This paper present a simulated annealing (SA) algorithm for solving the combined economic emission dispatch (CEED) problem in power systems considering the power limits. The CEED is to minimize both the operating fuel cost and emission level simultaneously while satisfying the load demand and operational constraints. The philosophy involves the introduction of a new decision variable through a ...

An algorithm (M-SIMPSA) suitable for the optimization of mixed integer non-linear programming (MINLP) problems is presented. A recently proposed continuous non-linear solver (SIMPSA) is used to update the continuous parameters, and the Metropolis algorithm is used to update the complete solution vector of decision variables. The M-SIMPSA algorithm, which does not require feasible initial points...

Simulated Annealing and Genetic Algorithm are two well-known metaheuristic algorithms for combinatorial optimization. These two methods have also been used for solving constrained continuous problems. In this study, five constrained continuous problems have been solved both Simulated Annealing (SA) and Genetic Algorithm (GA). Optimum results have been compared with real optimum values obtained ...

in this paper, the researchers have investigated a concatenated robot move (crm) sequence problem and minimal part set (mps) schedule problem with different setup times for two-machine robotic cell. they have focused on simultaneous solving of crm sequence and mps schedule problems with different loading and unloading times. they have applied a simulated annealing (sa) algorithm to provide a go...

Multilayers of Ni-2lAl and Ni-ZOCr-1OAl were subjected to ion beam mixing using 350 keV Ni+ ions and/or thermal annealing at 440 o C to study the development of grain growth and phase morphology. Two film thicknesses of Ni-21 Al (60 and 120 nm) were investigated. Both thermal annealing and irradiation resulted in grain growth in the Ni-21Al samples. Grain size increased by a factor of 7 after i...

This paper provides empirical evidence in support of the hypothesis, that a populational extension of simulated annealing with cooperative transitions leads to a significant increase of efficiency and solution quality for a given combinatorial optimization problem (and a neighborhood relation) if and only if the globally optimal solution is located "close" to the center of all locally optimal s...

We present an in-depth study of the simulated annealing approach to the scheduling of serial multiproduct batch processes under the assumption of a permutation schedule. Four versions of the simulated annealing algorithm are studied based on two move acceptance criteria, the Metropolis algorithm and the Glauber algorithm, and two annealing schedules, the exponential schedule and the Aarts and v...

We consider a special type of dimensionality reduction classification problem where the decision-making objective is to minimize misclassification cost and attributes (MMCA). We propose a two-stage solution approach for solving the MMCA problem. Using simulated data sets and different misclassification cost matrices, we test our two-stage exhaustive and simulated annealing procedures. Our resul...

This paper presents a new method to pack convex polygons into bins (the nesting problem). To do this polygons are placed in rows within bins using a metaheuristic algorithm (simulated annealing) and by utilising the No Fit Polygon. We show that simulated annealing out performs hill climbing. The nesting algorithm is described in detail, along with various aspects that have been incorporated in ...