Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

In this paper, valid bounds for a facility location bilevel problem with capacities are proposed. This problem arises from the situation when a company aims to locate some facilities such that the location and distribution costs are minimized. Nevertheless, the customers are free to choose the facility they prefer for satisfying their demand. Under this assumption, this problem can be modeled as a bilevel program, in which, the upper level is associated with the company’s decision and the lower level corresponds to the allocation of the customers based on their preferences. The resulting lower level problem is NP-hard, which complicates the resolution of the bilevel problem due to the difficulty of obtaining –in general- bilevel feasible solutions. Hence, we explore other approaches for handling this issue. By considering traditional bounds for the lower level problem, we are able to propose valid bounds for the bilevel one. However, the impossibility of classify them as upper or lower bounds is shown through computational experimentation.

The project portfolio selection is one of the most important strategic problems, both in private and in public sector. This can become an incredibly complex task due to several factors. Decision maker (DM) preferences are an essential element for decision-making, vary between decision-makers, and evolve over time.  A strategy is required to assist the decision maker in the identification of the best compromise, an optimal or near-optimal solution that satisfies their preferences. This paper addresses the interactive incorporation of preferences to deal with preferences that evolve over time, specifically, involving the participation of the DM during the process of portfolio optimization and analysis. To model DM preferences, the methodology Preference Disaggregation Analysis (PDA) is incorporated in a hybrid algorithm that gives a solution to the public portfolio selection problem. This paper presents a study of the efficiency of the PDA incorporation in an interactive search process. The experimental results showed the potential of the proposed method.

The supply of products of first necessity is one of the most important problems inside to the humanitarian logistics for, this activity must have attributes such as a) quantity; b) propitious derived from the physical and social aspects of the area; c) speed, and d) reliability.   This document addresses this problem during the emergency phase of the disaster; two methods of solution are put to evaluation and comparison, with their different characteristics, attributes, advantages, and disadvantages, but with the same objective, to find the routes of delivery of products that allow the worthy survival of the victims.   These methods are tested in the municipality of La Perla, Veracruz, Mex., houses 46 localities and it has been impacted by a natural phenomenon in repeated occasions.   Through the heuristic technique of the nearest neighbor (NN), five delivery routes of products are obtained, and a locality is omitted. While the exact programming through the classic vehicle routing problem with capacity (CVRP) throws six paths

The Job Shop Scheduling Problem (JSSP) arises in the context of high-performance computing and belongs to the NP-hard combinatorial optimization problems. The purpose of JSSP is to find the order of execution of a set of jobs on a group of machines, subject to certain precedence and resource availability constraints. The objective in this problem is minimizing the makespan that is the time elapsed from the starting time of the first job until the completion time of the last job. In this paper, a novel hybrid algorithm named AntGenSA for solving JSSP is proposed. AntGenSA uses Ant Colony System (ACS), Simulated Annealing (SA), and Genetic Algorithm (GA). To assess the performance of this algorithm, it is executed in a parallel computer, using a set of instances proposed by Fisher-Thompson, Yamada-Nakano, Taillard, Lawrence, and Applegate-Cook. The evaluation of this algorithm was performed mainly by the quality of the solution but the execution time was measuring as well. The experimental results show that the performance of the parallel execution of AntGenSA is highly competitive with the state-of-the-art algorithms.

The aim of this paper is to analyze the interactions between the factors influencing the performance of the reverse logistics chain. We attempted to explore the factors touching performance of reverse logistics relatively to customer satisfaction. We have proposed a structural analysis based on MICMAC method to classify factors rendering to their direct / indirect influences and dependencies. The outcome of this research is to identify the relationship between the 31 variables used in the experimentation. It can be observed that this exploration may cooperative in reverse logistics policy development arrangement, motivated by customer necessity.

To solve difficult problems of combinatorial optimization, heuristic methods such as Simulated Annealing (SA) and Threshold algorithm (TA) have been proposed. Both SA and TA should have adequate characteristics to explore efficiently the space of solutions. The process to determine these characteristics is known as parameter tuning problem. There is a strong interest in developing techniques to adjust parameters correctly, since the heuristic algorithms have a great applicability in industrial problems. Given the quantitative nature of multiple parameters it is possible to propose the selection of the best parameters of a heuristic as a combinatorial optimization problem. In this paper, a new tuning method based on the proportional controller derived from classical control theory for tuning the cooling scheme in real time is presented. Experimentation shows that this method has a better performance than the classical one.

One of the most frequent problems identified in the hospital network is the administration and control of inventories. When analyzing the logistic indicators, especially those related to inventories, we can observe how the availability indicator of some important items presents lower levels than previously established. It is also common to observe how the levels of inventories for some SKU (Stock-Keeping Unit) are very high while for others the levels of inventories are very low. This article seeks to provide a solution to the problems arising with the administration and control of inventories of a hospital in the City of Cali, Colombia. For this, the two-bin methodology with a periodic control system (R, S) will be used. This model will fit the needs of the hospital network and the resources available for the management of inventories in the organization.

In this paper, we develop a numerical model for imperfect electricity market with governmental subsidies. The model is driven by generalized Cournot model and applied to the current electricity market in Mexico. State-owned electricity producer maximizes its profit taking into account subsidies endowed by government. We establish the problem as mixed complementarity problem [MCP]; and as programming language General Algebraic Modeling System (GAMS) has been chosen. As the solver to obtain numerical solutions we have chosen the solver PATH which is the generalized Newton Method. We have found that generalized Cournot model brings quite reasonable and most realistic prices and demand for electricity, compared to classical Cournot case.