A hub location model in the sustainable supply chain considering customer segmentation

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ali Heidari ◽  
Din Mohammad Imani ◽  
Mohammad Khalilzadeh
Keyword(s):  
Supply Chain ◽  
Customer Segmentation ◽  
The Other ◽  
Supply Chain Network ◽  
Meaningful Difference ◽  
Sustainable Supply Chain ◽  
Hub Location ◽  
Nsga Ii ◽  
Content Type ◽  
Multi Objective

Purpose This paper aims to study the hub transportation system in supply chain networks which would contribute to reducing costs and environmental pollution, as well as to economic development and social responsibility. As not all customers tend to buy green products, several customer groups should be considered in terms of need type. Design/methodology/approach In this paper, a multi-objective hub location problem is developed for designing a sustainable supply chain network based on customer segmentation. It deals with the aspects of economic (cost reduction), environment (minimizing greenhouse gas emissions by the transport sector) and social responsibility (creating employment and community development). The epsilon-constraint method and augmented epsilon-constraint (AEC) method are used to solve the small-sized instances of this multi-objective problem. Due to the non-deterministic polynomial-time hardness of this problem, two non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective grey wolf optimizer (MOGWO) metaheuristic algorithms are also applied to tackle the large-sized instances of this problem. Findings As expected, the AEC method is able to provide better Pareto solutions according to the goals of the decision-makers. The Taguchi method was used for setting the parameters of the two metaheuristic algorithms. Considering the meaningful difference, the MOGWO algorithm outperforms the NSGA-II algorithm according to the rate of achievement to two objectives simultaneously and the spread of non-dominance solutions indexes. Regarding the other indexes, there was no meaningful difference between the performance of the two algorithms. Practical implications The model of this research provides a comprehensive solution for supply chain companies that want to achieve a rational balance between the three aspects of sustainability. Originality/value The importance of considering customer diversity on the one hand and saving on hub transportation costs, on the other hand, triggered us to propose a hub location model for designing a sustainable supply chain network based on customer segmentation.

scholarly journals Mathematical modeling for optimizing the blood supply chain network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amir Rahimzadeh Dehaghani ◽  
Muhammad Nawaz ◽  
Rohullah Sultanie ◽  
Tawiah Kwatekwei Quartey-Papafio
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Nsga Ii ◽  
Content Type ◽  
Supply Chain Networks ◽  
Multi Objective ◽  
Blood Supply Chain ◽  
The Cost

PurposeThis research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.Design/methodology/approachSince the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.FindingsA novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.Originality/valueBy building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.

A multi-objective optimization model for sustainable supply chain network with using genetic algorithm

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Reza Ehtesham Rasi ◽  
Mehdi Sohanian
Keyword(s):  
Supply Chain ◽  
Performance Indicators ◽  
Supplier Selection ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Sustainability Performance ◽  
Multi Objective ◽  
Sustainable Supplier Selection

Purpose The purpose of this paper is to design and optimize economic and environmental dimensions in a sustainable supply chain (SSC) network. This paper developed a mixed-integer linear programing (MILP) model to incorporate economical and environmental data for multi-objective optimization of the SSC network. Design/methodology/approach The overall objective of the present study is to use high-quality raw materials, at the same time the lowest amount of pollution emission and the highest profitability is achieved. The model in the problem is solved using two algorithms, namely, multi-objective genetic and multi-objective particle swarm. In this research, to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system. Findings The differences found between the genetic algorithms (GAs) and the MILP approaches can be explained by handling the constraints and their various logics. The solutions are contrasted with the original crisp model based on either MILP or GA, offering more robustness to the proposed approach. Practical implications The model is applied to Mega Motor company to optimize the sustainability performance of the supply chain i.e. economic (cost), social (time) and environmental (pollution of raw material). The research method has two approaches, namely, applied and mathematical modeling. Originality/value There is limited research designing and optimizing the SSC network. This study is among the first to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization of sustainability indexes of the system.

scholarly journals Developing a meat supply chain network design using a multi-objective possibilistic programming approach

2017 ◽  
Vol 119 (3) ◽  
pp. 690-706 ◽  
Author(s):  
Ahmed Mohammed ◽  
Qian Wang
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Meat Products ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Content Type ◽  
Multi Objective ◽  
Possibilistic Programming ◽  
Conflicting Objectives ◽  
Solution Methods

Purpose The purpose of this paper is to present a study in developing a cost-effective meat supply chain network design aiming to minimizing the total cost of transportation, the number of transportation vehicles and the delivery time of meat products. The developed model was also used for determining the optimum numbers and allocations of farms and abattoirs that need to be established and the optimal quantity flow of livestock from farms to abattoirs and meat products from abattoirs to retailers. Design/methodology/approach A multi-objective possibilistic programming model was formulated with a focus on minimizing the total cost of transportation, the number of transportation vehicles and the delivery time of meat products. Three sets of Pareto solutions were obtained using the three different solution methods. These methods are the LP-metrics method, the ɛ-constraint method and the weighted Tchebycheff method, respectively. The TOPSIS method was used for seeking a best Pareto solution as a trade-off decision when optimizing the three conflicting objectives. Findings A case study was also applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. The research concludes that the ɛ-constraint method has the superiority over the other two proposed methods as it offers a better solution outcome. Research limitations/implications This work addresses as interesting avenues for further research on exploring the delivery planner under different types of uncertainties and transportation means. Also, environmentalism has been increasingly becoming a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function. Practical implications The developed design methodology can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management. Originality/value The paper presents a methodology that can be used for tackling a multi-objective optimization problem of a meat supply chain network design. The proposed optimization method has the potential in solving the similar issue providing a compromising solution due to conflicting objectives in which each needs to be achieved toward an optimum outcome to survive in the competitive sector of food supply chains network.

