Abstract
In almost all scientific contributions to the field of Nature-Inspired Algorithms (NIAs), the researchers select some benchmark test suites, which makes possible to draw conclusions on the merit of the proposed algorithm. Hence, it is a vital task to compose comprehensive test suites with the aim of covering variety of different scenarios. Furthermore, while conducting comparative analysis of results obtained with NIAs, selection of the proper performance indicators are of paramount importance. This paper intends to address these two topics with a special stress on NIAs designed for constrained optimization.
Highlights
A constrained optimization problems (COPs) in n dimensional space can be defined by two components: an objective function to be maximized or minimized, and several inequality and equality constraints
The benchmark problems in the domain may be grouped into two main classes based on the resource that they originated from (El-Ghazali, 2009): 1. Artificial Problems: From the early stages of the intelligent problem solving with nature-inspired algorithms (NIAs), different researchers from various backgrounds have introduced countless many COPs
Based on the abstracted guidelines, the benchmark problems are selected to test the different variants of the proposed algorithm
Summary
A COP in n dimensional space can be defined by two components: an objective function to be maximized or minimized, and several inequality and equality constraints. In the vast realm of nonlinear programming with nature-inspired algorithms (NIAs), collecting all constrained optimization problems (COPs) is a cumbersome task to be realized. Keeping this fact in mind, this work attempts to bring together the most common COPs while testing the performance of NIAs by the practitioners.
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