A simulated annealing approach to the solution of minlp problems

Cardoso, Margarida Fonseca; Salcedo, Romualdo; Azevedo, S. Feyo de; Barbosa, Domingos

doi:10.1016/s0098-1354(97)00015-x

Cited by 167 publications

(104 citation statements)

References 30 publications

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“…The criteria for reaching a global optimal solution (x * , y * ) by an approximation (x,ŷ) is given in Equation (2).…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Babu and Angira [1], Cardoso [2], Costa and Oliveira [3], Deep et al [4], Glover [6], Liang et al [11], Mohammed [12], Munawar [13], Wasanapradit et al [28], Young et al [30], Yiqing et al [29] or Yue et al [32]. One advantage of evolutionary algorithms is their robustness towards the analytical properties of the objective and constraint functions.…”

Section: Introductionmentioning

confidence: 99%

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MIDACO Parallelization Scalability on 200 MINLP Benchmarks

Schlueter

Munetomo

2017

Journal of Artificial Intelligence and Soft Computing Research

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This contribution presents a numerical evaluation of the impact of parallelization on the performance of an evolutionary algorithm for mixed-integer nonlinear programming (MINLP). On a set of 200 MINLP benchmarks the performance of the MIDACO solver is assessed with gradually increasing parallelization factor from one to three hundred. The results demonstrate that the efficiency of the algorithm can be significantly improved by parallelized function evaluation. Furthermore, the results indicate that the scale-up behaviour on the efficiency resembles a linear nature, which implies that this approach will even be promising for very large parallelization factors. The presented research is especially relevant to CPU-time consuming real-world applications, where only a low number of serial processed function evaluation can be calculated in reasonable time.

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“…The criteria for reaching a global optimal solution (x * , y * ) by an approximation (x,ŷ) is given in Equation (2).…”

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MIDACO Parallelization Scalability on 200 MINLP Benchmarks

Schlueter

Munetomo

2017

Journal of Artificial Intelligence and Soft Computing Research

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“…Different methods have been proposed to solve the optimization problem 13 . Evolutionary algorithms, such as genetic algorithm 14,15 , particle swarm optimization 16,17 , taboo search [18][19][20] , ant colony optimization [21][22][23] , bees algorithm [24][25][26] , simulated annealing 27,28 , biogeography based optimization 29,30 , firefly optimization 31,32 and artificial bee colony 33,34 are a set of algorithms that were suggested in the past decades for solving optimization problems in different branches of engineering. Imperialist Competitive Algorithm (ICA) is an algorithm introduced for the first time in 2007 by Atashpaz-Gargari and Lucas 35 and used for optimizing inspired by the imperialistic competition and has a considerable relevance to several engineering applications.…”

Section: Introductionmentioning

confidence: 99%

A novel technology for minimizing the synthesis time of nanostructured powders in planetary mills

Abdellahi

Bahmanpour

2014

Mat. Res.

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A key objective in processing of nanostructured powders via high energy ball milling is to minimize the synthesis time. This paper presents the application of imperialist competitive algorithm (ICA) for optimization of milling parameters in order to minimize the synthesis time of nanostructured powders in planetary mills. At first a direct relationship between the inverse of the milling time and the power of the planetary mill was established, which allows the validation of theoretical models proposed in the literature for the energy transfer in milling devices and the comparison of milling equipment efficiencies. Afterwards based on the obtained relation, eight design parameters in milling, namely, number of balls, ball diameter, vial radius, vial height, ball diameter distribution coefficient, plate spinning rate, vial spinning rate and distance between the center of the plate and the center of the vial were optimized. Using these optimized variables in milling process the energy transferred to the raw materials was maximized or in the equivalent expression the synthesis time of nanostructured powders was minimized. At the end a test case was solved to demonstrate the effectiveness and accuracy of the proposed design. Computational results showed that the proposed optimization algorithm is quite effective and powerful in optimizing the planetary mills.

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“…In the chemical engineering field some applications can be mentioned like in heat exchange networks (Dolan, Cummings, & Van, 1990), in batch process scheduling (Cardoso, Salcedo, Azevedo, & Barbosa, 1997;Das, Cummings, & LeVan, 1990;Ku and Karimi, 1991;Patel, Mah, & Karimi, 1991), in the optimization of batch distillation processes (Hanke and Li, 2000) and in dynamic optimization (Faber et al, 2005). In what concerns optimization problems only involving continuous variables one can mention the works of Press and Teukolsky (1991) and Cardoso, Salcedo, and Azevedo (1996).…”

Section: Introductionmentioning

confidence: 99%

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Martins¹,

Costa

2010

Computers & Chemical Engineering

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Screening of topologies developed by hierarchical heuristic procedures can be carried o ut by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration.The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for produc-ing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

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A simulated annealing approach to the solution of minlp problems

Cited by 167 publications

References 30 publications

MIDACO Parallelization Scalability on 200 MINLP Benchmarks

MIDACO Parallelization Scalability on 200 MINLP Benchmarks

A novel technology for minimizing the synthesis time of nanostructured powders in planetary mills

Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

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