In this paper, an integration of Analytic Network Process (ANP) and achievement scalarizing functions is proposed to choose the best suppliers and define the optimum quantities among the selected suppliers by considering tangible–intangible criteria and time horizon. To reflect the decision maker’s (DM’s) preferences more accurate, an additive achievement function is defined consist of several ...

the liver is a multifactorial organ which is involved in a number of critical excretory, synthetic and metabolic functions. although the term 'liver function test' is commonly used, it is imprecise since many of the tests, such as transaminase, do not measure liver function. therefore, these tests should be referred to as 'liver enzyme tests', and 'liver function tests' should be the term used ...

In this paper we investigate a vector optimization problem (P) where objective and constraints are given by set-valued maps. We show that by mean of marginal functions and suitable scalarizing functions one can characterize certain solutions of (P) as solutions of a scalar optimization problem (SP) with single-valued objective and constraint functions. Then applying some classical or recent res...

In recent years, the paradigm of ‘soft glassy matter’ has been used to describe diverse nonergodic materials exhibiting strong local disorder and slow mesoscopic rearrangement. As so far formulated, however, the resulting ‘soft glassy rheology’ (SGR) model treats the shear stress in isolation, effectively ‘scalarizing’ the stress and strain rate tensors. Here we offer generalizations of the SGR...

Come with us to read a new book that is coming recently. Yeah, this is a new coming book that many people really want to read will you be one of them? Of course, you should be. It will not make you feel so hard to enjoy your life. Even some people think that reading is a hard to do, you must be sure that you can do it. Hard will be felt when you have no ideas about what kind of book to read. Or...

In this paper, a new general scalarization technique for solving multiobjective optimization problems is presented. After studying the properties of this formulation, two problems as special cases of this general formula are considered. It is shown that some well-known methods such as the weighted sum method, the -constraint method, the Benson method, the hybrid method and the elastic -constrai...

Currently, stochastic optimization on the one hand and multi-objective optimization on the other hand are rich and well-established special fields of Operations Research. Much less developed, however, is their intersection: the analysis of decision problems involving multiple objectives and stochastically represented uncertainty simultaneously. This is amazing, since in economic and managerial ...

The functional programming community is paying increasing attention to static structure-based transformations. For example, generic control operators , such as fold, have been introduced in functional programming to increase the power and applicability of a particular kind of static transformation, called deforestation, which prevents the construction of useless intermediate data structures in ...