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This paper aims at proposing a Constraint-based Learning Estimation of Distribution Algorithm (EDA) to solve the Multi-Mode Resource Constrained Project Scheduling Problem (MMRCPSP). This problem is considered a combinatorial optimization problem and consists of a set of tasks to be carried out in an ordered way, limited availability of resources, and an execution mode for each task. Generally, traditional EDAs handle the constraints of the problem using strategies such as penalty, Pareto dominance, or others, without taking into account these constraints during the learning process. These traditional approaches usually cause the generation of infeasible solutions in each iteration. In this paper, an approach based on the constraints handling during the learning process of the probabilistic model is proposed. To validate the performance of the algorithms, the new approach in two scenarios is compared. First, in the solution of a set of classical optimization problems, where different EDAs are compared in terms of efficiency and efficacy. The second group of experiments is performed on a set of instances of the PSPLIB database. In this case, the proposed algorithm is compared with a traditional EDA and with other results reported in the bibliography. The experimental results demonstrate that the proposal outperforms both the results of traditional EDA and other EDA reported in the literature. [ABSTRACT FROM AUTHOR]

In this study we considered the optimization problem that integrates the logistics operations of location, routing and multiperiod inventory in a two echelon distribution network, named 2eLIRP. In this paper we propose a new hybrid metaheuristic based on Tabu search, genetic algorithms and the nearest neighbor heuristic. The performances of our technique was compared with classics metaheuristics and the results of the experiments carried out in 96.67% were better. [ABSTRACT FROM AUTHOR]

This paper presents an algorithm using CSi Application Programming Interface (CSi API), which allows the automation of the structural optimization process for plane frames, linking powerful computational tools such as SAP2000v16 and Matlab. In addition, aspects usually ignored in modelling and structural analysis for structural optimization are included, such as the influence of cracking of concrete elements in their stiffness and the inclusion of a second order analysis. On the other hand, due to the complexity of the objective function, it was necessary to use metaheuristic optimization methods: a hybridization between genetic algorithms and the Nelder-Mead algorithm, instead of the classical methods used in previous studies, obtaining satisfactory results. The results are expressed in the form of design recommendations and they are compared with those obtained in previous investigations. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of applying the optimization of mean-variance mapping technique in the problem of estimating the parameters of the soil model of two horizontal layers. This problem consists of determining the parameters of the soil model from experimental measurements of apparent resistivity obtained with Wenner method, minimizing the mean square error between values of the experimental and theoretical resistivity curves, which are calculated with mathematical expressions and soil parameters acquired through the optimization of mean-variance mapping technique. Several tests were carried out with resistivity measurements that correspond to different soil types, the results were contrasted with those reported in the technical literature and metaheuristics implemented. In conclusion, according to the results, the performance of the optimization of mean-variance mapping technique was found to be superior than other analyzed optimization techniques. [ABSTRACT FROM AUTHOR]

This paper addresses the Capacitated Location-Routing Problem (CLRP) in which the aim is to determine the depots to be opened, the customers to be assigned to each open depot, and the routes to be performed to fulfill the demand of the customers. The objective is to minimize the sum of the cost of the open depots, of the used vehicle costs, and of the variable costs associated with the distance traveled by the performed routes. In this paper, a Granular Tabu Search (GTS) with different diversification strategies within a Iterated Local Search (ILS) is proposed to solve the CLRP. A shaking procedure is applied whenever the best solution found so far is not improved for a given number of iterations. Computational experiments on benchmark instances taken from the literature show that the proposed approach is able to obtain, within short computing times, high quality solutions illustrating its effectiveness. [ABSTRACT FROM AUTHOR]

An efficient methodology for the optimal selection of conductor in distribution systems through the implementation of the metaheuristic optimization technique called Tabu Search is presented in this paper. To represent the problem a mono-objective mathematical model of nonlinear mixed integer type is used. The minimization of investment costs of conductors and operating costs (power losses) for a study period of one year is considered as objective function. A single-phase equivalent system is used for the evaluation. The set of constraints relates to technical and operational characteristics of the system, which are assessed through a backward/forward sweep load flow. Initial configuration to tabu search algorithm is created by using a constructive heuristic that ensures feasibility of the initial solution; to generate the neighborhood strategies of tree searching and graph theory are used. In order to verify its applicability and efficiency, two test feeders of specialized literature are employed, obtaining better quality results than those reported in the literature. [ABSTRACT FROM AUTHOR]

