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This paper presents two algorithms, Simulated Annealing and Iterated Local Search. Both metaheuristics use a neighborhood hybrid structure to evaluate their effectiveness and maximize the mechanical strength of microalloyed steel. Tests show that the best metaheuristic for this type of problem, which makes use of a neighborhood structure and a chemical composition, is Iterated Local Search because it gives a better mechanical strength than Simulated Annealing. Acicular Ferrite was developed in the laboratory using the best mechanical properties obtained by the heuristics in computational tests. Then the mechanical strength of the created steel was evaluated. The experimental results show that the yield strength obtained in the laboratory is comparable to that obtained in computational tests. [ABSTRACT FROM AUTHOR]

This paper proposes a real mathematical constraint satisfaction model which defines the timetabling problem in the Faculty of Chemical Sciences and Engineering (FCSE) at the Autonomous University of Morelos State, Mexico. A Constructive Approach Algorithm (CAA) is used to obtain solutions in the proposed model. A comparison is made between the CAA’s results and the schedule generated by the FCSE administration. Using the constraint satisfaction model, it is possible to improve the allocation of class hours in the FCSE so that classroom use is more efficient. [ABSTRACT FROM AUTHOR]

A stochastic algorithm for obtaining feasible initial populations to the Vehicle Routing Problem with Time Windows is presented. The theoretical formulation for the Vehicle Routing Problem with Time Windows is explained. The proposed method is primarily divided into a clustering algorithm and a two-phase algorithm. The first step is the application of a modified k-means clustering algorithm which is proposed in this paper. The two-phase algorithm evaluates a partial solution to transform it into a feasible individual. The two-phase algorithm consists of a hybridization of four kinds of insertions which interact randomly to obtain feasible individuals. It has been proven that different kinds of insertions impact the diversity among individuals in initial populations, which is crucial for population-based algorithm behavior. A modification to the Hamming distance method is applied to the populations generated for the Vehicle Routing Problem with Time Windows to evaluate their diversity. Experimental tests were performed based on the Solomon benchmarking. Experimental results show that the proposed method facilitates generation of highly diverse populations, which vary according to the type and distribution of the instances. [ABSTRACT FROM AUTHOR]

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing. [ABSTRACT FROM PUBLISHER]

This paper presents a methodological scheme to obtain the maximum benefit in occupational health by attending to psychosocial risk factors in a company. This scheme is based on selecting an optimal subset of psychosocial risk factors, considering the departments' budget in a company as problem constraints. This methodology can be summarized in three steps: First, psychosocial risk factors in the company are identified and weighted, applying several instruments recommended by business regulations. Next, a mathematical model is built using the identified psychosocial risk factors information and the company budget for risk factors attention. This model represents the psychosocial risk optimization problem as a Multidimensional Knapsack Problem (MKP). Finally, since Multidimensional Knapsack Problem is NP-hard, one simulated annealing algorithm is applied to find a near-optimal subset of factors maximizing the psychosocial risk care level. This subset is according to the budgets assigned for each of the company's departments. The proposed methodology is detailed using a case of study, and thirty instances of the Multidimensional Knapsack Problem are tested, and the results are interpreted under psychosocial risk problems to evaluate the simulated annealing algorithm's performance (efficiency and efficacy) in solving these optimization problems. This evaluation shows that the proposed methodology can be used for the attention of psychosocial risk factors in real companies' cases. [ABSTRACT FROM AUTHOR]

This work presents an optimization proposal to better the computational convergence time in convection-diffusion and driven-cavity problems by applying a simulated annealing (SA) metaheuristic, obtaining optimal values in relaxation factors (RF) that optimize the problem convergence during its numerical execution. These relaxation factors are tested in numerical models to accelerate their computational convergence in a shorter time. The experimental results show that the relaxation factors obtained by the SA algorithm improve the computational time of the problem convergence regardless of user experience in the initial low-quality RF proposal. [ABSTRACT FROM AUTHOR]

The objective of this research was to determine the main genera of nematodes associated with lychee adult plants and their association with the symptom of chlorosis. To do this, from March to August 2013, soil samples were collected from four commercial lychee plots in the tree drip zone. Five asymptomatic and five plants with chlorosis of the Brewster and Mauritius varieties were selected in three phenological stages: flowering, harvesting and vegetative development. Aphelenchus, Ditylenchus, Helicotylenchus, Hemicriconemoides, Longidorus, Mesocriconema, Pratylenchus, Psilenchus, Rotylenchus, Trichodorus, Tylenchorhynchus, Tylenchus and Xiphinema were the main genera identified. The highest number of total nematodes in Mauritius variety was obtained in the harvest stage (300.6, p=0.05), while in Brewster was in flowering (576, p=0.05). A direct relationship between the total population of nematodes and the symptom of chlorosis was not observed for the different phenological stages evaluated. [ABSTRACT FROM AUTHOR]

• The integer-valued vector representing a candidate solution encodes all dataset features. • The feature subset size is determined by using an additional element in the vector. • Feature relevance is represented through its relative position in the vector. • A permutation-matrix-based mutation operator can be used to create new solutions. • A simple repair-based recombination operator is used to ensure feasible solution creation. This paper describes a permutational-based Differential Evolution algorithm implemented in a wrapper scheme to find a feature subset to be applied in the construction of a near-optimal classifier. In this approach, the relevance of a feature chosen to build a better classifier is represented through its relative position in an integer-valued vector, and by using a permutational-based mutation operator, it is possible to create new feasible candidate solutions only. Furthermore, to provide a controlled diversity rate in the population, a straightforward repair-based recombination operator is utilized to evolve a population of candidate solutions. Unlike the other approaches in the existing literature using integer-valued vectors and requiring a predefined subset size, in this approach, this size is determined by an additional element included in the encoding scheme, allowing to find an adequate feature subset size to each specific dataset. Experimental results show that this approach is an effective way to create more accurate classifiers as they are compared with those obtained by other similar approaches. [ABSTRACT FROM AUTHOR]

Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures. [ABSTRACT FROM AUTHOR]