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Solution of stochastic multi-objective system design problems
Fatema Baheranwala
, David W. Coit
,
Sadan Kulturel-Konak
Division of Engineering, Business & Computing (Berks)
Research output
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›
peer-review
1
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Keyphrases
System Design
100%
Design Problems
100%
Multi-objective System
100%
Pareto Optimal Solution
100%
Decision Maker
75%
Tabu Search
75%
Best Solution
50%
Multi-objective Function
50%
Redundancy Allocation Problem
50%
Single Solution
50%
Multi-objective Problem
50%
Single Objective Problems
50%
Pareto Optimal Set
50%
Genetic Algorithm
25%
Minimum Weight
25%
System Reliability
25%
Monte Carlo Simulation
25%
Minimizing Cost
25%
Solution Approach
25%
Utility Function
25%
Reliability Estimation
25%
Uncertainty Estimation
25%
Probability Distribution
25%
Single-objective
25%
Best Compromise Solution
25%
Multi-objective Optimization Problem
25%
Realistic Scenario
25%
Minimum Cost
25%
Numerical Value
25%
Weight Function
25%
Search Algorithm
25%
Variance Measure
25%
Pareto Optimality
25%
Heuristic Approach
25%
Objective System
25%
Weighted Sums
25%
Joint Probability Density Function
25%
Explicit Constraints
25%
Utility Theory
25%
Deterministic Solution
25%
Series-parallel System
25%
Redundancy Allocation
25%
Random Weights
25%
Risk-averse Decision
25%
Stochastic Problems
25%
Engineering
Design Problem
100%
Objective Function
100%
Pareto Optimal Solution
40%
Decision Maker
30%
Single Solution
20%
Multiobjective Problem
20%
Objective Problem
20%
Genetic Algorithm
10%
System Reliability
10%
Reliability Estimation
10%
Multiobjective Optimization Problem
10%
Risk Averse
10%
Numerical Value
10%
Pareto Optimality
10%
Weight Function
10%
Real Life
10%
Joint Probability Density Function
10%
Computer Science
Life Situation
10%
Assignment Weight
10%
Weighted Sum Method
10%
Mathematics
Multiobjective Optimization Problem
10%
Function Weight
10%