In this Chapter, we imagine a decision maker (or a group of experts) trying to establish or examine fair procedures to combine opinions about alternatives related to different points of view.

Multiple criteria decision making

Two decades was systematically reviewed on fuzzy MCDM techniques from 1994 to 2014.The database for review was 403 papers from more than 150 high-ranking journals.403 scholarly papers were grouped in four different main fields.Papers were classified based on utilizing, developing and proposing research papers. MCDM is considered as a complex decision-making tool involving both quantitative and qualitative factors. In recent years, several fuzzy FMCDM tools have been suggested to choosing the optimal probably options. The purpose of this paper is to review systematically the applications and methodologies of the fuzzy multi decision-making (FMCDM) techniques. This study reviewed a total of 403 papers published from 1994 to 2014 in more than 150 peer reviewed journals (extracted from online databases such as ScienceDirect, Springer, Emerald, Wiley, ProQuest, and Taylor & Francis). According to experts' opinions, these papers were grouped into four main fields: engineering, management and business, science, and technology. Furthermore, these papers were categorized based on authors, publication date, country of origin, methods, tools, and type of research (FMCDM utilizing research, FMCDM developing research, and FMCDM proposing research). The results of this study indicated that, in 2013, scholars have published papers more than other years. In addition, hybrid fuzzy MCDM in the integrated method and fuzzy AHP in the individual section were ranked as the first and second methods in use. Additionally, Taiwan was ranked as the first country that contributed to this survey, and engineering was ranked as the first field that has applied fuzzy DM tools and techniques.

Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014

Wireless sensor networks (WSNs) have attracted substantial research interest, especially in the context of performing monitoring and surveillance tasks. However, it is challenging to strike compelling tradeoffs amongst the various conflicting optimization criteria, such as the network’s energy dissipation, packet-loss rate, coverage, and lifetime. This paper provides a tutorial and survey of recent research and development efforts addressing this issue by using the technique of multi-objective optimization (MOO). First, we provide an overview of the main optimization objectives used in WSNs. Then, we elaborate on various prevalent approaches conceived for MOO, such as the family of mathematical programming-based scalarization methods, the family of heuristics/metaheuristics-based optimization algorithms, and a variety of other advanced optimization techniques. Furthermore, we summarize a range of recent studies of MOO in the context of WSNs, which are intended to provide useful guidelines for researchers to understand the referenced literature. Finally, we discuss a range of open problems to be tackled by future research.

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A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/192648/Ho - The state-of-the-art integrations and applications of the analytic hierarchy process.pdf

The state-of-the-art integrations and applications of the analytic hierarchy process

A comprehensive MCDM-based approach using TOPSIS, COPRAS and DEA as an auxiliary tool for material selection problems

Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain

The theory of constraints (TOC) emphasizes the exploitation of resource constraints in order to increase the product throughput of an organization. The product-mix decision is one application of the five steps in the TOC. This paper considers an integrated heuristic model comprising the analytic hierarchy process (AHP) and the TOC in a decision model in which priority of product and resource center optimizes the product throughput in a multiple constraint resource environment. An AHP component allows the decision maker to incorporate tangible and intangible criteria into the decision-making process and use the priority rankings of the AHP to represent a measure of value in the TOC model. The TOC identifies the constraints and the product ranking of the AHP maximizes the product throughput in a multiple constraint resource environment. The methodology incorporates sensitivity analysis to provide the decision maker with additional information regarding the robustness of the model so that he or she can make a better decision. The model compares three alternatives: the standard TOC, Integer Linear Programming (ILP), and our own solution. The numerical result shows that the proposed approach is superior to TOC and to ILP analysis and provides a measure of the model's performance.

The TOC-Based Algorithm for Solving Multiple Constraint Resources

This paper proposes three new extended fuzzy multi-criteria decision making methodologies capable of handling subjective and objective factors for the evaluation and selection of warehouse location...

Warehouse location selection by fuzzy multi-criteria decision making methodologies based on subjective and objective criteria

Article history: Received 25 October 2011 Received in revised form November, 2, 2011 Accepted February, 3 2012 Available online 16 February 2012 To acquire the competitive advantages in order to survive in the global business scenario, modern companies are now facing the problems of selecting key supply chain strategies. Strategy selection becomes difficult as the number of alternatives and conflicting criteria increases. Multi criteria decision making (MCDM) methodologies help the supply chain managers to take a lead in a complex industrial set-up. The present investigation applies fuzzy MCDM technique entailing multi-objective optimization on the basis of ratio analysis (MOORA) in selection of alternatives in a supply chain. The MOORA method is utilized to three suitable numerical examples for the selection of supply chain strategies (warehouse location selection and vendor/supplier selection). The results obtained by using current approach almost match with those of previous research works published in various open journals. The empirical study has demonstrated the simplicity and applicability of this method as a strategic decision making tool in a supply chain. © 2012 Growing Science Ltd. All rights reserved

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Subir Kumar Sanyal

Papers

Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain

The TOC-Based Algorithm for Solving Multiple Constraint Resources

Warehouse location selection by fuzzy multi-criteria decision making methodologies based on subjective and objective criteria

A MOORA based fuzzy multi-criteria decision making approach for supply chain strategy selection

A De Novo multi-approaches multi-criteria decision making technique with an application in performance evaluation of material handling device