scholarly journals Designing a Fuzzy Strategic Integrated Multiechelon Agile Supply Chain Network

2013 ◽  
Vol 2013 ◽  
pp. 1-16 ◽  
Author(s):  
Morteza Abbasi ◽  
Reza Hosnavi ◽  
Mehrdad Mohammadi
Keyword(s):  
Supply Chain ◽  
Design Criterion ◽  
Strategic Decision ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Nsga Ii ◽  
Volume Flexibility ◽  
Simulating Annealing ◽  
Biobjective Optimization ◽  
The Cost

This paper integrates production, distribution and logistics activities at the strategic decision making level, where the objective is to design a multiechelon supply chain network considering agility as a key design criterion. A network with five echelons of supply chains including suppliers, plants, distribution centers, cross-docks, and customer zones is addressed in this paper. The problem has been mathematically formulated as a biobjective optimization model that aims to minimize the cost (fixed and variable) and maximize the plant flexibility and volume flexibility. A novel multiobjective parallel simulating annealing algorithm (MOPSA) is proposed to obtain the Pareto-optimal solutions of the problem. The performance of the proposed solution algorithm is compared with two well-known metaheuristics, namely, nondominated sorting genetic algorithm (NSGA-II) and Pareto archive evolution strategy (PAES). Computational results show that MOPSA outperforms the other metaheuristics.

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.

Robust Hazardous Materials Closed-Loop Supply Chain Network Design with Emergency Response Teams Location

2021 ◽  
pp. 036119812199207
Author(s):  
Nasrin Mohabbati-Kalejahi ◽  
Alexander Vinel
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Emergency Response ◽  
Closed Loop ◽  
Hazardous Materials ◽  
Risk Exposure ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Closed Loop Supply Chain

Hazardous materials (hazmat) storage and transportation pose threats to people’s safety and the environment, which creates a need for governments and local authorities to regulate such shipments. This paper proposes a novel mathematical model for what is termed the hazmat closed-loop supply chain network design problem. The model, which can be viewed as a way to combine several directions previously considered in the literature, includes two echelons in the forward direction (production and distribution centers), three echelons in the backward direction (collection, recovery, and disposal centers), and emergency response team positioning. The two objectives of minimizing the strategic, tactical, and operational costs as well as the risk exposure on road networks are considered in this model. Since the forward flow of hazmat is directly related to the reverse flow, and since hazmat accidents can occur at all stages of the lifecycle (storage, shipment, loading, and unloading, etc.), it is argued that such a unified framework is essential. A robust framework is also presented to hedge the optimization model in case of demand and return uncertainty. The performance of both models is evaluated based on a standard dataset from Albany, NY. Considering the trade-offs between cost and risk, the results demonstrate the design of efficient hazmat closed-loop supply chain networks where the risk exposure can be reduced significantly by employing the proposed models.

scholarly journals A Robust Fuzzy Optimization Model for Closed-Loop Supply Chain Networks Considering Sustainability

2019 ◽  
Vol 11 (20) ◽  
pp. 5726 ◽  
Author(s):  
Xin Zhang ◽  
Gang Zhao ◽  
Yingxiu Qi ◽  
Botang Li
Keyword(s):  
Supply Chain ◽  
Social Impact ◽  
Closed Loop ◽  
Cost Minimization ◽  
Fuzzy Optimization ◽  
Three Dimensions ◽  
Strategic Decision ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain ◽  
Solution Approach

Supply chain network design (SCND) is an important strategic decision determining the structure of each entity in the supply chain, which has an important impact on the long-term development of a company. An efficient and effective supply chain network is of vital importance for improving customer satisfaction, optimizing the allocation of resources, and increasing profitability. The environmental concerns and social responsibility awareness of the whole society have spurred researchers and managers to design sustainable supply chains (SSCs) integrating the economic, environmental, and social factors. In addition, the innate uncertainty of the SCND problem requires an integrated method to cope. In this regard, this study develops a multi-echelon multi-objective robust fuzzy closed-loop supply chain network (CLSCN) design model under uncertainty including all three dimensions of sustainability. This model considers the total cost minimization, carbon caps, and social impact maximization concurrently to realize supply chain sustainability, and is able to make a balance between the conflicting multiple objectives. Meanwhile, the uncertainty of the parameters is divided into two categories and addressed with two approaches: the first category is missed working days related to social impact, which is solved by the fuzzy membership theory; the second category is the demand and remanufacturing rate, which is settled by a robust optimization method. To validate the ability and applicability of the model and solution approach, a numerical example is conducted and solved using ILOG CPLEX. The result shows that the supply chain network structure and the value of the optimization objectives will change when considering sustainability and different degrees of uncertainty. This will enable supply chain managers to reduce the environmental impact and enhance the social benefits of their supply chain activities, and design a more stable supply chain to better cope with the influence of uncertainty.

