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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]

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]