Date of Graduation
5-2025
Document Type
Thesis
Degree Name
Master of Science in Industrial Engineering (MSIE)
Degree Level
Graduate
Department
Industrial Engineering
Advisor/Mentor
Sullivan, Kelly M.
Committee Member
Liao, Haitao
Second Committee Member
Curry, Robert
Keywords
All-terminal Network; Monte Carlo Simulation; Multi-objective Bottleneck Spanning Tree Problem; Network Reliability; Survival Signature
Abstract
This research examines the problem of estimating the survival signature of all-terminal networks using Monte Carlo (MC) simulation. Following a recent similar result for twoterminal networks, we show that the work required within each MC replication corresponds to solving a multi-objective bottleneck spanning tree (MOBST) problem. We implement the resulting MC procedure using a “Blocks” algorithm from the literature to solve the MOBST in each replication by identifying its minimal set of non-dominated points. We compare this implementation against intuitive benchmark procedures for completing the work within an MC replication. We conduct numerical experiments to assess the efficacy of multi-objective optimization algorithms in expediting survival signature estimation for network structures. Our focus is to determine if these advanced computational strategies can significantly reduce the time complexity inherent in large-scale network analyses.
Citation
Zaman, D. (2025). Survival Signature Estimation for All-Terminal Networks by Solving the Multi-Objective Bottleneck Spanning Tree Problem. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/5625