Environmental Engineering Reference
In-Depth Information
MADM problems. The most relevant techniques are: dominant, maxi-min, maxi-
max, conjunctive method, disjunctive methods, lexicographic method, elimination
by aspects, permutation method, Simple Additive Weighting (SAW), hierarchi-
cal additive weighting, Elimination and Choice Expressing Reality (ELECTRE),
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS),
Linear programming Techniques for Multidimensional Analysis of Preference
(LINMAP) and etc. (Hwang and Yoon
1981
). Some other MADM methods have
been successfully used in various location problems in literatures such as Analytic
Network Process (ANP), Analytic Hierarchy Process (AHP), Multi-Attribute
Utility Theory (MAUT), and Stochastic Multi-criteria Acceptability Analysis
(SMAA) (Aras et al.
2004
; Higgs
2006
; Tuzkaya et al.
2008
).
1.3 Agricultural Service Center Location Problem
Improving efficiency is the key parameter of any system to be sustainable and suc-
cessful. A strategy has been developed by Iranian agricultural ministry to create a
network of agricultural service firms. In this study a new framework for specifying
the service center location is developed. Agricultural services have different char-
acteristics in comparison with other public services such as health, police or etc.
These characteristics make their location selection procedure somehow different.
Some assumptions have been considered in current location problems regarding
customers (see Table
1
). There are three types of customers in this location prob-
lem, which their characteristics explained in following section:
Customer type A
: The number of farms is very large, and is hard to consider all
of them; so this study will aggregate the all demand of each village in the center
of that village. Also the demand weight of all farms will be sum up as demand of
village point (these aggregated points will be called as demand point in this study).
Any demand point has different type of service requirements and may need sev-
eral services in several times. Candidate locations and demand points are the same
(both are the village points). For transport any product of each demand point, it's
enough to reach the demand point and the destination is not important in this loca-
tion problem.
Customer type B and C
: they want to access the services on their location.
There may be customers of these types or not.
The layout of location problem of agricultural service centers (ASC) can be
seen in Fig.
1
. Since there are several services, more distance functions should be
considered.
Initially a Delphi fuzzy-AHP survey has been done to extract the objec-
tives and attributes of the ASCLP. Subsequently using Fuzzy Analytic Hierarchy
Process (FAHP) the local weight of location attributes for the location problem
is computed (Zangeneh et al.
2014
). The main aim of current study is developing
a multi-attribute decision making approach to consider all aspects of the ASCLP
for customer type A (the most popular customer of ASC). The ideal solution for
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