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With the simulation and optimization of a manufacturing system, the input parameters are sought to obtain the best performance of the system, considering in many cases a single objective or measure of performance. However, many decisions involve multiple criteria, usually in conflict. Currently, companies are required to improve their profitability as well as to reduce their impact on the environment and use energy rationally. In this paper, the wood products manufacturing process of a small company was studied to determine redesign alternatives, with simultaneous economic and environmental criteria. A simulation model of the system was built, which was validated and verified, and an optimization model for it in which two objectives were combined in a single function, incorporating in it the preferences of the decision makers with respect to each criterion. Results expose that combining both criteria it is possible to achieve substantial improvements in the benefit, at the same time that generating less emissions than if only the economic objective were pursued. It is concluded that simulation and optimization combining both criteria can improve economic-environmental performance in wood manufacturing systems, even in small companies. [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]

The present paper discusses the fleet distribution side of the Ship Routing and Scheduling problem combining factors of tactical and operative levels for an industrial service of maritime transportation of cargoes. A mathematical model based on the Generalized Bin Packing Problem wasused, which issupportedin the Local Search algorithm with first ascent and restart, to guarantee the solution of big instances that make computationally untreatable the problem. Through experimentation, it was determined that the best results were obtained by modifying 3 bits in the allocation matrix of ships by transport directions. In addition,a restart parameter was set based in the iterations quantity, so it remarkable improves de exploration process of the algorithm. The variation of the algorithm proposed, allows to obtain acce [ABSTRACT FROM AUTHOR]

Introduction: The goal of this paper is to illustrate how science can aid and have a positive impact on industrial decision-making problems. The combinatorial optimization problem consists of finding a partition of the set of basic units into territories so as to maximize a unique compactness objective function. The solution must also satisfy several constraints or requirements such as, balancing the different node activity measures among territories and territory contiguity. Method: We present a metaheuristic solution method, called GRASP, to a commercial territory design problem motivated by a real-world application in a beverage distribution firm. The heuristic integrates both construction and local search methods that attempt to intelligently exploit the mathematical structure of the problem. Results: The algorithm has been tested in several data sets. The results show the effectiveness of the proposed approach. GRASP obtained solutions of much better quality (in terms of both its dispersion measure and its feasibility with respect to the balancing constraints) than those found by the firm method in relatively fast computation times. Previous to this work, the company was struggling in obtaining design plans with less than 20% imbalance. The proposed method can always obtain design plans with less than 5% imbalance. Conclusion: It has been illustrated how Operations Research models and techniques can aid decision-making problems, resulting in territory plans of better quality. [ABSTRACT FROM AUTHOR]

This paper introduces a proactive version of Hill Climbing (or Local Search). It is based on the identification of the best neighborhood through the repeated application of mutations and the evaluation of theses neighborhood by using FDC (Fitness Distance Correlation). The best neighborhood is used during a time window, and then the analysis is repeated. An experimental study was conducted in 28 functions on binary strings. The proposed algorithm achieves good performance compared to other metaheuristics (Evolutionary Algorithms, Great Deluge Algorithm, Threshold Accepting, and RRT). [ABSTRACT FROM AUTHOR]

Nowadays, both the quantity of information stored and the necessity of developing algorithms in order to extract useful knowledge of this information automatically have been increased in a parallel way. These algorithms are included inside the area of extraction of knowledge in databases and they are focused on a certain model (rules, groups, trees). The development of appropriate models can lead to obtaining successful decisions and for that reason this paper proposes a more flexible way to represent the extracted knowledge of databases. The presented method is based on the paradigm of predicates logic and the calculation of its values using fuzzy logic operators. It also includes a process of optimization that allows to obtain the results and to improve them. [ABSTRACT FROM AUTHOR]

This paper studied the permutation flowshop with sequence dependent setup times and makespan minimization. An ant colony algorithm which turns the original problem into an asymmetric TSP (Traveling Salesman Problem) structure is presented, and applied to problems proposed in the literature and is compared with an adaptation of the NEH heuristic. Subsequently a neighborhood search was applied to the solution obtained by the ACO algorithm and the NEH heuristic. [ABSTRACT FROM AUTHOR]

This paper studied the permutation flowshop with sequence dependent setup times and makespan minimization. An ant colony algorithm which turns the original problem into an asymmetric TSP (Traveling Salesman Problem) structure is presented, and applied to problems proposed in the literature and is compared with an adaptation of the NEH heuristic. Subsequently a neighborhood search was applied to the solution obtained by the ACO algorithm and the NEH heuristic. [ABSTRACT FROM AUTHOR]

The aim of this paper is to analyze the results of the implementation of several parallelization techniques for the metaheuristics applied to the p-median problem. Further analysis showed: constraints on the number of processors used because of the network technology, advantages in the use of multiprocessors and the penalty in performance when using intensive communications strategies. Moreover, within the optimization using heuristics there is always an implicit balance between speed in obtaining a solution and the quality of it, which suggests the use of hybrid strategies that exploit the best of each. [ABSTRACT FROM AUTHOR]