Two general-purpose metaheuristic algorithms for solving multiobjective stochastic combinatorial optimization problems are introduced: SP-ACO (based on the Ant Colony Optimization ...
Multi-objective optimization methods are essential to resolve real-world problems as most involve several types of objects. Several multi-objective genetic algorithms have been pro...
Mifa Kim, Tomoyuki Hiroyasu, Mitsunori Miki, Shiny...
A tabu search approach to solve multi-objective combinatorial optimization problems is developed in this paper. This procedure selects an objective to become active for a given it...
Sadan Kulturel-Konak, Alice E. Smith, Bryan A. Nor...
The proliferation of all kinds of devices with different security requirements and constraints, and the arms-race nature of the security problem are increasingly demanding the de...
The generic Multi-objective Evolutionary Algorithm (MOEA) aims to produce Pareto-front approximations with good convergence and diversity property. To achieve convergence, most mu...