scholarly journals The institutional logic of the sustainable organisation: the case of a chocolate supply network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kate McLoughlin ◽  
Joanne Meehan
Keyword(s):  
Supply Chain ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Structured Interviews ◽  
Content Type ◽  
Analyse Power ◽  
Stakeholder Network ◽  
New Research ◽  
Competitive Activities ◽  
Social Logics

PurposeThe purpose of this paper is to examine how, and by whom, institutional logics are determined in the action of sustainable organisation. The authors analyse a supply chain network structure to understand how multiple stakeholders' perceptions of sustainability emerge into a dominant logic and diffuse across an organisational field.Design/methodology/approachStakeholder network theory provides novel insights into emerging logics within a chocolate supply chain network. Semi-structured interviews with 35 decision-makers were analysed alongside 269 company documents to capture variations in emergent logics. The network was mapped to include 63 nodes and 366 edges to analyse power structure and mechanisms.FindingsThe socio-economic organising principles of sustainable organisation, their sources of power and their logics are identified. Economic and social logics are revealed, yet the dominance of economic logics creates risks to their coexistence. Logics are largely shaped in pre-competitive activities, and resource fitness to collaborative clusters limits access for non-commercial actors.Research limitations/implicationsPowerful firms use network structures and collaborative and concurrent inter-organisational relationships to define and diffuse their conceptualisation of sustainability and restrict competing logics.Originality/valueThis novel study contributes to sustainable supply chain management (SSCM) through presenting the socio-economic logic as a new conceptual framework to understand the action of sustainable organisation. The identification of sophisticated mechanisms of power and hegemonic control in the network opens new research agendas.

scholarly journals Sustainable Closed-Loop Mask Supply Chain Network Design Using Mathematical Modeling and a Fuzzy Multi-Objective Approach

2021 ◽  
Vol 13 (10) ◽  
pp. 5353
Author(s):  
Roy Setiawan ◽  
Rabia Salman ◽  
Bari G. Khairov ◽  
Valeriy V. Karpov ◽  
Svetlana Dmitrievna Danshina ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Social Responsibility ◽  
Fuzzy Optimization ◽  
Optimization Approach ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Multi Objective ◽  
Closed Chain ◽  
Total Profit

The outbreak of the deadly coronavirus, which is increasing the number of victims every day, has created many changes in today’s world. The use of various masks is the most important social tool against this virus. Given the importance of rapid and quality supply of masks in the current situation, it is necessary to study supply chain in particular. In this research, the design of a closed chain supply chain network for different types of masks is assessed. The studied supply chain includes suppliers, manufacturers, distributors, and retailers in the forward flow and collection centers, separate centers, recycling centers, and disposal centers in the backward flow. In this regard, a multi-objective mathematical model with the objectives of increasing the total profit and reducing the total environmental impact, and maximizing social responsibility is presented. The optimization of this mathematical model has been done using a fuzzy optimization approach in GAMS software. The results of this study show that maximizing the total profit and minimizing the environmental effects and maximizing social responsibility are in contrast to each other. In addition, the sensitivity analysis indicated that the customers’ demand can affect all aspects of the sustainable supply chain simultaneously.

Development of a Generic decision support system based on multi-Objective Optimisation for Green supply chain network design (GOOG)

2015 ◽  
Vol 26 (7) ◽  
pp. 1069-1084 ◽  
Author(s):  
Kanda Boonsothonsatit ◽  
Sami Kara ◽  
Suphunnika Ibbotson ◽  
Berman Kayis
Keyword(s):  
Supply Chain ◽  
Environmental Impact ◽  
Lead Time ◽  
Decision Makers ◽  
Green Supply Chain ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Content Type ◽  
Supply Chain Networks ◽  
Multi Objective

Purpose – The purpose of this paper is to propose a Generic decision support system which is based on multi-Objective Optimisation for Green supply chain network design (GOOG). It aims to support decision makers to design their supply chain networks using three key objectives: the lowest cost and environmental impact and the shortest lead time by incorporating the decision maker’s inputs. Design/methodology/approach – GOOG aims to suggest the best-fitted parameters for supply chain partners and manufacturing plant locations, their order allocations, and appropriate transportation modes and lot-sizes for cradle-to-gate. It integrates Fuzzy Goal Programming and weighted max-min operator for trade-off conflicting objectives and overcome fuzziness in specifying target values of individual objectives. It is solved using exact algorithm and validated using an industrial case study. Findings – The comparative analysis between actual, three single-objective, and multi-objective decisions showed that GOOG is capable to optimising three objectives namely cost, lead time, and environmental impact. Research limitations/implications – Further, GOOG requires validation for different supply chain scenarios and manufacturing strategic decisions. It can improve by including multi-echelon supply chain networks, entire life cycle and relevant environmental legislations. Practical implications – GOOG helps the decision makers to configuring those supply chain parameters whilst minimising those three objectives. Social implications – Companies can use GOOG as a tool to strategically select their supply chain that reduces their footprint and stop rebound effect which imposes significant impact to the society. Originality/value – GOOG includes overlooked in the previous study in order to achieve the objectives set. It is flexible for the decision makers to change the relative weightings of the inputs for those contradicting objectives.

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