Pendekatan Pengembangan Metaheuristik dalam optimisasi kombinatorial

Abstract

Combinatorial problems are problems that have a finite set of feasible solutions. Although in principle the solution to this problem can be obtained with complete enumeration, in complex problems it takes time that cannot be practically accepted, combinatorial analysis is a mathematical study of the arrangement, grouping, ordering, or selection of discrete objects, usually limited in number (finite in number) , many combinatorial optimization problems have been generated by research in computer design, computational theory, and by computer applications on numerical problems that require new methods, new approaches, and new mathematical insights, on combinatorial optimization, the function g (x) is defined as mapping g: {0,1} n → {0,1}, obtaining feasible regions Most methods for solving combinatorial optimization problems propose feasible regions, namely areas that are constrained by problem constraints after relaxation such as counts or binary variables, Field slices generally use the metaheuristic method proposed by para Other researchers, for example Genetic algorithms, simulated annealing, taboo search, plant propagation, methods do not use feasible regional concepts, but proposing the starting point for abstract completion is a brief summary of the paper to help readers quickly ascertain the research objectives and match the research needs.