Multi-objective supplier selection process: a simulation–optimization framework integrated with MCDM

Author(s):  
Nihan Kabadayi ◽  
Mohammad Dehghanimohammadabadi
2019 ◽  
Vol 11 (24) ◽  
pp. 7017 ◽  
Author(s):  
Marco A. Miranda-Ackerman ◽  
Catherine Azzaro-Pantel ◽  
Alberto A. Aguilar-Lasserre ◽  
Alfredo Bueno-Solano ◽  
Karina C. Arredondo-Soto

An important contribution to the environmental impact of agro-food supply chains is related to the agricultural technology and practices used in the fields during raw material production. This problem can be framed from the point of view of the Focal Company (FC) as a raw material Green Supplier Selection Problem (GSSP). This paper describes an extension of the GSSP methodology that integrates life cycle assessment, environmental collaborations, and contract farming in order to gain social and environmental benefits. In this approach, risk and gains are shared by both parties, as well as information related to agricultural practices through which the FC can optimize global performance by deciding which suppliers to contract, capacity and which practices to use at each supplying field in order to optimize economic performance and environmental impact. The FC provides the knowledge and technology needed by the supplier to reach these objectives via a contract farming scheme. A case study is developed in order to illustrate and a step-by-step methodology is described. A multi-objective optimization strategy based on Genetic Algorithms linked to a MCDM approach to the solution selection step is proposed. Scenarios of optimization of the selection process are studied to demonstrate the potential improvement gains in performance.


2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan

Procurement selection process in the acceptance of prospective students is an initial step undertaken by private universities to attract superior students. However, sometimes this selection process is just a procedural process that is commonly done by universities without grouping prospective students from superior students into a class that is superior compared to other classes. To process the selection results can be done using the help of computer systems, known as decision support systems. To produce a better, accurate and objective decision result is used a method that can be applied in decision support systems. Multi-Objective Optimization Method by Ratio Analysis (MOORA) is one of the MADM methods that can perform calculations on the value of criteria of attributes (prospective students) that helps decision makers to produce the right decision in the form of students who enter into the category of prospective students superior.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.


Author(s):  
Santiago D. Salas ◽  
Lizbeth Contreras-Salas ◽  
Pamela Rubio-Dueñas ◽  
Jorge Chebeir ◽  
José A. Romagnoli

2008 ◽  
Vol 27 (1) ◽  
pp. 49-62
Author(s):  
Sameer Kumar ◽  
John Bisson

With a growing global economy and competition and increased outsourcing, the supplier selection process has gained more focus and importance within many business enterprises for developing an integrated supply network. Analytic Hierarchy Process (AHP) has been identified as an ideal multi-objective decision support tool to assist firms in completing the supplier selection process as part of strengthening their procurement strategies. This paper involved secondary research methods to gain an understanding of AHP, its various applications, and exploration of how to incorporate non-traditional selection criteria such as environmental criterion into the process. AHP's application for optimal supplier selection to support integrated procurement process is illustrated through an example of a Medical Device Manufacturer (MDM), known for established supplier-customer partnerships and alliances. Major limitation in studying this example included data availability to complete a comprehensive AHP decision management model. However, it was found that AHP is a powerful, structured but flexible method of addressing the multi-criteria supplier selection decision that facilitates building an integrated supply chain.


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