Non-interactive approach to solve multi-objective thermal power dispatch problem using composite search algorithm
[Display omitted] •A non-interactive approach is employed to solve multi-objective problem.•A Chaotic differential evolutionary and Powell’s method based approach is proposed.•Two CDEPS variants: Gauss map and Tent map based are proposed.•Tested on generalized test functions and multi-objective load...
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| Veröffentlicht in: | Applied soft computing Jg. 65; S. 644 - 658 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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Elsevier B.V
01.04.2018
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| ISSN: | 1568-4946, 1872-9681 |
| Online-Zugang: | Volltext |
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| Abstract | [Display omitted]
•A non-interactive approach is employed to solve multi-objective problem.•A Chaotic differential evolutionary and Powell’s method based approach is proposed.•Two CDEPS variants: Gauss map and Tent map based are proposed.•Tested on generalized test functions and multi-objective load dispatch problem.•Wilcoxon signed rank test is employed to analyze the performance.
This paper deals with a non-interactive approach to solve multi-objective thermal power load dispatch (MTPLD), where either decision maker is not involved or preference information is available in prior. To reduce the computational complexities due to generation of Pareto-front and selection of satisficing solution, this paper adopts no-preference approach. A satisficing function to resolve the conflict of non-commensurable objectives is proposed, which reformulates the MTPLD problem as scalar thermal power load dispatch (MTPLD) problem. Owing to ambiguous or vague in objectives, the proposed method exploits fuzzy theory. MTPLD problems’ satisfying solution is obtained by implementing hybrid chaotic differential evolution algorithm and Powell’s pattern search algorithm (CDEPS). The chaotic differential evolution algorithm is responsible for the diversification of feasible solutions and provides global solution. Whereas Powell’s pattern search, method improves the exploitation by performing local search. The paper investigates the performance of two CDEPS variants based on Gauss map and Tent map, respectively. The performance of the proposed solution procedure is analyzed using generalized benchmark test functions and complex MTPLD problems. The exhaustive analysis using non-parametric significance test and descriptive statistics shows that the Tent map based CDEPS solution procedure has better ability to generate quality generation schedule and faster convergence rate. |
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| AbstractList | [Display omitted]
•A non-interactive approach is employed to solve multi-objective problem.•A Chaotic differential evolutionary and Powell’s method based approach is proposed.•Two CDEPS variants: Gauss map and Tent map based are proposed.•Tested on generalized test functions and multi-objective load dispatch problem.•Wilcoxon signed rank test is employed to analyze the performance.
This paper deals with a non-interactive approach to solve multi-objective thermal power load dispatch (MTPLD), where either decision maker is not involved or preference information is available in prior. To reduce the computational complexities due to generation of Pareto-front and selection of satisficing solution, this paper adopts no-preference approach. A satisficing function to resolve the conflict of non-commensurable objectives is proposed, which reformulates the MTPLD problem as scalar thermal power load dispatch (MTPLD) problem. Owing to ambiguous or vague in objectives, the proposed method exploits fuzzy theory. MTPLD problems’ satisfying solution is obtained by implementing hybrid chaotic differential evolution algorithm and Powell’s pattern search algorithm (CDEPS). The chaotic differential evolution algorithm is responsible for the diversification of feasible solutions and provides global solution. Whereas Powell’s pattern search, method improves the exploitation by performing local search. The paper investigates the performance of two CDEPS variants based on Gauss map and Tent map, respectively. The performance of the proposed solution procedure is analyzed using generalized benchmark test functions and complex MTPLD problems. The exhaustive analysis using non-parametric significance test and descriptive statistics shows that the Tent map based CDEPS solution procedure has better ability to generate quality generation schedule and faster convergence rate. |
| Author | Dhillon, J.S. Kothari, D.P. Singh, Nirbhow Jap |
| Author_xml | – sequence: 1 givenname: Nirbhow Jap surname: Singh fullname: Singh, Nirbhow Jap email: nirbhow@thapar.edu organization: Department of Electrical and Instrumentation Engineering, Thapar University, Patiala, 147004, Punjab, India – sequence: 2 givenname: J.S. surname: Dhillon fullname: Dhillon, J.S. email: jsdhillon@sliet.ac.in organization: Department of Electrical and Instrumentation Engineering, Sant Longowal Institute of Engineering and Technology, Longowal, Sangrur, 148106, Punjab, India – sequence: 3 givenname: D.P. surname: Kothari fullname: Kothari, D.P. email: dpkvits@gmail.com organization: Gaikwad-Patil Group of Institutions, Wardha Road, Nagpur, 441 108, India |
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| Keywords | Thermal power load dispatch Multi-objective optimization Surrogate worth function Powell’s pattern search Chaotic differential evolution algorithm No preference approach |
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