scholarly journals Adding value to satisficing decisions using TOPSIS in service provider selection problems

2016 ◽  
Vol 7 (1) ◽  
pp. 34-39
Author(s):  
Solly Matshonisa Seeletse
Keyword(s):  
Service Provider ◽  
Selection Process ◽  
Decision Makers ◽  
Added Value ◽  
Ideal Solution ◽  
Scientific Methods ◽  
Selection Problems ◽  
Selection Processes ◽  
Order Preference ◽  
Reduced Costs

Selection processes of credible candidates in competitions are often flawed. The flaws may be deliberate when there is corruption. In other cases the flaws occur because of the decision makers’ inadequacies. Many competitors do their best in developing exceptional proposals, but unfairness of the decision makers undermines these efforts. Ideally, undeserving candidates should be disqualified, and deserving ones be allowed to contest. Systematic methods should be used in the proposal evaluation, and the process should be verifiable. This paper discusses scientific methods proposed for use to select a criterion-based worthy competitor in service provider selection problems. The method is a technique for order preference by similarity to ideal solution (TOPSIS). TOPSIS is a mathematically-derived statistical method useful to offset the biases in the selection process. Features that address both added value and reduced costs are incorporated in the TOPSIS selection process. A numerical example is included to demonstrate TOPSIS fortes

scholarly journals Supplier selection using different metric functions

2015 ◽  
Vol 25 (3) ◽  
pp. 413-423 ◽  
Author(s):  
S.E. Omosigho ◽  
Dickson Omorogbe
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Fuzzy Topsis ◽  
Ideal Solution ◽  
Order Preference ◽  
Metric Functions ◽  
Metric Function ◽  
Topsis Technique ◽  
Intuitionistic Fuzzy Topsis ◽  
Selection Of

Supplier selection is an important component of supply chain management in today?s global competitive environment. Hence, the evaluation and selection of suppliers have received considerable attention in the literature. Many attributes of suppliers, other than cost, are considered in the evaluation and selection process. Therefore, the process of evaluation and selection of suppliers is a multi-criteria decision making process. The methodology adopted to solve the supplier selection problem is intuitionistic fuzzy TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution). Generally, TOPSIS is based on the concept of minimum distance from the positive ideal solution and maximum distance from the negative ideal solution. We examine the deficiencies of using only one metric function in TOPSIS and propose the use of spherical metric function in addition to the commonly used metric functions. For empirical supplier selection problems, more than one metric function should be used.

scholarly journals KLASIFIKASI SENTRA INDUSTRI PERIKANAN BERBASIS PELABUHAN PERIKANAN: KASUS DI KABUPATEN BELITUNG

2017 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
Marwan Syaukani ◽  
Muhammad Fedi Alfiadi Sondita ◽  
Daniel Monintja ◽  
Akhmad Fauzi ◽  
Victor Petrus Hiliary Nikijuluw
Keyword(s):  
Service Provider ◽  
The Other ◽  
Ideal Solution ◽  
New Classification ◽  
Alternative Formula ◽  
Fishing Capacity ◽  
Order Preference ◽  
Effectiveness And Efficiency ◽  
Multi Criteria Analysis ◽  
Solution Parameter

