Distance-directed augmenting path algorithms for maximum flow and parametric maximum flow problems

Algorithms for network flow problems, such as maximum flow, minimum cost flow, and multi-commodity flow problems, are continuously developed and improved, and so, random network generators become indispensable to simulate the functionality and to test the correctness and the execution speed of these algorithms. For this purpose, in this paper, the well-known Erdős–Rényi model is adapted to generate random flow (transportation) networks. The developed algorithm is fast and based on the natural property of the flow that can be decomposed into directed elementary s-t paths and cycles. So, the proposed algorithm can be used to quickly build a vast number of networks as well as large-scale networks especially designed for s-t flows.

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Hard test generation for augmenting path maximum flow algorithms using genetic algorithms: Revisited

2015 IEEE Congress on Evolutionary Computation (CEC) ◽

10.1109/cec.2015.7257146 ◽

2015 ◽

Cited By ~ 2

Author(s):

Maxim Buzdalov ◽

Anatoly Shalyto

Keyword(s):

Genetic Algorithms ◽

Test Generation ◽

Maximum Flow ◽

Augmenting Path

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Inverse feasibility problems of the inverse maximum flow problems

Sadhana ◽

10.1007/s12046-013-0134-4 ◽

2013 ◽

Author(s):

ADRIAN DEACONU ◽

ELEONOR CIUREA

Keyword(s):

Maximum Flow ◽

Flow Problems

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Resource allocation problem in project management

E3S Web of Conferences ◽

10.1051/e3sconf/20199701003 ◽

2019 ◽

Vol 97 ◽

pp. 01003 ◽

Cited By ~ 2

Author(s):

Irina Burkova ◽

Boris Titarenko ◽

Amir Hasnaoui ◽

Roman Titarenko

Keyword(s):

Resource Allocation ◽

Project Management ◽

Job Shop ◽

Job Shop Scheduling ◽

Maximum Flow ◽

Allocation Problem ◽

Real Problem ◽

Resource Allocation Problem ◽

Flow Problems ◽

Solution Methods

Resource allocation problems in project management are notoriously complex. Therefore the development of efficient algorithms for solving various specific cases is a real problem. This paper shows a specific case of the problem, where a program has a particular structure. The resource allocation problem in such a program is reduced to classical Johnson’s problem or job-shop scheduling problem. Effective solution methods, by way of reducing to maximum flow problems, are suggested for some types of resources. For other cases, heuristic rules are developed, with a description of the situations in which these rules allow good enough solutions to be obtained.

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