- Landscape Aware Algorithm Configuration

Cody Dennis, Beatrice M. Ombuki-Berman and Andries P Engelbrecht

- Massive Dimensions Reduction and Hybridization with Metaheuristics in Deep Learning

Rasa Khosrowshahli, Shahryar Rahnamayan and Beatrice Ombuki-Berman - Integrating Transformers and Many-Objective Optimization for Cancer Drug Design

Nicholas Aksamit, Jinqiang Hou, Yifeng Li and Beatrice Ombuki-Berman -
A Comparative Study of Evolutionary Algorithms and Particle Swarm Optimization Approaches for Constrained Multi-Objective Optimization Problems

Alanna McNulty, Beatrice M. Ombuki-Berman and Andries P. Engelbrecht

- A Memetic Algorithm for Large-Scale Real-World Vehicle Routing Problems with Simultaneous Pickup and Delivery
with Time Windows.

Ethan Gibbons and Beatrice M. Ombuki-Berman

*15th, Metaheuristics International Conference*, MIC 2024, Lorient, France, June 2024

*To Appear As Springer Lecture Notes in Computer Science* -
Stochastic Grouping and Subspace-Based Initialization in Decomposition and Merging Cooperative Particle Swarm Optimization for Large-Scale
Optimization Problems

Zachary McGovarin, Andries Engelbrecht and Beatrice M. Ombuki-Berman

*37th Canadian AI Conference*, Guelph, May 2024 -
Genetic Algorithm and Loading Strategy for the Dynamic Vehicle Routing Problem with Simultaneous Pickup and Delivery

Ethan Gibbons, Alex Bailey and Beatrice M. Ombuki-Berman

*37th Canadian AI Conference*, Guelph, May 2024 - Decomposition and Merging Co-operative Particle Swarm Optimization with Random Grouping for Large-Scale Optimization

Alanna McNulty, B. M. Ombuki-Berman and A. P. Engelbrecht

*Swarm Intelligence*, Springer, Nov. 2023. - A Framework for Meta-heuristic Parameter Performance Prediction Using Fitness Landscape Analysis and Machine Learning

L. McDevitt, K. R. Harrison and B. M. Ombuki-Berman

*2023 IEEE CEC Congress of Evolutionary Computation*, CEC 2023, Accepted, Chicago, USA, July 2023 - A Comparative Study of Multi-Guide Particle Swarm Optimization Topologies in Dynamic Multi-Objective Environments

A. McNulty and B. M. Ombuki-Berman

*2023 IEEE CEC Congress of Evolutionary Computation*, CEC 2023, Accepted, Chicago, USA, July 2023. - Identification and Classification of JMH Microbenchmark States Using Time Series Analysis

T. Wallace, B. M. Ombuki-Berman and N. Ezzati-Jivan

*14th ACM/SPEC International Conference on Performance Engineering*, ICPE'23, pp. 101-105, Coimbra, Portugal, April 2023. - Cooperative Coevolutionary Multi-guide Particle Swarm Optimization Algorithm for Large-Scale Multi-Objective Optimization

Amirali Madani, Andries .P Engelbrech and Beatrice M. Ombuki-Berman

*Swarm and Evolutionary Computation*, v.78, Feb. 2023. - A Particle Swarm Optimization Decomposition Strategy for Large Scale Global Optimization

Liam McDevitt, Beatrice M. Ombuki-Berman and Andries P Engelbrecht

*IEEE Symposium Series on Computation Intelligence*, IEEE SSCI 2022, Singapore, pp. 1574-1581, December 2022. - Cooperative Particle Swarm Optimization Decomposition Methods for Large-scale Optimization

Mitchell D. Clark, Beatrice M. Ombuki-Berman, Nicholas Aksamit and Andries .P Engelbrecht

*IEEE Symposium Series on Computation Intelligencee*, IEEE SSCI 2022, Singapore, pp. 1582-1591, December 2022. - Decomposition and Merging Co-operative Particle Swarm Optimization with Random Grouping

Alanna McNulty, B. M. Ombuki-Berman and A. P. Engelbrecht

*13th International Conference on Swarm Intelligence*, ANTS 2022, Malaga, Spain, pp.117–129, November, 2022. - Cooperative Multi-objective Particle Swarm Optimization and Differential Evolution for Drug Design

Nicholas Aksamit, B. M. Ombuki-Berman and Yifeng Li

*19th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biologye*, IEEE CIBCB 2022, Extended 2-page abstract, Ottawa, Canada, Augus, 2022. - Dynamic Multi-objective Optimisation Using Multi-guide Particle Swarm Optimisation

Jocko Pawel, B. M. Ombuki-Berman and A. P. Engelbrecht

*at World Congress on Computational Intelligence,*, IEEE CEC 2022, Padova, Italy, Accepted, July, 2022.

IEEE 2022 IEEE CEC Congress of Evolutionary Computation - Multi-guide Particle Swarm Optimization Archive Management Strategies for Dynamic Optimization Problems

Jocko Pawel, Beatrice M. Ombuki-Berman and Andries P Engelbrecht

*Swarm Intelligence*(Springer), 16:143-168, February, 2022. - An analysis of the impact of subsampling on the neural network error surface

Cody Dennis, Andries Engelbrecht and Beatrice M. Ombuki-Berman

*Neurocomputing*(Elsevier), 466:252-264, November 2021. - Visualizing and characterizing the parameter configuration landscape of Particle Swarm Optimization using physical landform
classification

K. R. Harrison, B. M. Ombuki-Berman and A. P. Engelbrecht

*2021 IEEE CEC Congress of Evolutionary Computation*, CEC 2021, pp.2299-2306, Krakow, Poland, June 2021. - Decision Space Scalability Analysis of Multi-objective Particle Swarm Optimization Algorithms

A. Madani, B. M. Ombuki-Berman and A.P Engelbrecht

*2021 IEEE CEC Congress of Evolutionary Computation*, CEC 2021, pp.2179-2186, Krakow, Poland, June 2021. - Predicting particle swarm control parameters from fitness landscape characteristics

C. Dennis, B. M. Ombuki-Berman and A.P Engelbrecht

*2021 IEEE CEC Congress of Evolutionary Computation*, CEC 2021, pp.2289-2298, Krakow, Poland, June 2021.T. Crane, A. P. Engelbrecht and B. M. Ombuki-Berman

*12th International Conference on Swarm Intelligence (ICSI’21)*, Qingdao, China, to Appear in Springer-Nature Lecture Notes (LNCS) in Computer Scienc, Accepted MArch 2021. - Visualizing and characterizing the parameter configuration landscape of differential evolution using physical landform classification

K. R. Harrison, B. M. Ombuki-Berman and A. P. Engelbrecht

*2020 IEEE Symposium Series on Computational Intelligence*, IEEE, Canberra, Australia, pp.2437- 2444, Devember 2020. - NichePSO and the Merging Subswarm Problem

T. Crane, B. Ombuki-Berman and A. Engelbrecht

*2020 7th International Conference on Soft Computing & Machine Intelligence (ISCMI)*, Stockholm, Sweden,pp. 17-22, November 2020. - A Hybrid Approach to Network Robustness optimization using edge rewiring and edge Addition

J. Paterson and B. M. Ombuki-Berman*2020 IEEE International Conference on Systems, Man and Cybernetics*, IEEE SMC 2020, Toronto, pp. 4051- 4057, October 2020. - Swarm Based Algorithms for Neural Network Training

R. McLean, B. M. Ombuki-Berman and A.P Engelbrecht

*2020 IEEE International Conference on Systems, Man and Cybernetics*IEEE SMC 2020, Toronto, pp. 2585- 2592, October 2020, - An Analysis of Activation Function Saturation in Particle Swarm Optimization Trained Neural Networks Training

C. Dennis, A.P Engelbrecht and B. M. Ombuki-Berman

*Neural Processing Letters*, 52:1123-1153, September 2020. - Juan C. Burguillo: Self-organizing coalitions for managing complexity

Ombuki-Berman B.

