Autonomous resource allocation of smart workshop for cloud machining orders

Abstract In order to realize the online allocation of collaborative processing resource of smart workshop in the context of cloud manufacturing, a multi-objective optimization model of workshop collaborative resources (MOM-WCR) was proposed. Considering the optimization objectives of processing time, processing cost, product qualification rate, and resource utilization, MOM-WCR was constructed. Based on the time sequence of workshop processing tasks, the workshop collaborative manufacturing resource was integrated in MOM-WCR. Fuzzy analytic hierarchy process (FAHP) was adopted to simplified the multi-objective problem into the single-objective problem. Then, the improved firefly algorithm which integrated the particle swarm algorithm (IFA-PSA) was used to solve MOM-WCR. Finally, a group of connecting rod processing experiments were used to verify the model proposed in this paper. The results show that the model is feasible in the application of workshop-level resource allocation in the context of cloud manufacturing, and the improved firefly algorithm shows good performance in solving the multi-objective resource allocation problem.

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Group influence based improved firefly algorithm for Design Space Exploration of Datapath resource allocation

Applied Intelligence ◽

10.1007/s10489-018-1371-3 ◽

2019 ◽

Vol 49 (6) ◽

pp. 2084-2100 ◽

Cited By ~ 1

Author(s):

Shathanaa Rajmohan ◽

Ramasubramanian Natarajan

Keyword(s):

Resource Allocation ◽

Design Space Exploration ◽

Firefly Algorithm ◽

Design Space ◽

Space Exploration ◽

Group Influence ◽

Improved Firefly Algorithm

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Multi-objective scheduling of cloud manufacturing resources through the integration of Cat swarm optimization and Firefly algorithm

Advances in Production Engineering & Management ◽

10.14743/apem2019.3.331 ◽

2019 ◽

Vol 14 (3) ◽

pp. 333-342 ◽

Cited By ~ 1

Author(s):

Y. Du ◽

J.L. Wang ◽

L. Lei

Keyword(s):

Firefly Algorithm ◽

Cloud Manufacturing ◽

Swarm Optimization ◽

Multi Objective ◽

Cat Swarm Optimization ◽

Manufacturing Resources

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A cooperative interference resource allocation method based on improved firefly algorithm

Defence Technology ◽

10.1016/j.dt.2020.07.006 ◽

2020 ◽

Author(s):

Huai-xi Xing ◽

Hua Wu ◽

You Chen ◽

Kun Wang

Keyword(s):

Resource Allocation ◽

Firefly Algorithm ◽

Allocation Method ◽

Improved Firefly Algorithm

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An improved firefly algorithm for collaborative manufacturing chain optimization problem

Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture ◽

10.1177/0954405418789981 ◽

2018 ◽

Vol 233 (6) ◽

pp. 1711-1722 ◽

Cited By ~ 3

Author(s):

Fuqiang Zhang ◽

Jizhuang Hui ◽

Bin Zhu ◽

Yunxin Guo

Keyword(s):

Resource Sharing ◽

Firefly Algorithm ◽

Solution Space ◽

Step Length ◽

Cloud Manufacturing ◽

Local Optimum ◽

Time Service ◽

Collaborative Manufacturing ◽

Improved Firefly Algorithm ◽

Manufacturing Chain

In order to conduct resource sharing and deployment in cloud manufacturing environment, a concept of collaborative manufacturing chain was proposed. Based on machining tasks with the sequential characteristics, the proposed model considering the criteria of service cost, service time, service quality and service utilization was constructed. Fuzzy analytical hierarchy process was adopted to add the above multi-criteria model to a single objective problem. Then, an improved firefly algorithm was used to solve a reasonable collaborative manufacturing chain scheme. Based on the discrete characteristics of the collaborative manufacturing chain, iterative position function was improved to make the solution space to be a discrete domain. Furthermore, particle swarm optimization was used to optimize the step length factor α, attraction degree β0 and light absorption coefficient γ so as to prevent the firefly algorithm from local optimum. Compared with the genetic algorithm, numerical result suggests that the improved firefly algorithm has more advantages in convergence speed and solving efficiency. It is expected that this study can provide a useful reference for the service composition of collaborative manufacturing chain.

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Fuzzy multi-objective location and routing problem

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-191654 ◽

2020 ◽

Vol 39 (3) ◽

pp. 3259-3273

Author(s):

Nasser Shahsavari-Pour ◽

Najmeh Bahram-Pour ◽

Mojde Kazemi

Keyword(s):

Firefly Algorithm ◽

High Reliability ◽

Research Area ◽

Nsga Ii ◽

Location Routing Problem ◽

Routing Problem ◽

Location Allocation ◽

Multi Objective ◽

Location Routing ◽

The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

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