Open Access journal
ISSN (Print) 0101-7438
Published by SciELO [684 journals] [SJR: 0.305] [H-I: 6]
- A SUPPLIER SELECTION MODEL BASED ON CLASSIFYING ITS STRATEGIC IMPACT FOR A
COMPANY'S BUSINESS RESULTS
Abstract: One of the most important aspects for companies' success is the relationship between companies and their suppliers. Consequently, the way that a supplier is selected is crucial to the outcome of the business. Thus, we propose a multicriteria decision support model with two phases: the analysis of the products/services from suppliers that need to be evaluated, using PROMSORT, and the analysis of the suppliers of such products/services which is considered critical, using PROMETHEE II. The model was applied to a Distribution Center of an important Brazilian retailer which serves stores in the North and Northeast regions of Brazil. Using the proposed model, companies can focus their attention on those products or services that have the greatest impact on their business results. The model predicts that different decision-making processes should be applied, in accordance with the class of importance into which the products or services are classified.
- INVESTORS' ASYMMETRIC VIEWS AND THEIR DECISION TO ENTER BRAZIL'S WIND
Abstract: Market players' investment decisions sometimes surprise analysts, especially when projects that are less feasible in financial terms enter first in the market, before more viable projects. One possible explanation is that firms have different expectations concerning the future of the market. In this article we use the Option-Games approach for asymmetric duopolies to analyze investors' decisions in the first auction for wind power in Brazil, held in 2009, in which some less viable firms pushed more viable firms out of the auction. Our analysis shows that even small differences in the investors' views can yield this unexpected result. When uncertainty is low and expectations are symmetric, the outcome is a lower energy tariff as well as a stronger wind industry in Brazil, highlighting the importance of a clear and credible long term governmental policy, not only for the wind industry, but also for any other industry in its early stages.
- PORTFOLIO SELECTION OF INFORMATION SYSTEMS PROJECTS USING PROMETHEE V WITH
Abstract: This paper presents a multicriteria decision model for selecting a portfolio of information system (IS) projects, which integrates strategic and organizational view within a multicriteria decision structure. The PROMETHEE V method, based on outranking relations is applied, considering the c-optimal concept in order to overcome some scaling problems found in the classical PROMETHEE V approach. Then, a procedure is proposed in order to make a final analysis of the c-optimal portfolios found as a result of using PROMETHEE V. Also, the organizational view is discussed, including some factors that may influence decision making on IS projects to be included in the portfolio, such as adding the company's strategic vision and technical aspects that demonstrate how IS contributes value to a company's business.
- LOCATING PUBLIC SCHOOLS IN FAST EXPANDING AREAS: APPLICATION OF THE
CAPACITATED p-MEDIAN AND MAXIMAL COVERING LOCATION MODELS
Abstract: The area of Guaratiba, in Rio de Janeiro, presents extraordinary population growth rates that exceed all other districts of the city. Moreover, the public investments underway, in view of the 2106 Olympic Games, are making the region even more attractive. Therefore, it is appropriate to suggest proactive measures to avoid the predicted collapse of several public systems among them the education system. This paper considers the projected population for the years 2015 and 2020 and, using various computing resources, specially the ArcGIS Network Analyst tool for measuring traveled distances, proposes locating new facilities with the Capacitated p-Median Model and with the Maximum Covering Location Problem, considering an ideal maximal home-school distance of 1,500 meters, but also evaluating longer distances. Both problems have been solved with AIMMS. The consideration of both models provides a constructive insight that certainly improves the implemented solution and favors the local community.
- AN EVOLUTIONARY STUDY ON CROP PRODUCTION IN SMALL FARM SYSTEMS IN THE
MID-WEST REGION OF BRAZIL BASED ON A LINEAR PROGRAMMING MODEL
Abstract: Based on an agro-technical study for the mid-west region of Brazil, and considering financial conditions like monthly expenses and long-term investments, a mixed integer and dynamic linear model has been proposed for representing crop production systems. This model establishes a monthly dynamic treatment of production and financial activities over a long-term planning horizon for small and medium farm systems. In this paper, by considering more recent government financial policies for the Brazilian agricultural sector related to the Pronaf and Proger credit lines, a mathematical model is updated for distinct situations derived from the use of short and long-term loans which were defined for small and medium farmers. In this way, new versions of the original model are obtained by separately implementing into the production systems economic and financial conditions of credit lines for the years 2006 and 2009. Computational tests are performed and the results obtained are presented in several scenarios. Also, an evolutionary analysis on the socio-economic and financial feasibility of the agricultural farm system is drawn over the last decade by comparing the results obtained to one known from the year 2002.
