Ali Khalilo ¹, Soheil Sadi-Nezhad ¹, Seyed Esmaeil Najafi ¹, Farhad Hosseinzadeh Lotfi ²

Affiliations
1 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, IR
2 Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, IR

Abstract

Background/Objectives: Nowadays, most organizations acknowledge the role and significance of different energy resources in the supply of present and future needs. As a result, they make sizeable investments and undertake extensive research on strategy and policy making as well as definition of infrastructure projects to reduce energy consumption. According to the diversity of projects and their cost of implementation, ranking the projects with different criteria is currently one of the complex problems in organizations. This paper presents a new solution based on the specific architecture of Perceptual Computer (Per-C) for project selection. Methods/Statistical Analysis: In project selection problem, decision makers express their assessment in the form of the linguistic terms that they are vague and uncertain. Using Per-C method is a new experience in project selection problems that has not been mentioned in any literature so far. The Per-C has three components: an Encoder, which maps words into IT2 FS models; a CWW engine, which operates on the input words and whose outputs are FOU(s); and a Decoder, which maps these FOU(s) into a recommendation. We used the Interval Approach (IA) for Decoding, Linguistic Weighted Average (LWA) method is used in CWW engine and Centroid method is used for Decoding. Findings and Application/Improvements: A real case study from a power plant is used to illustrate the applicability of the approach. Using Per-C method is a new experience in project selection problems that has not been mentioned in any literature so far. The results show the applicability of the proposed methodology clearly.

Keywords

Computing with Word and Interval Type 2 Fuzzy Set, Fuel Consumption Reduction, Perceptual Computing Based, Project Selection

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Amin Mahmoudi ¹, Soheil Sadi-Nezhad ¹, Ahmad Makui ¹

Affiliations
1 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, IR

Abstract

Background/Objectives: Supplier Selection Problem (SSP) has become critical issue for purchasing department because of its significant effect toward successful logistic and Supply Chain Management (SCM). Due to the fact that various conflicted criteria must be considered, SSP is inherently Multiple Criteria Decision Making (MCDM) problem. Methods/Statistical Analysis: The aim of this paper is to solve SSP under group decision making and fuzzy environment. To do so, as main contribution of this paper, a hybrid approach which employs both Fuzzy Rule Based System (FRBS) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), is proposed to select suitable supplier. Findings: One advantage of MCDM techniques is providing Decision Maker's (DM) preferences and utilities. To do so, we have modeled DM's utilities using fuzzy logic and then implemented in PROMETHEE method. Improvement/Application: Ultimately, numerical illustration and sensitivity analyses are performed to demonstrate the applicability of the proposed method for a supplier selection problem.

Keywords

Fuzzy Rule based Systems, MADM, PROMETHEE, Supplier Selection Problem

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