Understanding Molecular Simulation: From Algorithms to Applications
Understanding Molecular Simulation: From Algorithms to Applications
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization by Means of the Thermodynamical Genetic Algorithm
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
A new dynamical evolutionary algorithm based on statistical mechanics
Journal of Computer Science and Technology
Multiobjective Evolutionary Algorithms: Analyzing the State-of-the-Art
Evolutionary Computation
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Asymptotic convergence of some metaheuristics used for multiobjective optimization
FOGA'05 Proceedings of the 8th international conference on Foundations of Genetic Algorithms
Exploiting molecular dynamics for multi-objective optimization
Expert Systems with Applications: An International Journal
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Molecular system possesses two main characteristics that seem to be applicable for the contrary goals of proximity and diversity in multiobjective optimization, namely the converging pressure in potential fields as dictated by the Maxwell-Boltzmann distribution and the inherent drift to a homogenous and uniform equilibrium with maximum entropy, even without any prior knowledge on the geometry and state of the enclosure. Inspired by this association, this paper explores the notion of exploiting molecular motion to solve multiobjective problems. By adapting the algorithmic structure of molecular dynamics, which essentially represents a technique for the computer simulation of molecular motion, a molecular system that is relevant for multiobjective optimization is proposed, known as molecular dynamics optimizer (MDO). The performance of MDO was subsequently compared with other conventional multiobjective optimizers, specifically EA and PSO, and the experimental results demonstrated that MDO is indeed a viable and practical approach for multiobjective optimization.