Drilling Path Optimization by Optimal Foraging Algorithm

Drilling path optimization (DPO) is a crucial issue in current manufacturing systems. In this paper, an optimization algorithm named the optimal foraging algorithm (OFA) is presented based on optimal foraging theory to solve the sequencing problem when many holes must be drilled. The objective of this study is to identify the optimal sequence of drilling operations using OFA to minimize the total processing cost. Since the drilling sequence optimization problem is considered a discrete optimization problem, five operators that can address the integer-encoding vector are built for OFA; thus, a discrete version of OFA is presented. The performance of OFA is evaluated against four other baseline algorithms in solving five real-world problems. The results, including the optimal solutions, the Kruskal–Wallis test, CPU time and the evolution curves, demonstrate that OFA improves the solution by minimizing nonproductive time. OFA is verified as a feasible method for solving DPO problems.

[1]  Guang-Yu Zhu,et al.  An improved Shuffled Frog-leaping Algorithm to optimize component pick-and-place sequencing optimization problem , 2014, Expert Syst. Appl..

[2]  Motaz Daadoo,et al.  Path Optimization For Computer Numerical Control-Printed Circuit Boards In Holes Drilling Process-Case Study , 2016 .

[3]  P. Taylor,et al.  Test of optimal sampling by foraging great tits , 1978 .

[4]  Ju-Jang Lee,et al.  Trajectory Optimization With Particle Swarm Optimization for Manipulator Motion Planning , 2015, IEEE Transactions on Industrial Informatics.

[5]  Graham H. Pyke,et al.  Optimal Foraging: A Selective Review of Theory and Tests , 1977, The Quarterly Review of Biology.

[6]  Oscar Castillo,et al.  Tool Path Optimization for Computer Numerical Control Machines based on Parallel ACO , 2022 .

[7]  Vincent Roberge,et al.  Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning , 2013, IEEE Transactions on Industrial Informatics.

[8]  Guang-Yu Zhu,et al.  A Genetic Optimization Approach to Optimize the Multi-head Surface Mount Placement Machine , 2008, ICIRA.

[9]  P. J. Pawar,et al.  Optimal sequence of hole-making operations using particle swarm optimization and modified shuffled frog leaping algorithm , 2016 .

[10]  Thomas Stützle,et al.  Ant colony optimization: artificial ants as a computational intelligence technique , 2006 .

[11]  MengChu Zhou,et al.  A Supervised Learning and Control Method to Improve Particle Swarm Optimization Algorithms , 2017, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[12]  Guang-Yu Zhu,et al.  Drilling path optimization by the particle swarm optimization algorithm with global convergence characteristics , 2008 .

[13]  S. G. Ponnambalam,et al.  Charged system search algorithm for robotic drill path optimization , 2015, 2015 International Conference on Advanced Mechatronic Systems (ICAMechS).

[14]  Joseph Y.-T. Leung,et al.  Worker assignment and production planning with learning and forgetting in manufacturing cells by hybrid bacteria foraging algorithm , 2016, Comput. Ind. Eng..

[15]  MengChu Zhou,et al.  Colored Traveling Salesman Problem , 2015, IEEE Transactions on Cybernetics.

[16]  Mohd Khairol Anuar Mohd Ariffin,et al.  Biogeography based optimization (BBO) algorithm to minimise non-productive time during hole-making process , 2015 .

[17]  J. J. Howard,et al.  Conditioning of scouts and recruits during foraging by a leaf-cutting ant, Atta colombica , 1996, Animal Behaviour.

[18]  Karim Hamza,et al.  Optimum drilling path planning for a rectangular matrix of holes using ant colony optimisation , 2011 .

[19]  Pei Li,et al.  A predator-prey particle swarm optimization approach to multiple UCAV air combat modeled by dynamic game theory , 2015, IEEE/CAA Journal of Automatica Sinica.

[20]  M. H. Misran,et al.  Firefly algorithm for path optimization in PCB holes drilling process , 2012, 2012 International Conference on Green and Ubiquitous Technology.

[21]  Guang-Yu Zhu,et al.  Optimal foraging algorithm for global optimization , 2017, Appl. Soft Comput..

[22]  Motaz Daadoo,et al.  Design and Implementation of Low Cost Computer Numerical Control-Printed Circuit Boards Drilling Machine , 2016 .

[23]  Xiaojun Liu,et al.  Process planning optimization of hole-making operations using ant colony algorithm , 2013 .

[24]  J. Alonso,et al.  Patch use in cranes: a field test of optimal foraging predictions , 1995, Animal Behaviour.

[25]  Ben Niu,et al.  Robot Path Planning Using Bacterial Foraging Algorithm , 2013 .

[26]  R. Cowie.  Optimal foraging in great tits (Parus major) , 1977, Nature.

[27]  T. P. Singh,et al.  Optimization of hole-making operations for injection mould using particle swarm optimization algorithm , 2015 .

[28]  Ruhul A. Sarker,et al.  An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems , 2013, IEEE Transactions on Industrial Informatics.

[29]  E. Charnov.  Optimal foraging, the marginal value theorem. , 1976, Theoretical population biology.

[30]  Karim Hamza,et al.  CNC Machining Path Planning Optimization for Circular Hole Patterns via a Hybrid Ant Colony Optimization Approach , 2014 .

[31]  Rodrigo Cogni,et al.  Recruitment Behavior During Foraging in the Neotropical Ant Gnamptogenys moelleri (Formicidae: Ponerinae): Does the Type of Food Matter? , 2004, Journal of Insect Behavior.

[32]  S. G. Ponnambalam,et al.  PCB Drill Path Optimization by Combinatorial Cuckoo Search Algorithm , 2014, TheScientificWorldJournal.

[33]  Godfrey C. Onwubolu,et al.  Optimal path for automated drilling operations by a new heuristic approach using particle swarm optimization , 2004 .

[34]  Michael P. Hassell,et al.  Foraging Strategies of Insects , 1978 .

[35]  Guang-Yu Zhu,et al.  Comparison and application of four versions of particle swarm optimization algorithms in the sequence optimization , 2011, Expert Syst. Appl..

[36]  Praveen Ranjan Srivastava.  A cooperative approach to optimize the Printed Circuit Boards drill routing process using Intelligent Water Drops , 2015, Comput. Electr. Eng..

[37]  P. J. Pawar,et al.  Tool path planning of hole-making operations in ejector plate of injection mould using modified shuffled frog leaping algorithm , 2016, J. Comput. Des. Eng..

[38]  J. T. Erichsen,et al.  Optimal prey selection in the great tit (Parus major) , 1977, Animal Behaviour.

[39]  Ming Liang,et al.  Optimization of hole-making operations: a tabu-search approach , 2000 .

[40]  Guang-Yu Zhu.  Drilling Path Optimization Based on Swarm Intelligent Algorithm , 2006, 2006 IEEE International Conference on Robotics and Biomimetics.