Главная Менеджмент Russian journal of management, 2015, том 3, вып. 3 (15) Июнь
Upon decision-making in alternative design problems
Ph.D., Professor of the Department of Industrial Engineering and Management, Ben-Gurion University of the Negev (Beer-Sheva, Israel); e-mail: Этот адрес e-mail защищен от спам-ботов. Чтобы увидеть его, у Вас должен быть включен Java-Script ;
Ph.D., Professor of the Department of Project and Innovation Management, Moscow State University of Economics, Statistics and Informatics (Moscow, Russian Federation); e-mail: Этот адрес e-mail защищен от спам-ботов. Чтобы увидеть его, у Вас должен быть включен Java-Script ;
lecturer of Department of Industrial Engineering and Management, Ariel University (Ariel, Israel), lecturer of Department of Management, Faculty of Social Sciences, Bar-Ilan University (Ramat-Gan, Israel); e-mail: Этот адрес e-mail защищен от спам-ботов. Чтобы увидеть его, у Вас должен быть включен Java-Script
Manuscript received: 30.04.2015. Revised: 05.05.2015. Accepted: 14.05.2015. Published online: 30.06.2015. © РИОР
Abstract. One of the main problems in alternative network planning boils down to determining the optimal variant to carry out the considered simulated program. In this paper we will formulate the optimal variants choice criteria for the case of homogenous alternative networks which have been described in our publications [1—3].
Key words: homogenous alternative stochastic network, full and joint variants, optimal decisionmaking variant, multi-variant optimization, optimality indicator.
While examining homogenous alternative networks the problem focuses on determining the full variant of a design program which is optimal from the viewpoint of a certain accepted criterion. The difference between stochastic and deterministic alternative models reveals itself in future utilization of the results of such “multi-variant” optimization. In deterministic alternative networks the optimal variant has to be executed regardless of any future conditions and circumstances; furthermore, it may be recommended to be adopted as a kind of master plan whilst controlling the process of a complicated system design. For stochastic networks, when each of the competing variants has a non-zero implementation probability, control problems become more complicated, since we are facing the additional indeterminacy as to the ways of reaching the ultimate program’s targets. Taking into account information regarding the stochastic variants quality, which has been acquired by means of the