Klasifikasi pelabuhan perikanan Indonesia yang terdiri atas PelabuhanPerikanan Samudera, Pelabuhan Perikanan Nusantara, Pelabuhan PerikananPantai, dan Pusat Pendaratan Ikan. Klasifikasi tersebut di atas didasari hubungan inti plasma di mana pelabuhan perikanan yang besar ditunjang beberapa pelabuhan perikanan yang lebih kecil (Direktorat Jenderal Perikanan Tangkap, 2008). Hubungan inti plasma tersebut tidak berjalan karena tidak mempunyai pola hubungan yang jelas. Oleh sebab itu diperlukan alternatif klasifikasi pelabuhan perikanan dengan memasukan unsur jaringan industri seperti yang diusulkan oleh Israel & Rouqe (2000) yang mengklasifikasikan pelabuhan perikanan menjadi tiga yaitu penyedia jasa utama, penyedia jasa antara (server), dan client. Penelitian ini bertujuan menentukan klasifikasi sentra industri perikanan berbasis pelabuhan perikanan dalam jaringan industri yang efektifdan efisien dilakukan di Kabupaten Belitung selama 11 bulan sejak Oktober 2007 sampai Agustus 2008. Metode yang dipergunakan adalah multi criteria analysis yang dilanjutkan dengan analisis technique for order preference by similarity to ideal solution. Parameter yang diukur meliputi infrastruktur pelabuhan perikanan, kapasitas kapal perikanan, kemandirian faktor input, dan produksi. Hasil penelitian menunjukan bahwa Pulau Belitung berperan sebagai penyedia jasa utama, Pulau Mendanau, dan Pulau Seliu berperan sebagai penyedia jasa antara (server), dan Pulau Gersik dan Pulau Sumedang berperan sebagai client.Klasifikasi pelabuhan perikanan dalam suatu jaringan industri berimplikasi pada peningkatan efektivitas dan efisiensi pembangunan pelabuhan perikanan tangkap sebagai sentra industri perikanan tangkap.Indonesian government classify fishing port into 4 categories namely Ocean Fishing Port, National Fishing Port, Sea Shore Fishing Port, and Fish Landing Fishing Port. The above classification based on partnership or lingkage industry among fishing ports. However, the lingkage industry do not run effectively due to unappropriate pattern. Improving the condition, Israel & Roque (2000) suggested to classify fishing port into 3 categories namely main service provider, intermediate service provider or server, and client. This paper describes an alternative formula that considers industrial linkage among fishing ports as fishing industrial centers. The research was held on Belitung Regency as long as 11 months from October 2007 to August 2008. There are several factors should be considered in building fishing port namely fishing facilities, fishing capacity, input dependency and fish landing capacity. The 4 factors are analyzed by multi criteria analysis then continued by technique for order preference by similarity to ideal solution analysis. The research concludes that the Belitung is as the main service provider, the Mendanau Island and Seliu Islands are as the intermediate service provider or server, the other 2 islands are as the client. The new classification will increase effectiveness and efficiency of fishing port developments.

scholarly journals A Novel Extension of the Technique for Order Preference by Similarity to Ideal Solution Method with Objective Criteria Weights for Group Decision Making with Interval Numbers

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1460
Author(s):  
Dariusz Kacprzak
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Ease Of Use ◽  
Decision Makers ◽  
Ideal Solution ◽  
Interval Numbers ◽  
Group Matrix ◽  
Order Preference ◽  
Criteria Weights

This paper presents an extension of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with objective criteria weights for Group Decision Making (GDM) with Interval Numbers (INs). The proposed method is an alternative to popular and often used methods that aggregate the decision matrices provided by the decision makers (DMs) into a single group matrix, which is the basis for determining objective criteria weights and ranking the alternatives. It does not use an aggregation operator, but a transformation of the decision matrices into criteria matrices, in the case of determining objective criteria weights, and into alternative matrices, in the case of the ranking of alternatives. This ensures that all the decision makers’ evaluations are taken into account instead of their certain average. The numerical example shows the ease of use of the proposed method, which can be implemented into common data analysis software such as Excel.

scholarly journals Support System for Determination of Low-Income Students Scholarship (BSM) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)

2020 ◽  
Vol 3 (1) ◽  
pp. 1-11
Author(s):  
Abdul Azis ◽  
Bagus Adhi Kusuma ◽  
Alfika Maselia
Keyword(s):  
Middle School ◽  
Data Storage ◽  
Support System ◽  
Low Income ◽  
Selection Process ◽  
System Development ◽  
Ideal Solution ◽  
Low Income Students ◽  
First Semester ◽  
Order Preference

