Open Access journal
ISSN (Print) 0101-7438
Published by SciELO [680 journals] [SJR: 0.305] [H-I: 6]
- The air transportation hub-and-spoke design problem: comparison
between a continuous and a discrete solution method
Abstract: The hub-and-spoke network design problem, also known as the hub location problem, aims to find the concentration points in a given network flow so that the sum of the distances of the linkages is minimized. In this work, we compare discrete solutions of this problem, given by the branch-and-cut method applied to the p-hub median model, with continuous solutions, given by the hyperbolic smoothing technique applied to a min-sum-min model. Computational experiments for particular instances of the Brazilian air transportation system, with the number of hubs varying from 2 to 8, are conducted with the support of a discretization heuristic and the Voronoi diagram.
- A bilateral and multi-issue negotiation framework to support a supply
chain of construction industry
Abstract: Any interaction involving individuals, whose objectives are conflicting with each other, may establish a negotiation process. In a negotiation, each party should develop his/her own strategy and, normally, a win-lose vision is frequently adopted. The main consequence of this behavior is a result, in which both parties lose, especially when the negotiation involves more than one aspect, such as negotiations resulting from purchases of material for construction industry, where aspects like price, quality and lead-time should be considered. Most of the negotiation involving construction industry adopts a win-lose vision; and, commonly, only the issue price is considered. The goal of this paper is to propose a framework to support negotiations between two parties (buyer and seller) in the supply chain of construction industry. The combination of a win-win strategy with a multicriteria analysis produces a best compromise solution for both parties. A simulation of negotiation using realistic data is presented.
- A comparative analysis of three metaheuristic methods applied to fuzzy
cognitive maps learning
Abstract: This work analyses the performance of three different population-based metaheuristic approaches applied to Fuzzy cognitive maps (FCM) learning in qualitative control of processes. Fuzzy cognitive maps permit to include the previous specialist knowledge in the control rule. Particularly, Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and an Ant Colony Optimization (ACO) are considered for obtaining appropriate weight matrices for learning the FCM. A statistical convergence analysis within 10000 simulations of each algorithm is presented. In order to validate the proposed approach, two industrial control process problems previously described in the literature are considered in this work.
- Collaborative dominance: when doing unto others as you would
have them do unto you is reasonable
Abstract: In this article, we analyze how reasonable it is to play according to some Nash equilibria if players have a preference for one of their opponents' strategies. To formalize our argument, we propose the concepts of collaborative dominance and collaborative equilibrium studying some of its properties. First, we prove that if the collaborative equilibrium exists, then it is always efficient, what can be seen as a focal property. Moreover, we argue that one reason that may lead players not to collaborate is that they can focus on security instead of efficiency properties, in which case they would prefer to play according to maximin strategies. This argument allows us to reduce the hall of reasonable equilibria for games where a collaborative equilibrium exists. Finally, we show that two-player zero-sum games do not have collaborative equilibrium, and that if they contain a strategy profile composed only of collaboratively dominated actions, then such profile is a Nash equilibrium of the game.
- Measures of irregularity of graphs
Abstract: A graph is regular if every vertex is of the same degree. Otherwise, it is an irregular graph. Although there is a vast literature devoted to regular graphs, only a few papers approach the irregular ones. We have found four distinct graph invariants used to measure the irregularity of a graph. All of them are determined through either the average or the variance of the vertex degrees. Among them there is the index of the graph, a spectral parameter, which is given as a function of the maximum eigenvalue of its adjacency matrix. In this paper, we survey these invariants with highlight to their respective properties, especially those relative to extremal graphs. Finally, we determine the maximum values of those measures and characterize their extremal graphs in some special classes.
- Scale of operation, allocative inefficiencies and separability of
inputs and outputs in agricultural research
Abstract: In this article we consider some properties of concern for research production at Embrapa. We apply statistical tests to address questions related to the scale of operation, the presence of allocative inefficiencies and separability of inputs and outputs. The production process is assessed by nonparametric methods with the use of Data Envelopment Analysis. The period under analysis is 2002-2009. We conclude that Embrapa's technology frontier shows variable returns to scale, is allocative efficient in general and is separable in inputs and outputs. These characteristics justify the company policy of adopting a VRS solution and the aggregation of output variables. Scale inefficiencies are the basis for further input congestion studies.
- A multicriteria decision model for selecting a portfolio of oil and gas
Abstract: As well as exploratory activity being at the heart of and guiding the future of the oil industry, it is fundamental that there be a comprehensive analysis covering the various factors and nuances that arise in the selection of exploration projects. Moreover, it is essential that a decision model enables the decisionmaker's preferences to be addressed in a structured (and methodologically correct) way, and one which is easy to understand and to apply in a real-world. Therefore, this paper proposes a multicriteria decision model which underpins using a deterministic procedure for selecting a portfolio of oil and gas exploration projects and thereafter a reality-based application is set out, based on a decision making context within Petrobras.
- Joint optimization of new production, warranty servicing strategy and
secondary market supply under consumer returns
Abstract: In this paper, we consider an OEM selling new products to the market offering (i) a warranty period during which defective units are dealt with at no cost for the customer, and (ii) a full refund to customers who return products that do not meet their expectations (consumer returns). The manufacturer has different options for satisfying the warranty cases as well as for utilizing the consumer returns. Warranty cases could be dealt with by repairing the defective units, replacing them with new products, or replacing them with refurbished consumer returns. Alternatively leftover new products or consumer returns can also be sold on a secondary market. We develop a model and derive the OEMs optimal decisions with respect to these options under demand uncertainty on the primary market.
- Decomposition approach for generation and transmission expansion
planning with implicit multipliers evaluation
Abstract: In an electric power systems planning framework, decomposition techniques are usually applied to separate investment and operation subproblems to take benefits from the use of independent solution algorithms. Real power systems planning problems can be rather complex and their detailed representation often leads to greater effort to solve the operation subproblems. Traditionally, the algorithms used in the solution of transmission constrained operation problems take great computational advantage with compact representation of the model, which means the elimination of some variables and constraints that don't affect the problem's optimal solution. This work presents a new methodology for solving generation and transmission expansion planning problems based on Benders decomposition where the incorporation of the traditional operation models require an additional procedure for evaluating the Lagrange's multipliers associated to the constraints which are not explicitly represented yet are used in the construction of the Benders cuts during the iterative process. The objective of this work is to seek for efficiency and consistency in the solution of expansion planning problems by allowing specialized algorithms to be applied in the operation model. It is shown that this methodology is particularly interesting when applied to stochastic hydrothermal problems which usually require a large number of problems to be solved. The results of this methodology are illustrated by a Colombian system case study.
- Determination of the carbon market incremental payoff considering a
stochastic jump-diffusion process
Abstract: The objective of this paper is to verify the robustness of the Least Square Monte Carlo and Grant, Vora & Weeks methods when used to determine the incremental payoff of the carbon market for renewable electricity generation projects, considering that the behavior of the price of Certified Emission Reductions, otherwise known as Carbon Credits, may be modeled using a jump-diffusion process. In addition, this paper analyses particular characteristics, such as absence of monotonicity, found in trigger curves obtained through use of the Grant, Vora & Weeks method to valuate these types of project.