scholarly journals Supply Chain Network Optimization by Considering Cost and Service Level Goals

2018 ◽  
Vol 6 (2) ◽  
pp. 60-72
Author(s):  
Mehmet Alegoz ◽  
Zehra Kamisli Ozturk
Keyword(s):  
Supply Chain ◽  
Network Optimization ◽  
Service Level ◽  
Supply Chain Network

scholarly journals Research on Intelligent Solution of Service Industry Supply Chain Network Optimization Based on Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Yixin Zhou ◽  
Zhen Guo
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Network Optimization ◽  
Service Industry ◽  
User Behavior ◽  
Service Level ◽  
Supply Chain Network ◽  
Supply Network ◽  
Running Time ◽  
Average Running Time

With the advent of the era of big data (BD), people’’s living standards and lifestyle have been greatly changed, and people’s requirements for the service level of the service industry are becoming higher and higher. The personalized needs of customers and private customization have become the hot issues of current research. The service industry is the core enterprise of the service industry. Optimizing the service industry supply network and reasonably allocating the tasks are the focus of the research at home and abroad. Under the background of BD, this paper takes the optimization of service industry supply network as the research object and studies the task allocation optimization of service industry supply network based on the analysis of customers’ personalized demand and user behavior. This paper optimizes the supply chain network of service industry based on genetic algorithm (GA), designs genetic operator, effectively avoids the premature of the algorithm, and improves the operation efficiency of the algorithm. The experimental results show that when m = 8 and n = 40, the average running time of the improved GA is 54.1 s. The network optimization running time of the algorithm used in this paper is very fast, and the stability is also higher.

scholarly journals Mathematical modelling of a decentralized multi-echelon supply chain network considering service level uncertainties

2018 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Raheleh Nourifar ◽  
Iraj Mahdavi ◽  
Nezam Mahdavi-Amiri ◽  
Mohammad Mahdi Paydar
Keyword(s):  
Supply Chain ◽  
Mathematical Modelling ◽  
Service Level ◽  
Supply Chain Network

scholarly journals An implementation of differential evolution algorithm for a single product and single period multi-echelon supply chain network model

2018 ◽  
Vol 1 (1) ◽  
pp. 1-14
Author(s):  
Ayda Emdadian ◽  
S. G. Ponnambalam ◽  
G. Kanagaraj
Keyword(s):  
Supply Chain ◽  
Differential Evolution ◽  
Network Optimization ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Value Added ◽  
Raw Material ◽  
Supply Chain Network ◽  
De Algorithm ◽  
Chain Problem

In this paper, five variants of Differential Evolution (DE) algorithms are proposed to solve the multi-echelon supply chain network optimization problem. Supply chain network composed of different stages which involves products, services and information flow between suppliers and customers, is a value-added chain that provides customers products with the quickest delivery and the most competitive price. Hence, there is a need to optimize the supply chain by finding the optimum configuration of the network in order to get a good compromise between several objectives. The supply chain problem utilized in this study is taken from literature which incorporates demand, capacity, raw-material availability, and sequencing constraints in order to maximize total profitability. The performance of DE variants has been investigated by solving three stage multi-echelon supply chain network optimization problems for twenty demand scenarios with each supply chain settings. The objective is to find the optimal alignment of procurement, production, and distribution while aiming towards maximizing profit. The results show that the proposed DE algorithm is able to achieve better performance on a set of supply chain problem with different scenarios those obtained by well-known classical GA and PSO.

Decision-Making Model of Network Optimization in Green Supply Chain

2014 ◽  
Vol 962-965 ◽  
pp. 2277-2282
Author(s):  
Cui Zhen Cao ◽  
Guo Huao Zhao
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Carbon Footprint ◽  
Network Optimization ◽  
Optimization Design ◽  
Service Level ◽  
Green Supply Chain ◽  
Low Carbon ◽  
Carbon Supply ◽  
Function Coefficient

Network optimization design of green supply chains not only decides the structure and value of supply chains themselves, but also has great impact on the healthy, low-carbon development of whole society’s logistics system and transportation system. Based on carbon footprint theory, this paper elaborates the influence of carbon emission on overall value of supply chain. Penalty function coefficient is introduced to covert a multi-objective optimization problem to a single objective one; three objects, namely, profitability, service level and environmental protection, are thus coordinated. A network optimization model is also developed so as to achieve a green, low carbon supply chain, and to balance cost, response time and carbon footprint. An example is offered as proof of this model’s effectiveness, serving as a supplementary solution to optimization design of green supply chain network.

Chemical supply chain network optimization

2008 ◽  
Vol 32 (11) ◽  
pp. 2481-2504 ◽  
Author(s):  
Jeff Ferrio ◽  
John Wassick
Keyword(s):  
Supply Chain ◽  
Network Optimization ◽  
Supply Chain Network
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