Selection of the best alternative for a road project to replace a section in a flood-prone area using GIS and AMC tools

被引:0
|
作者
Zaoui, Mohamed [1 ]
Himouri, Slimane [2 ]
Kadri, Tahar [1 ]
Benaouina, Charef [1 ]
机构
[1] Univ Mostaganem, Lab Mat & Proc Construct LMPC, Mostaganem, Algeria
[2] Univ Mostaganem, Lab Construct Transport & Protect Environm LCTPE, Mostaganem, Algeria
来源
关键词
Multi-criteria analysis; Decision support; GIS; A.H.P; PROMETHEE; CRITERIA;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Decision-making involves the selection from various possible alternatives and generally implicates huge financial resources. In addition, one characteristic of a territory making it difficult to make a decision is its multi-criteria aspect. These multi-criteria generally have antagonistic effects and analytical methods are most congruent for solving this kind of difficult decision-making situation. The work presented in this article focuses on the problem of decision-making in order to identify the most favorable road alignment with regard to a series of topographical, geometric, geological and economic criteria. The main goal of this study is to select the best road alignment project to replace part of the road section of the CW 42 connecting the city of Sidi Belattar to National Road 90 (RN 90) using GIS and AMC tools. This road section has been blocked several times in recent years during rare winter flooding. The proposed approach deals with the following points: First, determination of the relevant criteria using GIS, then evaluation and classification of the various alternatives by applying the AHP method using AMC Expert-choice software and PROMETHEE-GAIA algorithms (laboratory-developed web.d-sight software, coded SMG, ULB). Four variants were recommended to replace the vulnerable section. From these four variants a classification was made, according to the two methods AHP and PROMETHEE. The calculated consistency of the results confirms the effectiveness of the proposed approach. Finally, Alternative 2 and Alternative 1 were ranked first by both AHP and PROMETHEE methods and are therefore a recommended choice. This work aims at helping decision makers to rank four road projects of the study area in order to replace the most vulnerable section.
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页码:307 / 324
页数:18
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