Sorting retail locations in a large urban city by using ELECTRE TRI-C and trapezoidal fuzzy numbers

Pereira, Javier; Oliveira, Elaine Cristina Batista de; Gomes, Luiz Flávio Autran Monteiro; Araújo, Renato Monte

doi:10.1007/s00500-018-3068-2

Cited by 20 publications

(3 citation statements)

References 33 publications

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“…The ELECTRE TRI-C has been applied in several studies and to support managerial decisions in public and private sectors (Govindan and Jepsen, 2015;Pereira and Mota, 2016;Costa et al, 2017;Pereira et al, 2019aPereira et al, , 2019b. The attractiveness criteria's importance, reflected in its weight, can be determined according to Simo's revised procedure (Figueira and Roy, 2002).…”

Section: Classification Methodsmentioning

confidence: 99%

Classification model for bid/no‐bid decision in construction projects

Araújo

Alencar

Mota

2021

Int Trans Operational Res

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For construction companies, the decision about whether to bid for a project is a strategic decision. This paper provides a model for assessing project attractiveness levels and deciding whether to submit a proposal. The model introduces a classification model that incorporates fuzzy preferential information to evaluate project attractiveness under multiple dimensions and enables the decision‐maker to make more effective decisions. Projects are assigned to ordinal categories of attractiveness based on an adapted fuzzy ELECTRE TRI‐C procedure. The main advantages of this model are that the attractiveness level can be used as an input for the bidding strategies, the attractiveness evaluation can support the contractor in prioritizing the projects to bid on, and the model captures the decision process's subjective assessments and situations of imprecision observed on early phases of the project life cycle.

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Section: Classification Methodsmentioning

confidence: 99%

Classification model for bid/no‐bid decision in construction projects

Araújo

Alencar

Mota

2021

Int Trans Operational Res

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“…In the study of the issues of retail site selection, competition degree [37] and market potential [38] are important evaluation indexes. However, considering only the competition degree of the business area factor may ignore the difference in the actual business situation of many stores.…”

Section: Methodsmentioning

confidence: 99%

Site Selection Improvement of Retailers Based on Spatial Competition Strategy and a Double-Channel Convolutional Neural Network

Ouyang

Fan

Wang

et al. 2020

IJGI

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The issue of site selection has become a critical challenge in the development of the retail industry with the growth of the Chinese economy and the improvement in the level of household consumption. Previous studies have considered the area of stores as the main factor of retail competition; however, the actual business performance of different stores in these studies was ignored. In addition, few studies have considered the differences in the spatial distribution of the factors of site selection. In this study, we discuss the improvement of site selection of small retail shops. A spatial competition index model was proposed as one of the features in estimating region market potential, and a market demand regression model of a double-channel convolutional neural network (CNN) was constructed based on the spatial correlation range of features. The study area was Guiyang, China. The experiments were based on the monthly sales data of fast-moving consumer goods retail stores in Guiyang. On the basis of the estimated results of the model, 18 sites with high potential for market demand were recommended. The performance of the proposed model was the best among well-known regression methods. Moreover, in comparison with a single-channel CNN, the proposed model decreased the root mean square error by 22.61%. Evaluation results showed that the proposed method could provide effective decision support for the issue of retail site selection.

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“…The proposed model is tested on an application of building energy class improvement and obtained solution results are evaluated. Tıp: Hastaların belirtiler temelinde hastalık sınıflarına sınıflandırılması [9] Örüntü tanıma: Nesnelerin veya bireylerin fiziksel özelliklerinin incelenmesi ve tanımlanması [10] İnsan kaynakları yönetimi: Nitelikleri doğrultusunda personelin uygun meslek gruplarına atanması [11] Üretim sistemleri yönetimi ve teknik teşhis: Stok sınıflandırma [12], tedarikçilerin gruplandırılması [13], karmaşık üretim sistemlerinin arıza teşhisi amacıyla izlenmesi [14] Pazarlama: Müşteri memnuniyeti ölçümü, farklı müşteri sınıflarının özelliklerinin analizi, mağaza yeri seçeneklerinin değerlendirilmesi [15], piyasa nüfuz stratejilerinin geliştirilmesi vb. [16] Çevre ve enerji yönetimi, ekoloji: Farklı enerji politikalarının çevresel etkilerinin analizi ve ölçülmesi, enerji politikalarının ülke düzeyinde etkinliğinin araştırılması [17,18] Finansal yönetim ve ekonomi: İşletme başarısızlığı tahmini, firmalar ve tüketiciler için kredi riski değerlendirmesi, hisse senedi değerlendirme ve sınıflandırma, ülke risk değerlendirmesi, tahvil derecelendirme vb.…”

Section: 17341/gazimmfd539218unclassified

İki amaçlı ters çok kriterli sıralama problemi için hedef programlama modeli

Ecer

Kabak

Dağdeviren

2020

Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi

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Bi-objective inverse multiple criteria sorting problem  Linear multiple criteria sorting model  Goal programming approach to obtain compromise solution between conflicting objectives Some kind of multi-criteria decision-making problems are interested in the assignment of objects to predetermined classes. Based on the existence of preference order between object classes, these problems are called as multi-criteria sorting or classification problems. Inverse multi-criteria sorting problem deals with the improvement of class assignments for objects to more preferred classes. In this study, a bi-objective formulation for inverse multi-criteria ranking problem is proposed. Solution to the model for a building energy efficiency labels improvement application is obtained by using goal programming approach to find a compromise solution between the improvement plan cost and the number of objects assigned to preferred classes. Figure A. Steps of modelling and solution process for the proposed model Purpose: The main aim of this study is to propose a new model for inverse multi-criteria sorting problem in order to extend the problem into multi-objective optimization context. To do so, a bi-objective model is proposed and solution to the model is obtained by goal programming approach. Theory and Methods: Inverse multi-criteria sorting problem aims to determine improvement strategies for assignment of objects to more preferred classes in sorting applications. The proposed model in this study is a multi-objective integer linear programming model. To obtain a compromise solution between two objectives, goal programming approach is utilized as the solution methodology. Results: A numerical example on the improvement of building energy efficiency labels is presented. According to the criteria used in the BEP-TR model, which measures the energy efficiency of buildings in Turkey, improvement plan is developed for energy labels of ten buildings. Conclusion: The first multi-objective model for inverse multi-criteria sorting problem is proposed in this study. Solution results seems promising for application of the problem in different areas.

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Sorting retail locations in a large urban city by using ELECTRE TRI-C and trapezoidal fuzzy numbers

Cited by 20 publications

References 33 publications

Classification model for bid/no‐bid decision in construction projects

Classification model for bid/no‐bid decision in construction projects

Site Selection Improvement of Retailers Based on Spatial Competition Strategy and a Double-Channel Convolutional Neural Network

İki amaçlı ters çok kriterli sıralama problemi için hedef programlama modeli

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