scholarly journals Study on Benefit Coordination of Supply Chain Network Based on Green Development

2019 ◽  
Vol 16 (8) ◽  
pp. 1458
Author(s):  
Gao ◽  
Wang
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Cost Sharing ◽  
Main Body ◽  
Supply Chain Network ◽  
Logistics Network ◽  
Coordination Model ◽  
Green Development ◽  
Green Index ◽  
The Cost

Based on Stackelberg's master–slave game theory and green index decision-making conditions, this paper studies the benefit coordination of a supply chain network composed of a business flow network and logistics network, discusses the decision-making behavior of the main body of the supply chain network under the performance of green contracts or speculative behavior, respectively, and further constructs the supply chain network collaborative benefit coordination model under the guidance of a manufacturer considering a green development index. The supply chain network interest coordination model analyzes the relationship between the dominant manufacturer behavior and the supply chain network green index and network profit. The results show that fulfilling green contracts helps improve the profitability and sustainability of supply chain networks. A counter-intuitive but interesting result is that the dominant manufacturers increase the cost-sharing ratio or penalties of the logistics network, which will reduce the profit level and green index of the logistics network, and increase the cost-sharing ratio or punishment of the suppliers. Strength will increase the profitability and green index of the logistics network. Finally, we validate the relevant conclusions of the model through numerical simulation analysis.

scholarly journals Integrated Location-Production-Distribution Planning in a Multiproducts Supply Chain Network Design Model

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Vincent F. Yu ◽  
Nur Mayke Eka Normasari ◽  
Huynh Trung Luong
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Network Design ◽  
Optimal Solution ◽  
Medium Size ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Distribution Planning ◽  
Production And Distribution

This paper proposes integrated location, production, and distribution planning for the supply chain network design which focuses on selecting the appropriate locations to build a new plant and distribution center while deciding the production and distribution of the product. We examine a multiechelon supply chain that includes suppliers, plants, and distribution centers and develop a mathematical model that aims at minimizing the total cost of the supply chain. In particular, the mathematical model considers the decision of how many plants and distribution centers to open and where to open them, as well as the allocation in each echelon. The LINGO software is used to solve the model for some problem cases. The study conducts various numerical experiments to illustrate the applicability of the developed model. Results show that, in small and medium size of problem, the optimal solution can be found using this solver. Sensitivity analysis is also conducted and shows that customer demand parameter has the greatest impact on the optimal solution.

Outbound supply chain network design with mode selection, lead times and capacitated vehicle distribution centers

2005 ◽  
Vol 165 (1) ◽  
pp. 182-206 ◽  
Author(s):  
Erdem Eskigun ◽  
Reha Uzsoy ◽  
Paul V. Preckel ◽  
George Beaujon ◽  
Subramanian Krishnan ◽  
...  
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Mode Selection ◽  
Lead Times ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Capacitated Vehicle

scholarly journals Combined Use of Mathematical Optimization and Design of Experiments for the Maximization of Profit in a Four-Echelon Supply Chain

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-25 ◽  
Author(s):  
Daniel Arturo Olivares Vera ◽  
Elias Olivares-Benitez ◽  
Eleazar Puente Rivera ◽  
Mónica López-Campos ◽  
Pablo A. Miranda
Keyword(s):  
Supply Chain ◽  
Design Of Experiments ◽  
Mathematical Optimization ◽  
Fractional Factorial ◽  
Mixed Integer ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Cost Component ◽  
Allocation Model

This paper develops a location-allocation model to optimize a four-echelon supply chain network, addressing manufacturing and distribution centers location, supplier selection and flow allocation for raw materials from suppliers to manufacturers, and finished products for end customers, while searching for system profit maximization. A fractional-factorial design of experiments is performed to analyze the effects of capacity, quality, delivery time, and interest rate on profit and system performance. The model is formulated as a mixed-integer linear programming problem and solved by using well-known commercial software. The usage of factorial experiments combined with mathematical optimization is a novel approach to address supply chain network design problems. The application of the proposed model to a case study shows that this combination of techniques yields satisfying results in terms of both its behavior and the obtained managerial insights. An ANOVA analysis is executed to quantify the effects of each factor and their interactions. In the analyzed case study, the transportation cost is the most relevant cost component, and the most relevant opportunity for profit improvement is found in the factor of quality. The proposed combination of methods can be adapted to different problems and industries.

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.

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