Decision Support in Algorithm Selection for Generic Optimisation

This paper presents the development of an algorithm-selection framework supported by a new intuitive user interface for the generic optimisation tool, GenOpt. The framework consists of an algorithm-selection flowchart to help identify relevant algorithms depending on the nature of the problem, followed by an algorithm-selection matrix which evaluates the algorithms’ suitability based on the user requirements. The algorithm selection framework acts as a decision support system to allow the user to select the most appropriate and effective optimisation algorithm for a given problem. Such a procedure improves decision-making, limits the algorithm selection errors and helps the user to achieve solutions closer to the Pareto optimum. The selection framework is supported by a user interface, developed in C++ and compatible with GenOpt, that allows users who do not have prior coding knowledge to use GenOpt successfully. The developed interface presents the user with the most relevant optimisation algorithms from those available in the programme. It allows the user to easily modify algorithmic variables in a user-friendly environment. The novelty of the approach is reflected in the built-in knowledge and intelligence in the pre-selection of optimisation algorithms, which are tailored to specific user-defined problems. This, consequently, improves the overall optimisation results by allowing the user to better understand the optimisation algorithm and its variables.