- DEFENSE-ATTACK INTERACTION OVER OPTIMALLY DESIGNED DEFENSE SYSTEMS VIA
GAMES AND RELIABILITY
Abstract: This paper analyzes defense systems taking into account the strategic interactions between two rational agents; one of them is interested in designing a defense system against purposeful attacks of the other. The interaction is characterized by a sequential game with perfect and complete information. Reliability plays a fundamental role in both defining agents' actions and in measuring performance of the defense system for which a series-parallel configuration is set up by the defender. The attacker, in turn, focuses on only one defense subsystem in order to maximize her efficiency in attacking. An algorithm involving backward induction is developed to determine the equilibrium paths of the game. Application examples are also provided.
- THE LEVERAGE EFFECT AND THE ASYMMETRY OF THE ERROR DISTRIBUTION IN
GARCH-BASED MODELS: THE CASE OF BRAZILIAN MARKET RELATED SERIES
Abstract: Traditional GARCH models fail to explain at least two of the stylized facts found in financial series: the asymmetry of the distribution of errors and the leverage effect. The leverage effect stems from the fact that losses have a greater influence on future volatilities than do gains. Asymmetry means that the distribution of losses has a heavier tail than the distribution of gains. We test whether these features are present in some series related to the Brazilian market. To test for the presence of these features, the series were fitted by GARCH(1,1), TGARCH(1,1), EGARCH(1,1), and GJR-GARCH(1,1) models with standardized Student t distribution errors with and without asymmetry. Information criteria and statistical tests of the significance of the symmetry and leverage parameters are used to compare the models. The estimates of the VaR (value-at-risk) are also used in the comparison. The conclusion is that both stylized facts are present in some series, mostly simultaneously.
- JOINT OPTIMIZATION OF PRODUCTION PLANNING AND VEHICLE ROUTING PROBLEMS: A
REVIEW OF EXISTING STRATEGIES
Abstract: Keen competition and increasingly demanding customers have forced companies to use their resources more efficiently and to integrate production and transportation planning. In the last few years more and more researchers have also focused on this challenging problem by trying to determine the complexity of the individual problems and then developing fast and robust algorithms to solve them. This paper reviews existing literature on integrated production and distribution decisions at the tactical and operational level, where the distribution part is modelled as some variation of the well-known Vehicle Routing Problem (VRP). The focus is thereby on problems that explicitly consider deliveries to multiple clients in a less-than-truckload fashion. In terms of the production decisions we distinguish in our review between tactical and operational production problems by considering lot-sizing/capacity allocation and scheduling models, respectively.
- AN EXPERIMENTAL COMPARISON OF BIASED AND UNBIASED RANDOM-KEY GENETIC
Abstract: Random key genetic algorithms are heuristic methods for solving combinatorial optimization problems. They represent solutions as vectors of randomly generated real numbers, the so-called random keys. A deterministic algorithm, called a decoder, takes as input a vector of random keys and associates with it a feasible solution of the combinatorial optimization problem for which an objective value or fitness can be computed. We compare three types of random-key genetic algorithms: the unbiased algorithm of Bean (1994); the biased algorithm of Gonçalves and Resende (2010); and a greedy version of Bean's algorithm on 12 instances from four types of covering problems: general-cost set covering, Steiner triple covering, general-cost set k -covering, and unit-cost covering by pairs. Experiments are run to construct runtime distributions for 36 heuristic/instance pairs. For all pairs of heuristics, we compute probabilities that one heuristic is faster than the other on all 12 instances. The experiments show that, in 11 of the 12 instances, the greedy version of Bean's algorithm is faster than Bean's original method and that the biased variant is faster than both variants of Bean's algorithm.
- A GENETIC ALGORITHM FOR THE ONE-DIMENSIONAL CUTTING STOCK PROBLEM WITH
Abstract: This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature.