NDLI: Multi task selection including part mix, tool allocation and process plans in CNC machining centers using new binary PSO

Content Provider	IEEE Xplore Digital Library
Author	Deep, K. Chauhan, P. Pant, M.
Copyright Year	2012
Description	Author affiliation: Dept. of Paper and Pulp Technology, Indian Institute of Technology Roorkee, Saharanpur-247001, Uttarakhand, India (Pant, M.) \|\| Dept. of Mathematics, Indian Institute of Technology Roorkee, 247667, Uttarakhand, India (Deep, K.; Chauhan, P.)
Abstract	This paper proposes a new binary PSO for solving multi-task selection problem concerning various issues such as Part mix, Tool allocation and Process plans in CNC machining centers. The mathematical formulation of considered selection problem emerges as highly constrained and 0–1, combinatorial optimization, which further belongs to the category of NP-hard problems. The proposed Binary PSO variant embeds a new sigmoid function namely “Gompertz function” as a binary number generator with an additional benefit of controlling its parameters so as to induce the combined effect of sigmoid as well as linear function. The corresponding variant is termed as “Gompertz Binary Particle Swarm Optimization (GBPSO)”. Before applying GBPSO for considered selection problem, the efficacy of proposed GBPSO is tested on a set of 0–1 Multi-dimensional knapsack problems and results are compared with standard binary PSO. Thereafter two test cases for considered optimal selection problem are solved and analyzed using GBPSO. The simulation results manifest the superiority of proposed variant over standard BPSO for solving benchmark problems and practical application as well.
Starting Page	1
Ending Page	8
File Size	938597
Page Count	8
File Format	PDF
ISBN	9781467315104
e-ISBN	9781467315098
e-ISBN	9781467315081
DOI	10.1109/CEC.2012.6256439
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-10
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mathematical model Equations Machining Standards Resource management Computer numerical control Benchmark testing combinatorial optimization process planning gompertz binary PSO
Content Type	Text
Resource Type	Article

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