Muhammadiyah 3 Middle School in Purwokerto is the school that organizes the Low-Income Students Scholarship (BSM) program every first semester held in each new school year. During this time, processing student data and other equipment have been processed with manual calculations, as well as data storage using only Microsoft Excel. In selecting ranking, it still uses paper. The paper calculation on the selection of BSM recipients in the previous year is often lost and hard to find already needed, also there is no particular system for processing the data so that the subjective method is still needed by relying trusts on personal. The purpose of this study is the creation of a Decision Support System (DSS) application for Determining Low-Income Students Scholarship (BSM) using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method at Muhammadiyah 3 Middle School in Purwokerto so that the selection process of Low-Income Students Scholarship (BSM) can be used. So that it is right on target to students who are entitled to BSM and can store data safely. The system development method used is a waterfall.

scholarly journals Application of Multi-Attribute Decision-Making Methods for the Selection of Conveyor

2021 ◽  
Author(s):  
Satyam Fulzele ◽  
Satywan Khatke ◽  
Shubham Kadam ◽  
Avinash Kamble
Keyword(s):  
Decision Making ◽  
Analytical Hierarchy Process ◽  
Material Handling ◽  
Selection Process ◽  
Decision Makers ◽  
Variable Cost ◽  
Fixed Cost ◽  
Order Preference ◽  
Multi Attribute Decision Making ◽  
Hierarchy Process

Abstract In the present time of innovation, conveyor assume an exceptionally indispensable part and have huge significance for material handling in different enterprises. A conveyor is essentially utilized for moving any sort of material from one area to other. It is made with nearer precisions, hence the expense related with manufacturing is additionally high. In this manner, it should work with better productivity. The choice of the best conveyor is a crucial activity for designers. Designers need to recognize different variables that will influence the functionalities of the conveyor system to limit bottlenecks in the system. An efficient methodology should be accomplished for the conveyor selection. Subsequently, the current work aims to the selection process of the best option for conveyor by using four decision making methods such as analytical hierarchy process, technique of order preference by similarity to ideal solution, compromise ranking method and Deng’s similarity based method. The selection is done among four alternatives based on six attributes viz: fixed cost each hour, variable cost each hour, conveyor speed, product width, product weight and flexibility. The analytical hierarchy process is used to determine weights of the attributes based on relative importance of each attribute. It is also observed that A3 conveyor is best suitable conveyor. Hence the above proposed strategies help decision-makers to examine and choose the best conveyor by considering the rank obtained of the alternatives.

Supplier Selection using MADM Method Under Uncertainty

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Mohammad Azadfallah
Keyword(s):  
Decision Making ◽  
Supplier Selection ◽  
Selection Process ◽  
Interval Data ◽  
Entropy Method ◽  
Ideal Solution ◽  
Topsis Method ◽  
Powerful Technique ◽  
Order Preference

In existing literature, there are several studies on supplier selection process, which opine that the suppliers information is usually incomplete and uncertain. Several methods have been proposed for solving this problem, one of which is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method with interval data. There is no doubt that the TOPSIS with interval data method is a powerful technique in uncertain decision-making context. Despite its usefulness, it is logical that when data are imprecise, weight is imprecise too. To overcome this limit, the extended Shannons Entropy method with interval data is used. The main findings of this study confirm the effectiveness of the hybrid proposed models.

A circular economy model for waste management in India

2021 ◽  
pp. 0734242X2110291
Author(s):  
Chandrakant B Kamble ◽  
Ramasamy Raju ◽  
Raman Vishnu ◽  
Raju Rajkanth ◽  
Agamuthu Pariatamby
Keyword(s):  
Waste Management ◽  
Circular Economy ◽  
Success Factors ◽  
Decision Makers ◽  
Ideal Solution ◽  
Economy Model ◽  
Critical Success ◽  
Order Preference ◽  
Closing The Loop ◽  
Structured Questionnaire

Management of waste is one of the major challenges faced by many developing countries. This study therefore attempts to develop a circular economy (CE) model to manage wastes and closing the loop and reducing the generation of residual wastes in Indian municipalities. Through extant literature review, the researchers found 30 success factors of CE implementation. Using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) SIMOS approach, the rating and weight of decision makers (DMs) for each factor were collected. A structured questionnaire has been developed incorporating all these 30 factors, to extract the most important factors. The data was collected from top 10 officials (DMs) from the Chennai municipality, who handle three regions (metropolitan, suburbia and industrial). Based on the TOPSIS SIMOS analysis, nine CE implementing factors (critical success factors (CSFs)) among the 30 variables that were significant based on the cut-off value was identified. A CE model has been proposed based on these nine CSFs for waste management in India.