*Genetic Programming and Evolvable Machines*(2020).

https://doi.org/10.1007/s10710-019-09372-2. Invited Book Review. - Random Regrouping and Factorization in Cooperative Particle Swarm
Optimization Based Large-Scale Neural Network Training

Cody Dennis, Beatrice M. Ombuki-Berman, and Andries P. Engelbrecht

*Neural Processing Letters*51(1), 759-796, 2020 , DOI 10.1007/s11063-019-10112-x -
A Parameter-Free Particle Swarm Optimization Algorithm using Performance
Classifiers

K.R.Harrison,B.M.Ombuki-Berman,and A.P.Engelbrecht

*Information Sciences*vol. 503, pp.381- 400, 2019. - The Parameter Configuration Landscape: A Case Study on Particle Swarm Optimization

K. R. Harrison, B. M. Ombuki-Berman, and A. P. Engelbrecht

*IEEE Congress on Evolutionary Computation (CEC 2019)*, pp. 808-814, 2019. - An Analysis of Control Parameter Importance in the Particle Swarm Optimization Algorithm

K.R.Harrison, B.M.Ombuki-Berman, and A.P.Engelbrecht

*In Advances in Swarm Intelligence,*, Y. Tan, Y. Shi, and B. Niu, Eds., Springer International Publishing, pp. pp. 93-105, 2019. - Optimizing Scale-Free Network Robustness with the Great Deluge Algorithm

J. Paterson and B. M. Ombuki-Berman

*The 31st International Conference on Industrial, Engineering & Other applications of Applied Intelligent Systems,*, Accepted, Montreal, June 2018.

IEA-AIE 2018 - Optimal Parameter Regions and the Time Dependence
of Control Parameter Values

for the Particle Swarm Optimization Algorithm

K.R Harrison, A.P Engelbrecht and B. M. Ombuki-Berman

*Swarm and Evolutionary Computation 41*, pp. 20-35, Elsevier, 2018. - Merging and Decomposition Variants of Cooperative Particle
Swarm Optimization:

New Algorithms for Large Scale Optimization Problems

Jay Douglas, Andries Engelbrecht and Beatrice Ombuki-Berman

*2018 2nd International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence*,

ISMSI2018, Accepted Phuket, Thailand, March 2018. - Gaussian-Valued Particle Swarm Optimization

K.R Harrison, B. M Ombuki-Berman and A.P Engelbrecht

in*Swarm Intelligence*, M. Dorigo, M. Birattari, C. Blum, A.L Christensen, A. Reina, and V. Trianni, Eds, Springer International Publishing, pp. 368- 377, 2018. - A Bi-Objective Critical Node Detection Problem

M. Venntresca, K. Harrison, and B.M. Ombuki-Berman

*European Journal of Operational Research*, 254(3):895-908, March 2018. - A Scalability Study of Many-Objective Optimization Algorithms

Justin Maltese, Beatrice M. Ombuki-Berman, and Andries P. Engelbrecht.

*IEEE Transactions on Evolutionary Computation*, pp: 79-96, February 2018. - Self-Adaptive Particle Swarm Optimization: A review and Analysis of Convergence

K.R Harrison, A.P Engelbrecht, and B. M Ombuki-Berman

*Swarm Intelligence*, 12(3) pp. 187–226, Springer, 2018. - An Age Layered Population Structure Genetic Algorithm for Multi-Depot Vehicle
Routing

Audrey Opoku-Amankwaar and B.M Ombuki

*2017 IEEE Symposium Series on Computation Intelligence*, pp.3403-3410, Hawai, November 2017. - Optimal Parameter Regions for Particle Swarm Optimization Algorithms

Kyle R. Harrison Beatrice M. Ombuki-Berman, and Andries P. Engelbrecht.

*IEEE Congress on Evolutionary Computation, CEC 2017*pp. 349-356, Spain, June 2017. - Inertia weight control strategies for particle swarm optimization

Kyle R. Harrison, Andries P. Engelbrecht and Beatrice M. Ombuki-Berman.

