نتایج جستجو برای: simulated annealing algorithm sa
تعداد نتایج: 900894 فیلتر نتایج به سال:
The permutation flowshop scheduling problem with the objective of minimizing total flow time is known as a NP-hard problem, even for the two-machine cases. Because of the computational complexity of this problem, a multi-start simulated annealing (MSA) heuristic, which adopts a multi-start hill climbing strategy in the simulated annealing (SA) heuristic, is proposed to obtain close-to-optimal s...
Fuzzy Cognitive Maps (FCMs) have successfully been applied in numerous domains to show the relations between essential components in complex systems. In this paper, a novel learning method is proposed to construct FCMs based on historical data and by using meta-heuristic: Genetic Algorithm (GA), Simulated Annealing (SA), and Tabu Search (TS). Implementation of the proposed method has demonstrat...
In this paper, optimal placement of Phasor Measurement Unit (PMU) using Global Positioning System (GPS) is discussed. Ant Colony Optimization (ACO), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for this problem. Pheromone evaporation coefficient and the probability of moving from state x to state y by ant are introduced into the ACO. The modifi...
This paper proposes a hybrid optimization method based on the fusion of the Simulated Annealing (SA) and Clonal Selection Algorithm (CSA), in which the SA is embedded in the CSA to enhance its search capability. The novel optimization algorithm is also employed to deal with several nonlinear benchmark functions as well as a practical engineering design problem. Simulation results demonstrate th...
This paper shows how the simulated annealing (SA) algorithm provides a simple tool for solving fuzzy optimization problems. Often, the issue is not so much how to fuzzify or remove the conceptual imprecision, but which tools enable simple solutions for these intrinsically uncertain problems. A well-known linear programming example is used to discuss the suitability of the SA algorithm for solvi...
Abstract: In this paper, an exergy analysis approach is proposed for optimal design of distillation column by using simulated annealing algorithm. First, the simulation of a distillation column was performed by using the shortcut results and irreversibility in each tray was obtained. The area beneath the exergy loss profile was used as Irreversibility Index in the whole column. Then, First Opti...
We describe a comparison between Simulated Annealing (SA), Dispatch Rules (DR), and a Coevolutionary Distributed Genetic Algorithm (DGA) solving a random sample of integrated planning and scheduling (IPS) problems. We found that for a wide range of optimization criteria the DGA consistently outperformed SA and DR. The DGA finds 8-9 unique high quality solutions per run, whereas the other techni...
This paper proposes a hybrid optimization method based on the fusion of the Simulated Annealing (SA) and Clonal Selection Algorithm (CSA), in which the SA is embedded in the CSA to enhance its search capability. The novel optimization algorithm is also employed to deal with several nonlinear benchmark functions as well as a practical engineering design problem. Simulation results demonstrate th...
Modeling of fermentation processes is so complicated and uncertain; therefore it is necessary to provide a robust and appropriate dynamic optimization method. In order to obtain the maximum amount of yeast (Saccharomyces cerevisiae), the bioreactor must be operated under optimal conditions. To determine substrate feeding in a fed-batch bioreactor, a simulated annealing (SA) approach was examine...
The quadratic assignment problem (QAP) is one of the well-known combinatorial optimization problems and is known for its various applications. In this paper, we propose a modified simulated annealing algorithm for the QAP – M-SA-QAP. The novelty of the proposed algorithm is an advanced formula of calculation of the initial and final temperatures, as well as an original cooling schedule with osc...
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