Date of Award
Summer 2021
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computational Modeling & Simulation Engineering
Program/Concentration
Modeling and Simulation
Committee Director
Duc Thai Nguyen
Committee Member
Yuzhong Shen
Committee Member
Hong Yang
Committee Member
Marsha Sosonkina
Abstract
While the minimum cost flow (MCF) problems have been well documented in many publications, due to its broad applications, little or no effort has been devoted to explaining the algorithms for identifying loop formation and computing the θ value needed to solve MCF network problems. This paper proposes efficient numerical procedures and MATLAB computer implementation for computing the θ value. Furthermore, this paper also proposes a mixed heuristic, shortest path (SP) Chavez-Nguyen (or Chayen) Algorithm in Phase 1 (to obtain the basic feasible solution) and, either the conventional MCF or MATLAB’s built-in Linprog() function, in Phase 2 (to obtain the optimal final solution), for a given network problem. Several academic and real-life network problems have been solved to validate the proposed algorithms; the numerical results obtained by the new heuristic code has been compared with the built-in MATLAB Linprog() function (Simplex algorithm) and with the conventional method (where the classical MCF algorithm is applied in both Phases 1 and 2); the results of which are used to validate both the accuracy and computational (time) efficiency of the proposed mixed/hybrid algorithm.
Rights
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DOI
10.25777/wy2m-1f42
ISBN
9798460435739
Recommended Citation
Chávez, Timothy M..
"A New Heuristic Algorithm for Accuracy and Computational Efficiency for Solving Minimum Cost Flow Problems"
(2021). Master of Science (MS), Thesis, Computational Modeling & Simulation Engineering, Old Dominion University, DOI: 10.25777/wy2m-1f42
https://digitalcommons.odu.edu/msve_etds/62
ORCID
0000-0002-6605-2001