Preventive Maintenance Decision Based on Data Envelopment Analysis and Technique for Order Preference by Similarity To ideal Solution

DOI

10.2991/msmee-17.2017.91How to use a DOI?

Keywords

Road engineering; DEA; TOPSIS; Preventive Maintenance Decision Conservation Measures

Abstract

In order to improve the effectiveness of multi-objective and multi-attribute decision of road preventive maintenance, the paper considers the characteristics of preventive maintenance decision-making, establishes a preventive maintenance decision-making model based on Data Envelopment Analysis (DEA) and technique for preference by similarity to ideal solution (TOPSIS). Using EDA to calculate the relative effectiveness of every decision index in preventive maintenance, and then calculate the relative effectiveness of the decision-making measures by using the method of multi-objective Euclidean distance. After that, the total order of the alternative results, and the best preventive maintenance decision of the road is finally achieved. The decision-making method takes the owner costs, user costs and construction period as input index, skid resistance, durability, water resistance, driving comfort, appearance, noise reduction as output index, the four kinds of alternative preventive maintenance measures are chosen. The results of case application showed that the model can effectively solve the multi-attribute decision-making problems of preventive maintenance.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fen Cheng
AU  - Wanxin Hu
PY  - 2017/05
DA  - 2017/05
TI  - Preventive Maintenance Decision Based on Data Envelopment Analysis and Technique for Order Preference by Similarity To ideal Solution
BT  - Proceedings of the 2017 2nd International Conference on Materials Science, Machinery and Energy Engineering (MSMEE 2017)
PB  - Atlantis Press
SP  - 451
EP  - 457
SN  - 2352-5401
UR  - https://doi.org/10.2991/msmee-17.2017.91
DO  - 10.2991/msmee-17.2017.91
ID  - Cheng2017/05
ER  -