*Swarm Intelligence*, Volume 10, Issue 4, pp:267-305, December 2016. - A Meta-Analysis of Centrality Measures for Comparing and Generating Complex Network Models.

Kyle Robert Harrison, Mario Ventresca, and Beatrice M. Ombuki-Berman.

*Journal of Computational Science,*Elsevier, 17(1):205-215, November 2016. - Automatic Inference of Graph
Models for Directed Complex Networks using Genetic Programming

Michael Medland, Kyle Robert Harrison, and Beatrice M. Ombuki-Berman.

*IEEE Congress on Evolutionary Computation,*IEEE CEC 2016, pp. 2337-2344, Vancouver, July 2016. - Pareto-Based Many-Objective Optimization using
Knee Points

Justin Maltese, Beatrice M. Ombuki-Berman, and Andries P. Engelbrecht.

*IEEE Congress on Evolutionary Computation,*IEEE CEC 2016, pp. pp. 3678 - 3686, Vancouver, July 2016. - The Sad State of Self-Adaptive Particle Swarm Optimizers

Kyle R. Harrison, Andries P. Engelbrecht and Beatrice M. Ombuki-Berman.

*IEEE Congress on Evolutionary Computation,*IEEE CEC 2016, pp. 431-439, Vancouver, July 2016. - A Radius-Free Quantum Particle Swarm Optimization Technique for Dynamic Optimization Problems

K.R. Harrison, B.M Ommbuki-Berman, and Andries P. Engelbrecht.

*IEEE Congress on Evolutionary Computation,*IEEE CEC 2016, pp. 578-585, Vancouver, July 2016. - High-Dimensional Multi-objective Optimization Using Co-operative Vector-Evaluated
Particle Swarm Optimization With Random Variable Grouping.

Justin Maltese, Andries P. Engelbrecht and Beatrice M. Ombuki.

*2015 IEEE Symposium on Swarm Intelligence.*1302 - 1309, Cape Town, SA, December 2015. - The Effect of Probability Distributions on the Performance of Quantum Particle Swarm
Optimization for Solving Dynamic Optimization Problems.

Kyle Harrison, Beatrice Ombuki-Berman and Andries P. Engelbrecht.

*2015 IEEE Symposium on Swarm Intelligence.*242 - 250, Cape Town, SA, December 2015. - Cooperative Vector Evaluated Particle Swarm Optimization for Multi-objective Optimization.

Justin Maltese, Beatrice Ombuki-Berman and Andries P. Engelbrecht.

*2015 IEEE Symposium on Swarm Intelligence.*pp. 1294 - 1301, Cape Town, SA, December 2015. - A GA Approach for finding decision rules based on bireducts

Oleg Rybik, Ivo Duntsch and Beatrice Ombuki-Berman

Extended abstract, RST 2015, Warsaw, Poland, June 2015. - Evaluating Landscape Characteristics of Dynamic Benchmark Functions.

Ron Bond, Andries Engelbrecht and Beatrice Ombuki-Berman.*2015 IEEE Congress on Evolutionary Computation, CEC 2015,*(CEC 2015), pp. 187 - 195, Sendai, Japan, May 2015. - Vector-Evaluated Particle Swarm Optimization with Local Search.

Derek Dibblee, Justin Maltese, Beatrice Ombuki-Berman and Andries Engelbrecht.*2015 IEEE Congress on Evolutionary Computation, CEC 2015,*(CEC 2015), pp. 1343 - 1350, Sendai, Japan, May 2015. - Investigating Fitness Measures for the Automatic Construction of Graph Models.

Kyle Harrison, Mario Ventresca and Beatrice Ombuki-Berman.*Lecture Notes in Computer Science*, 9028 pp:189-200, 2015

*18th European Conference on the Applications of Evolutionary Computation ,*EvoCOMPLEX, Copenhagen, Denmark, April, 2015. - An Experimental Evaluation of Multi-Objective
Evolutionary Algorithms for Detecting Critical
Nodes in Complex Networks.

