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A Two-Phase Linear programming Approach for Redundancy Problems

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Title: Multi-scale Reliability Analysis and Updating of Complex Systems by Use of Linear Programming Author: Yelena Last modified by: YELENA Created Date – PowerPoint PPT presentation

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Title: A Two-Phase Linear programming Approach for Redundancy Problems


1
A Two-Phase Linear programming Approach for
Redundancy Problems
  • by
  • Yi-Chih HSIEH
  • Department of Industrial Management National
    Huwei Institute of Technology Taiwan, R.O.C.

2
Outline
  • Introduction
  • PHASE I - APPROXIMATION STAGE
  • PHASE II - IMPROVING STAGE
  • Example
  • Conclusion

3
Introduction
  • Main advantages of highly reliable systems
  • to reduce loss of money
  • time in the real world
  • Two available approaches to enhance the system
    reliability
  • using highly reliable components
  • using redundant components in various subsystems
    in the system

4
Introduction Second Approach
  • SA Enhances system reliability directly
  • Simultaneously impacted parameters
  • System cost
  • System volume
  • System weight

5
Redundancy Allocation Problem
  • The redundancy allocation problem is to maximize
    system reliability subject to specific
    constraints, e.g. cost, weight and volume etc.
  • Numerous approaches for solving the redundancy
    allocation problem

6
Several Approaches
  • Heuristics
  • Artificial Algorithms
  • genetic algorithms
  • simulated annealing
  • tabu search
  • Exact Methods
  • cutting plane
  • branch-and-bound
  • surrogate constraint method
  • dynamic programming
  • implicit search

7
Continuation
  • Approximate Methods
  • Lagrange multiplier
  • geometric programming
  • discrete maximum principle
  • sequential simplex search
  • random search
  • boundary search
  • differential dynamic programming

8
Two-Phase Linear Programming Approach
  • Phase I (Approximation stage) Initially, with
    the linear approximation of the objective
    function and the relaxation of integer
    constraints, a general LP is solved for the
    approximate solution of problem (P1).
  • Phase II (Improving stage) A 0-1 knapsack
    problem with m n linear constraints is then
    solved to improve the real solutions of Phase I
    to (feasible) integer solutions.

9
  • Thanks
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