An Optimal Resource Allocation Method for IIoT Network

Author(s):  
Pratik Goswami ◽  
Amrit Mukherjee ◽  
Pushpita Chaterjee ◽  
Lixia Yang
2010 ◽  
Vol 156-157 ◽  
pp. 1397-1403
Author(s):  
Jie Zhang ◽  
Zhi Jia Xu ◽  
Yuan Li

Subassembly has an important role in aircraft manufacturing. There are different shop orders at different periods, so subassembly system need to adjust production capacity through reallocation of resources. Based on graphic ant colony algorithm(GACA), an optimal resource allocation method was proposed on aircraft subassembly system. In the method, first, a Petri Net(PN) model was used to describe the logic of tasks and resources in system. Next, to support solving process of GACA, structure graph for ant routing was designed by PN model. Then according to features of aircraft subassembly, solving rules and procedures of GACA are discussed in detail, which can obtain an optimal resource allocation scheme by requirement of production capacity adjustment. In addition, an example on flaperon assembly was introduced and the result demonstrated the functionality of the method.


Algorithms ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 55
Author(s):  
Natsumi Oyamaguchi ◽  
Hiroyuki Tajima ◽  
Isamu Okada

Although exploring the principles of resource allocation is still important in many fields, little is known about appropriate methods for optimal resource allocation thus far. This is because we should consider many issues including opposing interests between many types of stakeholders. Here, we develop a new allocation method to resolve budget conflicts. To do so, we consider two points—minimizing assessment costs and satisfying allocational efficiency. In our method, an evaluator’s assessment is restricted to one’s own projects in one’s own department, and both an executive’s and mid-level executives’ assessments are also restricted to each representative project in each branch or department they manage. At the same time, we develop a calculation method to integrate such assessments by using a multi-branch tree structure, where a set of leaf nodes represents projects and a set of non-leaf nodes represents either directors or executives. Our method is incentive-compatible because no director has any incentive to make fallacious assessments.


Author(s):  
Pratik Goswami ◽  
Amrit Mukherjee ◽  
Moinak Maiti ◽  
Sumarga K. Sah Tyagi ◽  
Lixia Yang

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