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USING FUZZY LOGIC FOR PRICING
Acácio Magno Ribeiro
Electrical Engineering Department, Federal University of Juiz de Fora, Cidade Universitária, 36036-330 Juiz de Fora,
MG, Brazil
Luiz Biondi Neto, Pedro Henrique Gouvêa Coelho
Electronics and Telecommunications Department, State University of Rio de Janeiro,
ua São Francisco Xavier, 524, Bl. A,
Sala 5036, Maracanã, 20550-013, Rio de Janeiro, RJ, Brazil
João Carlos C. B. Soares de Mello, Lidia Angulo Meza
Production Engineering Department, Fluminense Federal University, Rua Passo da Pátria, 156, São Domingos, 24240-
240, Niterói, RJ, Brazil
Keywords: Pricing, Fuzzy S
ets, Risk Assessment
Abstract
: This paper deals with traditional pricing models under uncertainties. A fuzzy model is applied to the
classical economical approach in order to calculate the possibilities of economical indices such as profits
and losses. A realistic case study is included to illustrate a typical application of the fuzzy model to the
pricing issue.
1 INTRODUCTION
Most of current challenges in electrical system
management issues are concerned to the new
world’s environment i.e. competition and
deregulation. The performance of a company should
be measured not only by its product quality but also
by the efficiency of its business in order to achieve
good contracts with low risks and high profits.
One of the major fundamental tasks related to the
n
ew competitive reality is pricing a contract which
can be a tough challenge.
The objective of this paper is to describe a new
com
putational tool customized for the risk
assessment. The mathematical model is based on the
application of fuzzy sets to the classical economic
theory and the overall solution scheme aims to
provide an effective and reliable help to the Decision
Maker on the new challenges of a competitive
environment.
2 CLASSICAL ECONOMICS
In a very simplified way, the classical economic
theory (Mas-Colell et al., 1995; Sher et al. 1986;
Varian 1992) establishes a product price based on
two main functions illustrated in Figure 1: the
production cost and the consumer utility. It is
important to note that every cost is associated to a
desired (or sometimes regulated) quality (reliability,
security) level. Therefore, the presented function
must be regarded as the minimum total cost
necessary to supply the load under corresponding
quality constraints.
Theoretically, in ideal conditions such as perfect
mark
et, competition, etc., the equilibrium between
offer and demand is achieved when the price equals
production costs – the break-even point corresponds
to demand D* cha
rged at price P*. However, it
should be noted that the future demand will not
necessarily equal to the optimal D*. A good load
management scheme would therefore bring the load
to the “profit” region; any commitment to supply
load at the “losses” region would require
331
Magno Ribeiro A., Biondi Neto L., Henrique Gouvêa Coelho P., Carlos C. B. Soares de Mello J. and Angulo Meza L. (2005).
USING FUZZY LOGIC FOR PRICING.
In Proceedings of the Seventh International Conference on Enterprise Information Systems, pages 331-334
DOI: 10.5220/0002548703310334
Copyright
c
SciTePress