| dc.contributor.author | Kakarlapudi, Madhumitha | |
| dc.description.abstract | The Strength Pareto Evaluation Algorithm (SPEA) (Zitzler and Thiele 1999) is one of the prominent technique for approximating the pareto-optimal set for the Multiple Objective Optimization (MOO) algorithm. The Strength Pareto Evaluation Algorithm 2 (SPEA2) is an improved version of SPEA that was introduced in the year 2001. SPEA2 in contrast to SPEA incorporates a fine-grained fitness assignment strategy, an improved archive truncation technique, and a density assessment procedure. In this paper, we studied the influence of the optimization ability of SPEA2 on different benchmark functions by evaluating different performance metrics. The benchmark functions used in the paper include 10 constrained functions (CF’s) and 10 unconstrained functions (UF’s), through which, by varying parameters such as number of iterations, variable size, population and archives, we performed our experiments. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Investigation of Strength Pareto Evolutionary Algorithm | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2019-03-29T21:23:28Z | |
| dc.date.available | 2019-03-29T21:23:28Z | |
| dc.date.issued | 2019 | |
| dc.identifier.uri | https://hdl.handle.net/10365/29449 | |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| dc.subject.mesh | Evolutionary computation. | |
| dc.subject.mesh | Multiple criteria decision making. | |
| dc.subject.mesh | Mathematical optimization. | |
| dc.subject.mesh | Genetic algorithms. | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Engineering | en_US |
| ndsu.department | Computer Science | en_US |
| ndsu.program | Computer Science | en_US |
| ndsu.advisor | Ludwig, Simone | |
