swarm Algorithm: A new bio-inspired based metaheuristic paradigm for global optimization

1014Citations
N/AReaders
Get full text

Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems

595Citations
N/AReaders
Get full text

Cited by Powered by Scopus

MSHHOTSA: A variant of tunicate swarm algorithm combining multi-strategy mechanism and hybrid Harris optimization

8Citations
N/AReaders
Get full text

A Hybrid Chaotic-Based Multiobjective Differential Evolution Technique for Economic Emission Dispatch Problem

8Citations
N/AReaders
Get full text

MOBCSA: Multi-Objective Binary Cuckoo Search Algorithm for Features Selection in Bioinformatics

3Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Rizk-Allah, R. M., Hagag, E. A., & El-Fergany, A. A. (2023). Chaos-enhanced multi-objective tunicate swarm algorithm for economic-emission load dispatch problem. Soft Computing, 27(9), 5721–5739. https://doi.org/10.1007/s00500-022-07794-2

Readers over time

‘23‘2401234

Readers' Seniority

Tooltip

Lecturer / Post doc 2

67%

PhD / Post grad / Masters / Doc 1

33%

Readers' Discipline

Tooltip

Business, Management and Accounting 1

50%

Engineering 1

50%

Save time finding and organizing research with Mendeley

Sign up for free
0