• Title/Summary/Keyword: Tradeoff B Life

Search Result 2, Processing Time 0.015 seconds

On the New Age Replacement Policy (새로운 연령교체 방식의 개발)

  • Seo, Sun-Keun
    • Journal of Applied Reliability
    • /
    • v.16 no.4
    • /
    • pp.280-286
    • /
    • 2016
  • Purpose: Recently, Jiang defines the tradeoff B life to minimize a sum of life lost by preventive maintenance (PM) and corrective maintenance (CM) contribution parts and sets up an optimal replacement age of age replacement policy as this tradeoff life. In this paper, Jiang's model only considering the known lifetime distribution is extended by assigning different weights to two parts of PM and CM in order to reflect the practical maintenance situations in application. Methods: The new age replacement model is formulated and the meaning of a weight factor is expressed with the implied cost of failure under asymptotic expected cost model and also discussed with one-cycle expected cost criterion. Results: The proposed model is applied to Weibull and lognormal lifetime distributions and optimum PM replacement ages are derived with corresponding implied cost of failure. Conclusion: The new age replacement policy to escape the estimation of cost of failure in classical asymptotic expected cost criterion based on the renewal process is provided.

A Pareto Ant Colony Optimization Algorithm for Application-Specific Routing in Wireless Sensor & Actor Networks (무선 센서 & 액터 네트워크에서 주문형 라우팅을 위한 파레토 개미 집단 최적화 알고리즘)

  • Kang, Seung-Ho;Choi, Myeong-Soo;Jung, Min-A;Lee, Seong-Ro
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.36 no.4B
    • /
    • pp.346-353
    • /
    • 2011
  • Routing schemes that service applications with various delay times, maintaining the long network life time are required in wireless sensor & actor networks. However, it is known that network lifetime and hop count of trees used in routing methods have the tradeoff between them. In this paper, we propose a Pareto Ant Colony Optimization algorithm to find the Pareto tree set such that it optimizes these both tradeoff objectives. As it enables applications which have different delay times to select appropriate routing trees, not only satisfies the requirements of various multiple applications but also guarantees long network lifetime. We show that the Pareto tree set found by proposed algorithm consists of trees that are closer to the Pareto optimal points in terms of hop count and network lifetime than minimum spanning tree which is a representative routing tree.