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In this paper, a problem of scheduling jobs with different sizes and fuzzy processing times (FPT) on non-identical parallel batch machines to minimize makespan is investigated. Moreover, the processing time (PT) of each batch is subject to the location-based learning and total-PT-based deterioration effect. Since this is an NP-hard combinatorial optimization problem, an improved intelligent algorithm based on fruit fly optimization algorithm (IFOA) is proposed. To verify the performance of the algorithm, the IFOA is compared with three state-of-the-art algorithms. The comparative results demonstrate that the proposed IFOA outperforms the other compared algorithms. [ABSTRACT FROM AUTHOR]

This paper concerns the optimization problem arising when a statistical agency must modify microdata to guarantee that the records satisfy a set of rules (called edits). Indeed, before using a collection of data records to infer statistical properties of some groups of responders, the agencies must check and possibly correct the consistence of the collected data. To this end, the edits must be tested on each record and whenever a record does not satisfy all the edits, then the agency must determine the fields in the record to be modified, as well as imputing the new values. Among all the possible solutions, the statistical agency is interested in finding those requiring a minimum number of modified fields, thus leading to a combinatorial optimization problem known as Editing-and-Imputation Problem. This paper presents an Integer Linear Programming model for the specific case in which all edits are linear constraints, and proposes a branch-and-cut algorithm for the exact solution. An extensive computational analysis shows the good performance of our proposal on randomly-generated and artificial instances. The algorithm is used in a new software (TEIDE) to be applied by the Statistical Office of Canary Islands (ISTAC). [ABSTRACT FROM AUTHOR]

It is known that the minimum affine separating committee (MASC) combinatorial optimization problem, which is related to some machine learning techniques, is NP-hard and does not belong to Apx class unless P=NP. In this paper, it is shown that the MASC problem formulated in a fixed dimension space within n>1 is intractable even if sets defining an instance of the problem are in general position. A new polynomial-time approximation algorithm for this modification of the MASC problem is presented. An approximation ratio and complexity bounds of the algorithm are obtained. [ABSTRACT FROM AUTHOR]

Robust optimization searches for optimal solutions which remain feasible under the effect of uncertainties. The conventional robust optimization, however, often requires great computational cost to find robust solutions. This paper introduces a novel robust optimization method based on genetic algorithm. In this method, individuals with "good" performance are selected and tested for their robustness for reduction of computational time. It is shown that the present method works in shorter time in comparison with the conventional robust optimization. [ABSTRACT FROM AUTHOR]

Recently, genetic algorithms (GAs) and their hybrids have achieved great success in solving difficult combinatorial optimization problems. In this paper, the issues related to the performance of the genetic search in the context of the grey pattern problem (GPP) are discussed. The main attention is paid to the investigation of the solution recombination, i.e., crossover operators which play an important role by developing robust genetic algorithms. We implemented seven crossover operators within the hybrid genetic algorithm (HGA) framework, and carried out the computational experiments in order to test the influence of the recombination operators to the genetic search process. We examined the one point crossover, the uniform like crossover, the cycle crossover, the swap path crossover, and others. A so-called multiple parent crossover based on a special type of recombination of several solutions was tried, too. The results obtained from the experiments on the GPP test instances demonstrate promising efficiency of the swap path and multiple parent crossovers. [ABSTRACT FROM AUTHOR]