This paper presents a multi objective geometric programming model which determines the product`s selling price in two markets. We assume demand is a function of price and marketing expenditure in two markets. The cost of production is also assumed to be a function of demands in both markets. Our model is a posynomial function which is solved using Geometric Programming (GP). In our GP implement...

0377-2217/$ see front matter 2011 Elsevier B.V. A doi:10.1016/j.ejor.2011.06.041 ⇑ Tel.: +886 920884730. E-mail address: [email protected] Goal programming (GP) has been, and still is, the most widely used technique for solving multiple-criteria decision problems and multiple-objective decision problems by finding a set of satisfying solutions. However, the major limitation of goal progr...

genetic programming (gp) is one of the computer algorithms in the family of evolutionary-computational methods, which have been shown to provide reliable solutions to complex optimization problems. the genetic programming under discussion in this work relies on tree-like building blocks, and thus supports process modeling with varying structure. in this paper the systems containing amino acids ...

Data envelopment analysis (DEA) is a common technique in measuring the relative efficiency of a set of decision making units (DMUs) with multiple inputs and multiple outputs. ‎‎Standard DEA models are ‎‎quite limited models‎, ‎in the sense that they do not consider a DMU ‎‎at different times‎. ‎To resolve this problem‎, ‎DEA models with dynamic ‎‎structures have been proposed‎.‎In a recent pape...

Genetic programming (GP) is one of the computer algorithms in the family of evolutionary-computational methods, which have been shown to provide reliable solutions to complex optimization problems. The genetic programming under discussion in this work relies on tree-like building blocks, and thus supports process modeling with varying structure. In this paper the systems containing amino ac...

This paper presents a fuzzy goal programming (FGP) methodology for solving bi-level quadratic programming (BLQP) problems. In the FGP model formulation, firstly the objectives are transformed into fuzzy goals (membership functions) by means of assigning an aspiration level to each of them, and suitable membership function is defined for each objectives, and also the membership functions for vec...

the fuzzy linear regression model with fuzzy input-output data andcrisp coefficients is studied in this paper. a linear programmingmodel based on goal programming is proposed to calculate theregression coefficients. in contrast with most of the previous works, theproposed model takes into account the centers of fuzzy data as animportant feature as well as their spreads in the procedure ofconstr...

Realization of autonomous behavior in mobile robots, using fuzzy logic control, requires formulation of rules which are collectively responsible for necessary levels of intelligence. Such a collection of rules can be conveniently decomposed and eeciently implemented as a hierarchy of fuzzy-behaviors. This article describes how this can be done using a behavior-based architecture. A behavior hie...