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1
Content available remote An Algorithm for Choosing, Ordering a New Criteria of a Bi-Objective Flow Problem
EN
In this paper, we propose an algorithm which is based on many things: the notions well-known of the simplex network method, Ford Fulkerson’s algorithm and our new idea, which is << the gain cycles >>, applied on a bi-objective minimum cost flow problem. This algorithm permits us to have a good order of many criteria in a rapid and an efficient way; because this classification permits us to structure the optimal area, in which we can choose the best action among the others which exist in the objective space. From this one, we distinguish, that the resolution of this problem comes to find an under set of good actions, among which the decider can select an action of best compromise, or make a decision, in the case where reference indications of the deciders may change. A didactic example is done to illustrate our algorithm.
PL
W pracy omówiono podstawy modelowania łańcuchów dostaw z wykorzystaniem matematycznej teorii grafów. Zaprezentowano podstawy teoretyczne analizy łańcuchów dostaw w aspekcie optymalizacji przepływów w sieciach i analizy czasowo-kosztowej na sieciach stochastycznych. Analizę poparto przykładami na rzeczywistych międzynarodowych łańcuchach dostaw elektronicznych systemów alarmowych do obiektów. W szczególności zaprezentowano analizę łańcucha logistyki zwrotnej, która ma istotne znaczenie w branży ochrony mienia. W zakończeniu sformułowano wnioski ogólne i szczegółowe z pracy.
EN
In the paper the fundamentals of supply chain modelling with the use of mathematical theory of graphs have been described. Theoretical basics of supply chain analysis have been resented in aspects of flow optimization in networks and time-cost analysis in stochastics supply networks. The analysis has been backed up with the examples based on real international supply chains of electronic security systems for buildings and premises. In particular the analysis of chain reverse logistics has been presented, which is of crucial importance in business of security systems. At the end the general and particular conclusions have been formulated.
EN
In this paper we propose a generalization of the Assignment Problem. First, we describe an algorithm, based on network flow techniques, that obtains just one solution of the approached problem; further, we develop an algorithm that is able to find all the solutions. Finally, we discuss how this general form of the Assignment Problem can be applied in solving the Rank Aggregation Problem, in the case of rankings with ties.
EN
Skillful control of a network flow, which creates a real bridge between the supplier and user, is one of the most important conditions for cost-efficient operation of an enterprise, foundry shop included. This paper describes modern principles of the network optimising for better distribution of the moulding sand, using modern methods of operational research and commonly available Excel calculation sheet equipped with an optimising tool called Solver.
5
Content available remote Filtering algorithms for the same and UseBy constraints
EN
We define the same and UsedBy constraints. UsedBy takes two sets of variables X and Z such that X≥Z and assigns values to them such that the multiset of values assigned to the variables in Z is contained in the multiset of values assigned to the variables in X. Same is the special case of UsedBy in which X=Z. We show algorithms that achieve arc-consistency and bound-consistency for these constraints.
6
Content available remote A scaling out-of-kilter algorithm for minimum cost flow
EN
The out-of-kilter algorithm is one of the basic algorithms that solve the minimum cost flow problem. Its drawback is that it can improve the objective function at each iteration by only a small value. Consequently, it runs in pseudo-polynomial time. In this paper, we describe a new out-of-kilter algorithm for minimum cost flow that runs in polynomial time. Our algorithm is a scaling algorithm and improves the objective function at each time by a "sufficiently large" value.
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