scholarly journals Green Supplier Selection in the Agro-Food Industry with Contract Farming: A Multi-Objective Optimization Approach

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
Keyword(s):  
Environmental Impact ◽  
Supplier Selection ◽  
Selection Process ◽  
Environmental Benefits ◽  
Raw Material ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Contract Farming ◽  
Green Supplier Selection ◽  
Multi Objective

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.

Environmental impact minimization through material substitution: a multi-objective optimization approach

2004 ◽  
Vol 6 (8) ◽  
pp. 407 ◽  
Author(s):  
Andr� Hugo ◽  
C�line Ciumei ◽  
Andrew Buxton ◽  
Efstratios N. Pistikopoulos
Keyword(s):  
Environmental Impact ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Material Substitution ◽  
Multi Objective

A new weighted fuzzy programming model for supplier selection and order allocation in the food industry

2020 ◽  
Vol 15 (2) ◽  
pp. 381-406 ◽  
Author(s):  
Mohamad Amin Kaviani ◽  
Alireza Peykam ◽  
Sharfuddin Ahmed Khan ◽  
Nadjib Brahimi ◽  
Raziyeh Niknam
Keyword(s):  
Supplier Selection ◽  
Programming Model ◽  
Fuzzy Programming ◽  
Bottled Water ◽  
Optimization Approach ◽  
Water Production ◽  
Multi Objective Optimization ◽  
Order Allocation ◽  
Content Type ◽  
Multi Objective

Purpose The purpose of this paper is to develop a combined intuitionistic fuzzy analytic hierarchy process (IFAHP) and fuzzy multi-objective optimization approach to select suppliers and allocate the orders to them in the bottled water production context. Design/methodology/approach First, the primary weights of criteria associated with the supplier selection problem are calculated using the IFAHP technique. Then a fuzzy multi-objective optimization model is developed to allocate the appropriate amount of orders to each supplier. Findings The proposed methodology has been successfully implemented in the case of an Iranian food company in its bottled water factory. Results demonstrate our model is capable of practically handling the uncertainty in DMs’ preference that leads to effective and efficient supplier selection and order allocation decisions. Originality/value The authors develop a novel hybrid decision-making tool to tackle the uncertainty in decision-makers’ opinions with a demonstrated applicability and some promising outcomes in efficiently allocating the order quantity to suppliers in the area of bottled water production.

Student Admission Assesment using Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA)

2018 ◽  
Author(s):  
Rivalri Kristianto Hondro ◽  
Mesran Mesran ◽  
Andysah Putera Utama Siahaan
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Initial Step ◽  
Optimization Method ◽  
Ratio Analysis ◽  
Multi Objective Optimization ◽  
Prospective Students ◽  
Multi Objective

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.

scholarly journals Multi-Objective Multidisciplinary Design Optimization of a Robotic Fish System

2021 ◽  
Vol 9 (5) ◽  
pp. 478
Author(s):  
Hao Chen ◽  
Weikun Li ◽  
Weicheng Cui ◽  
Ping Yang ◽  
Linke Chen
Keyword(s):  
Design Optimization ◽  
Optimization Algorithm ◽  
Multidisciplinary Design Optimization ◽  
Robotic Fish ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Cfd Method ◽  
The Individual

Biomimetic robotic fish systems have attracted huge attention due to the advantages of flexibility and adaptability. They are typically complex systems that involve many disciplines. The design of robotic fish is a multi-objective multidisciplinary design optimization problem. However, the research on the design optimization of robotic fish is rare. In this paper, by combining an efficient multidisciplinary design optimization approach and a novel multi-objective optimization algorithm, a multi-objective multidisciplinary design optimization (MMDO) strategy named IDF-DMOEOA is proposed for the conceptual design of a three-joint robotic fish system. In the proposed IDF-DMOEOA strategy, the individual discipline feasible (IDF) approach is adopted. A novel multi-objective optimization algorithm, disruption-based multi-objective equilibrium optimization algorithm (DMOEOA), is utilized as the optimizer. The proposed MMDO strategy is first applied to the design optimization of the robotic fish system, and the robotic fish system is decomposed into four disciplines: hydrodynamics, propulsion, weight and equilibrium, and energy. The computational fluid dynamics (CFD) method is employed to predict the robotic fish’s hydrodynamics characteristics, and the backpropagation neural network is adopted as the surrogate model to reduce the CFD method’s computational expense. The optimization results indicate that the optimized robotic fish shows better performance than the initial design, proving the proposed IDF-DMOEOA strategy’s effectiveness.

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