Mario Ventresca, Kyle Harrison, and Beatrice Ombuki-Berman.*Lecture Notes in Computer Science*, 9028 pp:164-176,2015.

*18th European Conference on the Applications of Evolutionary Computation ,*EvoCOMPLEX, Copenhagen, Denmark, April 2015. - Demonstrating the Power of Object-Oriented Genetic Programming via the Inference of Graph Models for
Complex Networks.

Michael Medland, Kyle Harrison and Beatrice Ombuki-Berman.

*6th World Congress on Nature and Biologically Inspired Computing,*(NABIC 2014), pp. pp. 305-311, Portugal, August 2014. - Dynamic Multi-Objective Optimization using Charged Vector Evaluated Particle Swarm Optimization.

Kyle Harrison, Beatrice Ombuki-Berman and Andries Engelbrecht.

*IEEE Conference on Evolutionary Computation,*(CEC 2014), pp. 1929 - 1936, Beijing, China, July 2014. - Incorporating Expert Knowledge in Object-Oriented Genetic Programming.

Michael Medland, Kyle Harrison and Beatrice Ombuki-Berman.

*Genetic and Evolutionary Computation Conference,*GECCO 2014, pp. 145 - 146, Vancouver, July 2014. - Genetic Programming for the Automatic Inference of Graph Models for Complex Networks.

A. Bailey, M. Ventresca and B.Ombuki-Berman.

*IEEE Transactions on Evolutionary Computation*, 18(3):405-419, June, 2014. - Automatic Inference of Hierarchical Graph Models using Genetic Programming
with an Application to Cortical Networks.

A. Bailey, B. Ombuki-Berman and M. Ventresca.*Genetic and Evolutionary Computation Conference, GECCO 2013*, pp.893-900, Amsterdam, July 2013. - A Scalability Study of Multi-Objective Particle Swarm Optimizers.

K. Harrison, A.P. Engelbrecht and B.Ombuki-Berman

*2013 IEEE Conference on Evolutionary Computation (CEC 2013),*, pp.189-197, Mexico, June 2013. - Cooperative Particle Swarm Optimization for Dynamic Environments.

N. Unger, B. Ombuki-Berman and A. P. Engelbrecht.

*2013 IEEE Symposium on Swarm Intelligence.*pp. 172-179, Singapore, April 2013. - Discrete Particle Swarm Optimization for the Single Allocation Hub Location Problem.

A. Bailey, B. Ombuki-Berman and S. Aseibola

*2013 IEEE Symposium Series on Computational Intelligence.*pp.92-98, Singapore, April 2013. -
Predicting GAs Performance on the Vehicle Routing Problem Using Information Theoretic Landscape Measures.
,

M. Ventresca, B. Ombuki-Berman and A. Runka.

*13th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP),*pp. 214-225, Vienna, Austria, April 2013. -
Knowledge Transfer Strategies for Vector Evaluated Particle Swarm Optimization.

K. Harrison, B. Ombuki-Berman and A. Engelbrecht.

*Evolutionary Multi-Criterion Optimization, Lecture Notes in Computer Science Volume 7811, 2013, pp. 171-184*, March 2013. -
Automatic Generation of Graph Models for Complex Networks using Genetic Programming,

A. Bailey, M. Ventresca, and B. Ombuki-Berman.

*Genetic and Evolutionary Computation Conference, GECCO 2012*, pp.711-718, Philadelphia, USA, July 2012. - Using Summed Ranks and Pareto Ranking to Design Outpatient Schedules,

Ombuki-Berman, B., Klassen, K. and Harrington, A.

*Canadian Operational Research Society Conference*, Niagara Falls, Ontario, June, 2012. - Developing Appointment Schedules with Genetic Algorithms,

Klassen, K., Ombuki-Berman, B. and Harrington, A..

*Production and Operations Management Society Conference*, Chicago, Illinois, April, 2012. - An Efficient Genetic Algorithm for the Uncapacitated Single Allocation Hub Location Problem.

