Multiobjective Simulated Annealing: Principles and Algorithm Variants
Reads0
Chats0
TLDR
The state of the art of simulated annealing algorithm with a focus upon multiobjective optimisation field is reviewed, allowing gradual convergence to a near-optimal solution.Abstract:
Simulated annealing is a stochastic local search method, initially introduced for global combinatorial mono-objective optimisation problems, allowing gradual convergence to a near-optimal solution. An extended version for multiobjective optimisation has been introduced to allow a construction of near-Pareto optimal solutions by means of an archive that catches nondominated solutions while exploring the feasible domain. Although simulated annealing provides a balance between the exploration and the exploitation, multiobjective optimisation problems require a special design to achieve this balance due to many factors including the number of objective functions. Accordingly, many variants of multiobjective simulated annealing have been introduced in the literature. This paper reviews the state of the art of simulated annealing algorithm with a focus upon multiobjective optimisation field.read more
Citations
More filters
Modified distance calculation in generational distance and inverted generational distance
TL;DR: It is demonstrated using simple examples that some Pareto non-compliant results of GD and IGD are resolved by the modified distance calculation and it is shown that IGD with themodified distance calculation is weakly PareTO compliant whereas the original IGD is Pare to non- Compliant.
Journal ArticleDOI
An improved Simulated Annealing algorithm based on ancient metallurgy techniques
Bernardo Morales-Castañeda,Daniel Zaldivar,Erik Cuevas,Oscar Maciel-Castillo,Itzel Aranguren,Fernando Fausto +5 more
TL;DR: The proposed algorithm modifies the original SA incorporating two new operators, folding and reheating, inspired by the ancient Japanese Swordsmithing technique, and demonstrates the high performance of the proposed method when compared to the originalSA and other popular state-of-the-art algorithms.
Journal ArticleDOI
Artificial intelligence techniques in refrigeration system modelling and optimization: A multi-disciplinary review
Rasel Ahmed,Shuhaimi Mahadzir,Nor Erniza Mohammad Rozali,Kallol Biswas,Fahad Matovu,Kamran Ahmed +5 more
TL;DR: This comprehensive review presents state-of-the-art theory and application of the most widely used CI techniques such as GA, PSO, SA, DE, HTS, CRO, MOGA, and NSGA II in the optimization of various refrigeration systems.
Journal ArticleDOI
A multi-objective AVR-LFC optimization scheme for multi-area power systems
TL;DR: A nonlinear threshold accepting heuristic with an innovative multi-objective optimization architecture is employed to select the control gains of a coupled AVR-LFC scheme for a two-area power system to ensure stable and fast AC generator bus voltage-frequency regulation in react to dynamic disturbances.
Journal ArticleDOI
FCCI: A fuzzy expert system for identifying coincidental correct test cases
TL;DR: FCCI is evaluated by conducting extensive experiments on 17 popular and open source subject programs ranging from small- to large-scale containing both artificial and real faults and indicates that FCCI successfully improves the accuracy of the CC identification as well as the accuracies of the representative SBFL techniques.
References
More filters
Journal ArticleDOI
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Journal ArticleDOI
A fast and elitist multiobjective genetic algorithm: NSGA-II
TL;DR: This paper suggests a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties, and modify the definition of dominance in order to solve constrained multi-objective problems efficiently.
Journal ArticleDOI
Equation of state calculations by fast computing machines
TL;DR: In this article, a modified Monte Carlo integration over configuration space is used to investigate the properties of a two-dimensional rigid-sphere system with a set of interacting individual molecules, and the results are compared to free volume equations of state and a four-term virial coefficient expansion.
Journal ArticleDOI
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
Journal ArticleDOI
Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach
Eckart Zitzler,Lothar Thiele +1 more
TL;DR: The proof-of-principle results obtained on two artificial problems as well as a larger problem, the synthesis of a digital hardware-software multiprocessor system, suggest that SPEA can be very effective in sampling from along the entire Pareto-optimal front and distributing the generated solutions over the tradeoff surface.