Supporting Demand Supply Network Optimization with Petri Nets

2007 ◽  
Vol 3 (4) ◽  
pp. 58-73 ◽  
Author(s):  
Teemu Tynjala
Keyword(s):  
Petri Nets ◽  
Network Optimization ◽  
Supply Network

Supporting Demand Supply Network Optimization with Petri Nets

2011 ◽  
pp. 2274-2287
Author(s):  
Teemu Tynjala
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Network Optimization ◽  
Business Groups ◽  
Product Structure ◽  
Reachability Analysis ◽  
Supply Network ◽  
Supply Networks ◽  
Supply Planning

The present study implements a generic methodology for describing and analyzing demand supply networks, that is, networks from a company’s suppliers to its customers. There can be many possible demand supply networks with different logistics costs for a product. Therefore, we introduce a Petri Net-based formalism, and a reachability analysis based algorithm that finds the optimum demand supply network for a user-specified product structure. The method has been implemented and is currently in production use inside all Nokia business groups. It is used in demand supply planning of both network elements and handsets. An example of the method’s application to a concrete Nokia product is included.

Supporting Demand Supply Network Optimization with Petri Nets

2011 ◽  
pp. 366-383
Author(s):  
Teemu Tynjala
Keyword(s):  
Petri Nets ◽  
Petri Net ◽  
Network Optimization ◽  
Business Groups ◽  
Product Structure ◽  
Reachability Analysis ◽  
Supply Network ◽  
Supply Networks ◽  
Supply Planning

The present study implements a generic methodology for describing and analyzing demand supply networks (i.e. networks from a company’s suppliers through to its customers). There can be many possible demand supply networks with different logistics costs for a product. Therefore, we introduced a Petri Net-based formalism, and a reachability analysis-based algorithm that finds the optimum demand supply network for a user-specified product structure. The method has been implemented and is currently in production use inside all Nokia business groups. It is used in demand supply planning of both network elements and handsets. An example of the method’s application to a concrete Nokia product is included.

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.

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