A Brief Review of Multi-Concept Multi-Objective Optimization Problems

In the context of design, multi-concept optimization (MCO) refers to the task of concurrently identifying the best concept and the corresponding variable values to optimize certain objective(s). Despite its relevance in various practical domains such as engineering, transport, and product design, there have been limited studies on developing computationally efficient algorithms specialized for MCO problems. One of the contributing factors towards this gap is the lack of benchmark problems for MCO that offer diverse challenges for the systematic evaluation and development of advanced algorithms. In this paper, we conduct a brief review of some existing multi-objective test problems in the domain and discuss some of their shortcomings. The key aim is to highlight the need for the development of a more extensive set of benchmark problems that are flexible and tunable in terms of the challenges posed to the solution methodologies. In turn, we hope that this will encourage the development of more advanced algorithms to solve practical MCO problems in the future.