Rating TAs in fuzzy QFD by objective penalty function and fuzzy TOPSIS based on weighted Hamming distance

2020 ◽  
Vol 39 (3) ◽  
pp. 3665-3679
Author(s):  
Jing Wang ◽  
Bing Yan ◽  
Guohao Wang ◽  
Liying Yu
Keyword(s):  
Nonlinear Programming ◽  
Penalty Function ◽  
Quality Function Deployment ◽  
Hamming Distance ◽  
Decision Makers ◽  
Programming Models ◽  
Ideal Solution ◽  
Quality Function ◽  
Order Preference ◽  
Objective Penalty Function

Quality function deployment (QFD) is an useful tool to solve Multi-criteria decision making, which can translate customer requirements (CRs) into the technical attributes (TAs) of a product and helps maintain a correct focus on true requirements and minimizes misinterpreting customer needs. In applying quality function deployment, rating technical attributes from input variables is a crucial step in fuzzy environments. In this paper, a new approach is developed, which rates technical attributes by objective penalty function and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) based on weighted Hamming distance under the case of uncertain preference characteristics of decision makers in fuzzy quality function deployment. A pair of nonlinear programming models with constraints and a relevant pair of nonlinear programming models with unconstraints called objective penalty function models are proposed to gain the fuzzy important numbers of technical attributes. Then, this paper compares the fuzzy numbers by fuzzy technique for order preference by similarity to an ideal solution (TOPSIS) method based on weighted Hamming distance in consideration of the uncertain preference characteristics of decision makers. To end with, the developed method is examined with the numerical examples.

scholarly journals Partner Selection in a Virtual Enterprise: A Group Multiattribute Decision Model with Weighted Possibilistic Mean Values

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Fei Ye ◽  
Qiang Lin
Keyword(s):  
Selection Process ◽  
Virtual Enterprise ◽  
Risk Preferences ◽  
Partner Selection ◽  
Decision Makers ◽  
Mean Values ◽  
Extended Technique ◽  
Fuzzy Environment ◽  
Order Preference ◽  
Decision Making Model

This paper proposes an extended technique for order preference by similarity to ideal solution (TOPSIS) for partner selection in a virtual enterprise (VE). The imprecise and fuzzy information of the partner candidate and the risk preferences of decision makers are both considered in the group multiattribute decision-making model. The weighted possibilistic mean values are used to handle triangular fuzzy numbers in the fuzzy environment. A ranking procedure for partner candidates is developed to help decision makers with varying risk preferences select the most suitable partners. Numerical examples are presented to reflect the feasibility and efficiency of the proposed TOPSIS. Results show that the varying risk preferences of decision makers play a significant role in the partner selection process in VE under a fuzzy environment.

scholarly journals ANALYSIS OF TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION IN DETECTING COFFEE BEAN QUALITY

2021 ◽  
Author(s):  
Solly Aryza ◽  
Lavenia Ulandari
Keyword(s):  
Decision Support ◽  
Good Method ◽  
Decision Makers ◽  
Coffee Bean ◽  
Ideal Solution ◽  
Best Value ◽  
Coffee Beans ◽  
Order Preference ◽  
Coffee Farm ◽  
Analysis Of Technique

Decision support system is a science that can be applied in various fields to be able to assistdecision makers in supporting not as absolute decision makers. As a decision has a reliablemethod in each case or data processed. Like TOPSIS is a very good method in helpingdecision making that is implemented well in a system. In this paper, detection is carried out tohelp support decisions on quality coffee beans. Coffee is a typical drink from variouscountries. Coffee produced from quality coffee beans and coffee farm fields. So that the finalresult of this paper is to get the best value for detecting quality coffee beans based on 3 coffeebean farming fields, in which the three fields are labeled with A1 and the optimal criterionvalue is 0.61.

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