Proposal of a nonlinear multi-objective genetic algorithm using conic scalarization to the design of cellular manufacturing systems

This paper presents a nonlinear multi-objective mathematical model to obtain quality solutions for design problems of cellular manufacturing systems. The objectives of the multi-objective model are, simultaneously, (1) to minimize the number of exceptional elements among manufacturing cells, (2) to minimize the number of voids in a cell, and (3) to minimize cell load variation. In this paper, a new multi-objective genetic algorithm (GA) approach has been proposed to solve the multi-objective problem. In contrast to existing GA approaches, this GA approach contains some revised genetic operators and uses a conic scalarization method to convert the mathematical model's objectives in a single objective function. This approach has been tested and compared with two test problems and some source models collected from the literature. The results have shown that the problem-solving performance of the proposed multi-objective approach is at least as good as the existing approaches in designing the cellular system, and in many cases better than them

Proposal for a decision support software for the design of cellular manufacturing systems with multiple routes

This study presents operational decision support software to efficiently solve cell formation problems with multiple routes. The software includes two revised algorithms that assist decision makers in choosing the best cellular layout. These revised algorithms are the multiobjective genetic algorithm that uses two different scalarization methods such as conic scalarization and weighted sum scalarization and the fuzzy c-means algorithm for problems with multiple routes. From these algorithms, the multiobjective genetic algorithm with conic scalarization has important advantages over many multiobjective approaches in the literature for being able to reach all efficient solutions for linear and nonlinear multiobjective models. These revised algorithms and the decision support software were tested on some data sets collected from an engine manufacturing plant and the literature. The test results showed that, in many cases, the revised multiobjective genetic algorithm with conic scalarization results in better performance than the revised fuzzy c-means algorithm and the methods used in the test problems for problems with multiobjective and multiple routes. Practitioners and researchers can use this operational decision support software and the multiobjective genetic algorithm with conic scalarization to obtain higher-quality cellular layout solutions compared with other software applications in the literature

Recurrent hyponatremia due to tolterodine

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Ankilozan Spondilitli Hastalarda Ortalama Platelet Hacmi Ve Hastalık Aktivitesi Ve Kardiyovaskuler Risk Faktörleri Varlığıyla Ilişkisi

Scopu

Prevalence of carotid artery calcification on panoramic radiographs in patients with renal stones

Aim: To determine the prevalence of carotid artery calcification (CAC) detected in routine dental radiography (PRs) in patients with kidney stones (KSs) and to investigate the relationship between CAC-atherosclerosis and KSs