The main objective of this work is the illustration of textual statistical analysis in confronting of the speeches of three great theorists of the world economy; it is aimed to review the emphasis from semantic segments that characterize the speech of each one. In this study, through a correspondence analysis, textual variables from the selected papers were identified, which are presented as characterizing the main concepts that establish patterns in each discourse. The results show the power of this methodology for applications in economics. [ABSTRACT FROM AUTHOR]

This paper exposes and details the most relevant methods for the solution of the Resource Constrained Project Scheduling Problem, RCPSP. A critical review of the state of the art, based on the most significant papers published in the academic literature on this topic is carried out. Initially, several metaheuristic methods of solution are shown, especially those that have been implemented for sequencing problems, and their main characteristics, advantages and disadvantages are explained. Furthermore, the so-called sequence generating schemes and the complexity indices most commonly used are presented. Finally, the test library PSPLIB, used in most academic papers related to such problems is considered. [ABSTRACT FROM AUTHOR]

This paper considers the vehicle routing problem with heterogeneous fleet (VRPH), which tries to determine the routes to be constructed for satisfying the demand of the customers by considering a fleet of vehicles with different capacities and costs not homogeneous. The main objective is to minimize the distance traversed by the different vehicles. This paper proposes a metaheuristic algorithm based on a granular tabu search for the solution of the problem. The algorithm allows infeasible solutions by penalizing them by a dynamic factor which is adjusted during the search. Computational experiments on real instances for a Colombian company show that the proposed algorithm is able to obtain, within short computing times, better solutions for those obtained by the current traditional method for planning the routes. [ABSTRACT FROM AUTHOR]

Tourists plan trips based on their personal preferences and the point of interest information at destination. This paper propose the formulation of optimization problem for their multi-day planning sightseeing where the preferences of the tourists on the points of interest and travel time constraints are fuzzy. The soft computing methodology proposed to solve the problem integrates fuzzy optimization methods with a constructive metaheuristic. Computational results on instances from the team orienteering problem benchmarks are analyzed. [ABSTRACT FROM AUTHOR]

When we face an optimization problem whose de finition (in some aspect) changes over the time, we are in the presence of a Dynamic Optimization Problem (DOP). The aspects that can change are the objective function, the variables' domain, the appearance/disappearance of variables or constraints, etc. This paper aims at providing a first introduction to those who are interested in the topic. Concretely, we present the DOPs, the most common performance measures as well as the methods used to solve them. We also briefly describe some of the most recent reviews and comment some current challenges and research opportunities in DOPs. [ABSTRACT FROM AUTHOR]

In this paper is analyzed and modeled the problem of discovery process models, in order to apply metaheuristic algorithms based on a point and populations. There are two main reasons for the growing interest to improving the efficiency of the discovery algorithms in process mining. First or all, the information systems, that support business processes in organizations, record the details of the executions. These contain a potential knowledge for decision making. In addition to the growing need to support business processes in competitive and rapidly changing environments. In order to meet the objective of this work that is selected best suited metaheuristics algorithms to the problem: The Hill Climbing and Evolutionary Strategy. The main contribution consists in modeling a first approach to the problem of finding models using metaheuristic strategies. [ABSTRACT FROM AUTHOR]

The enormous volume of geospatial data existent and the increment of the necessities to using them in dissimilar applications, have made indispensable the emergence of mechanisms of Geographic Information Retrieval that facilitates the opportune and specify access to this information. In this sense, more used techniques are based on querying and browsing. However, current proposals of Geographic Information Retrieval don't provide good results when the ambiguity in the terms used in the query is present, and their semantics is not treated, and when the information necessities of the users are not well defined. In this paper, a first approach of a Recovery of Geographic Information Model is proposed, in which the use of the browsing technique and a geographical ontology (geo-ontology), as a knowledge resource for supporting the retrieval process, are integrated. The geo-ontology describes and formalizes the semantic information associated to the geospatial data and constitutes the core of the proposed model. Additionally, in the model is included a semiautomatic for enrichment or maintenance the geo-ontology from different sources, as well as a mechanism for visual query generation, which also be supported by the geo-ontology. [ABSTRACT FROM AUTHOR]