M. Naeem and B. Ombuki-Berman.

*2010 IEEE Conference on Evolutionary Computation (CEC 2010)*, pp.941-948, Barcelona, Spain, July 18-23, 2010. -
A Search Space Analysis for the Waste Collection Vehicle Routing Problem with Time Windows.

A. Runka, B. Ombuki-Berman, M. Ventresca.

*Refereed Poster Paper, GECCO 2009*, Montreal, July 2009. - Using genetic algorithms for multi-depot vehicle routing.

B. Ombuki-Berman and F. Hanshar.

F.B. Pereira, J.Tavares (Eds.)

in,*Bio-Inspired Algorithms for the Vehicle Routing Problem,*Springer-Studies in Computational Intelligence, v.161, pp:77-99, 2009. - Genetic Algorithm Cryptanalysis of Substitution Permutation Network.

J. Brown, S. Houghten and B. Ombuki-Berman.

*IEEE Symposium on Computational Intelligence in Cyber Security .*pp:115-121, Nashville, Tennessee, USA, 2009. -
Particle swarm optimization for the Design of Two Connected Networks with Bounded Rings.

E. B. Foxwell and B. Ombuki-Berman.

*Journal of High Performance System Architecture*, Vol. 1. no.4, pp. 220-230, 2008.

(Initial results presented at*Workshop on Parallel Architectures and Bioinspired Algorithms,*pp:21-29, Toronto, Oct. 2008) - Dynamic Vehicle Routing
using Genetic Algorithm.

F.T. Hanshar and B. Ombuki-Berman.

*Applied Intelligence,*27(1):89-99, August 2007. - Waste collection
vehicle routing problem with time windows using multi-objective genetic algorithms .

B. Ombuki-Berman, A. Runka and F. Hanshar.

*Computational Intelligence (CI 2007)*, Banff, Canada, July 2007. - Search Difficulty of Two-Connected
Ring-based Topological Network Designs.

B. Ombuki-Berman, M. Ventresca.

*IEEE Symposium on Foundations of Computational Intelligence (FOCI),*pp:267-274, Honolulu, USA, April 2007. - Epistasis in Multi-Objective
Evolutionary Recurrent Neuro-Controllers.

M. Ventresca, B. Ombuki-Berman.*IEEE Symposium on Artificial Life (CI-ALIFE),*pp:77-84, Honolulu, USA, April 2007. - Search Space Analysis of Recurrent Spiking and Continuous-time Neural
Networks.

M. Ventresca and B. M. Ombuki.

*IEEE International Joint Conference on Neural Networks (IJCNN),*pp:8947-8954, Vancouver, Canada, July 2006. - Multi-Objective Genetic Algorithms for Vehicle Routing
Problems with

Time Windows. B. Ombuki, Brian J. Ross and F. Hanshar.

*Applied Intelligence,*24(1):17-30, February 2006. - A Genetic Algorithm for the
Design of Two Connected Networks with Bounded

Rings". M. Ventresca and B. Ombuki.*Computational Intelligence and Applications,*Special Issue on Nature-Inspired Approaches to Networks and Telecommunications, 5(2):267-281, November 2005. - Ant Colony Optimization for Job Shop
Scheduling Problem.

M. Ventresca and B. M. Ombuki.

Proceedings of 8th*IASTED Intl. Conf. On Artificial Intelligence and Soft Computing,*(ASC 2004), CDROM.

451-152. Marbella,Spain, ed. A.P.del Pobil, ACTA Press, September 2004. - A Genetic Algorithm for
the Design of Two Connected Networks with Bounded

Rings". M. Ventresca and B. Ombuki.

Workshop on Nature Inspired Approaches to Networks and Telecommunications

workshop at the*8th International Conference on Parallel Problem Solving from Nature (PPSN VIII)*,

Birmingham, UK, on 18-22 September, 2004. -
Local Search Genetic Algorithm for the Job Shop Scheduling Problem.

