Further research and extensions

Throughout this book, advances and developments of variants of grouping genetic algorithms (GGAs) have been presented, tested, and applied to various grouping problems in a wide range of industrial disciplines. In spite of these revelations, it is hoped that further extensions to the algorithms are quite possible, and this could lead to further fruitful applications. It is therefore useful to look into the possible developments of the algorithm and their applications. In this view, this chapter highlighted some of the possible further extensions to GGA, from three perspectives, namely (i) extensions to genetic mechanisms and grouping techniques such as the encoding scheme, fitness evaluation, selection, crossover, mutation, inversion, and termination, (ii) hybridization of GGA with other heuristic algorithms, which may lead to hyper-heuristics, and (iii) extensions to use of domain-specific heuristics that enhance the efficiency and effectiveness of algorithms. Following these GGA extensions, potential application areas of the techniques were suggested and presented. Over and above the suggested extensions, there still remains more potency in the use of fuzzy theoretic concepts and fuzzy logic control both in modeling fuzzy problem variables and guiding the global optimization process. Reflecting on the research work presented in this book, it is with much hope that the advances, extensions, and applications in the work will be a significant addition to the body of knowledge in expert systems, computational algorithms, operations research, operations management, and intelligent systems. GGAs are quite handy, when applied to medium- to large-scale real-world grouping problems in various industrial disciplines, including healthcare, information and communication technology, tertiary education, maintenance planning, warehouse and logistics planning, economics and business, production and manufacturing systems, and design. The knowledge will therefore go a long way toward equipping the computational scientists, operations analysts, industrial engineers, and other decision makers.