B. Ombuki and M. Ventresca.

*Applied Intelligence*21 (1): 99-109, July 2004. - Meta-heuristics for the Job Shop Scheduling Problem.
M. Ventresca and B. Ombuki.
*Proceedings of Late*(GECCO-2003) pp.303-306,

Breaking Papers, Genetic and Evolutionary Computation Conference M. Ventresca and B.M. Ombuki.

Chicago, 2003. -
A Hybrid Search Based on Genetic Algorithms and Tabu Search for

Vehicle Routing. B.Ombuki, M. Nakamura & M.Osamu.

*6th International Conference on Artificial Intelligence and Soft*, pp. 176-181, Banff, Canada, July 2002.

Computing -
An Evolutionary Algorithm Approach to the Design of

Minimum Cost Survivable Networks with Bounded Rings. B.Ombuki, M. Nakamura & M.Osamu.*IEICE Transactions on Fundamentals of*, Vol.E84-A No.6 pp.1545-1548, June 2001.

Electronics, Communications and Computer Sciences - Cyclic job-shop-scheduling based

on evolutionary Petri nets. Nakamura, M., Tome, H., Hachiman, K., Ombuki, B.M. and Onaga, K.

*Industrial Electronics Society, 2000. 26th Annual Conference of the IEEE,*, Vol. 4, pp. 2855-2860, 2000, Nagoya, Japan.

IECON 2000 - A
Genetic Algorithm Approach for the Design of

Minimum Cost Survivable Networks With Bounded Rings. B. Ombuki, M. Nakamura, Z. Nakao and K. Onaga.

*Proceedings of International Technical Conference On*, Vol. 1,pp 493-496, 2000, Pusan, Korea.

Circuits/Systems, Computers And Communications, ITC-CSSS'00 -
A Flexible Routing based on Object Oriented GAs in Vehicle Routing

Problem with Time Constraints. Khan S., Nakamura M., Ombuki B.M and Onaga K.

*Proceedings of the IEICE General Conference (Institute of Electronics, Information*, VOL.2000;NO.;PAGE.252(2000).

and Communication Engineers) -
Evolutionary Computation for Topological Optimization

of 3-Connected Computer Networks. B. Ombuki, M. Nakamura, Z. Nakao and K.

Onaga.*IEEE International Conference on Systems, Man, and*, CD, Tokyo, Oct. 1999

Cybernetics -
A Genetic Algorithm Approach to Vehicle Routing

Problem with Time Deadlines in Geographical Information Systems. O.Maeda, M.Nakamura, B. Ombuki, and K.

Onaga.*IEEE*, Vol.II, pp.595-600, Tokyo, Oct. 1999.

International Conference on Systems, Man, and Cybernetics -
Experimental Evaluation of an Evolutionary Scheduling Scheme

based on gkGA Approach to the Job Shop Problem. B. Ombuki, M. Nakamura, and K. Onaga.*Second International Conference on*, Vol. 3, pp 197-201, Adlaide, Australia, April 1998.

Knowledge-Based Intelligent Electronic Systems -
An Evolutionary Scheduling Scheme based on gkGA Approach to

the Job Shop Problem. B. Ombuki, M. Nakamura, and K. Onaga.*IEICE Transactions on Fundamentals of Electronics, Communication and*, Vol. E pp 1063-1071, June 1998.

Computer Sciences -
A New Hybrid GA Solution to Combinatorial

Optimization Problems - An Application to the Multiprocessor Scheduling Problems. . Nakamura, B. Ombuki, K. Shimabukuro, and K. Onaga.*Journal for Artificial*, Vol.2, 74-79, 1998.

Life and Robotics, Springer Verlag - A Hybridized GA Approach to the Job Shop Problem. B. Ombuki, M. Nakamura, and K. Onaga.

Proceedings of International Technical Conference On Circuits/Systems, Computers

and Communications

- (
*PhD*) Evolutionary Computation for Scheduling

and Network Design Problems - (
*ME*) Genetized-Knowledge Genetic Algorithm Approach

for Combinatorial Optimization