Professor Ruhul Sarker

Professor
School of Engineering and Information Technology
+61 2 6268 8051
+61 2 6268 8581

LOCATION

Room 218, Building 15, SEIT, UNSW-Canberra, Australia

  • ABOUT
  • PUBLICATIONS

Ruhul A Sarker obtained his PhD from Dalhousie University (former TUNS), Canada. He is a Professor in the School of Engineering and IT (SEIT) at UNSW Canberra located at ADFA. He served as the Director of Faculty PG Research (June 2015 to May 2020) and as the Deputy Head of School (Research) of SEIT (2011-2014). Prof. Sarker’s broad research interests are decision analytics, CI / evolutionary computation, operations research, and applied optimization.

For Future Research Students: PhD scholarships ($35,000 per year) are available for high achieving students (with H1 /High Distinction in UG and Masters by Research) in Computer Science, Information Sciences, Operations Research, or Industrial Engineering under my supervision. If you are interested contact me at r.sarker@adfa.edu.au

Linkedin pagehttps://www.linkedin.com/in/ruhul-a-sarker-0b88b652/

Link to our Canberra Evolutionary Optimization Research - EvOpt

For details of my personal research activities, go to the link: https://research.unsw.edu.au/people/professor-ruhul-sarker

We offer a Master by Coursework Program, see details in the link Master of Decision Analytics

We also offer Professional Development Short Courses, see details in the page (right column at the bottom): Operations and Decision Analysis

Books

Sarker R; Newton CS, 2008, Optimization Modelling: A Practical Approach, Original, Taylor and Francis Group/CRC Press, USA, http://www.amazon.com/gp/product/1420043102/sr=1-2/qid=1155535669/ref=sr_1_2/002-2329019-2363244?ie=UTF8&s=books#noop

Sarker R, 2003, Operations Research Applications in a Mining Company, Original, Berlin : Dissertation.de, 2003., Germany, http://www.dissertation.de/englisch/index.php3

Book Chapters

Chakrabortty R; Sarker R; Essam D, 2018, 'A Comparative Study of Different Integer Linear Programming Approaches for Resource-Constrained Project Scheduling Problems', in , Springer, Cham, pp. 227 - 242, http://dx.doi.org/10.1007/978-3-319-55914-8_17

Chakrabortty RK; Sarker ; Essam , 2017, 'Resource Constrained Multi-project Scheduling: A Priority Rule Based Evolutionary Local Search Approach', in Intelligent and Evolutionary Systems, edn. Proceedings in Adaptation, Learning and Optimization, vol 8., Springer, Canberra, Australia, pp. 75 - 86, http://dx.doi.org/10.1007/978-3-319-49049-6_6

Sallam K; Elsayed S; Sarker R; Essam D, 2016, 'Differential evolution with landscape-based operator selection for solving numerical optimization problems', in Intelligent and Evolutionary Systems The 20th Asia Pacific Symposium, IES 2016, Canberra, Australia, November 2016, Proceedings, pp. 371 - 387, https://link.springer.com/content/pdf/10.1007%2F978-3-319-49049-6.pdf

Elsayed S; Zaman M; Sarker , 2015, 'Automated Differential Evolution for Solving Dynamic Economic Dispatch Problems', in Lavangnananda K; PhonAmnuaisuk S; Engchuan W; Chan JH (ed.), Intelligent and Evolutionary Systems The 19th Asia Pacific Symposium, IES 2015, Bangkok, Thailand, November 2015, Proceedings, edn. Proceedings in Adaptation Learning and Optimization, Springer, King Mongkuts Univ Technol Thonburi, Sch Informat Technol, Bangkok, THAILAND, pp. 357 - 372, http://dx.doi.org/10.1007/978-3-319-27000-5_29

Elsayed S; Sarker R, 2014, 'Evolving the Parameters of Differential Evolution using Evolutionary Algorithms', in Proceedings in Adaptation, Learning and Optimization 1, Springer Cham Heidelberg, New York, pp. 523 - 534, http://dx.doi.org/10.1007/978-3-319-13359-1

Ray T; Sarker R, 2012, 'Memetic algorithms in constrained optimization', in Neri F; Cotta C; Moscato P (ed.), Handbook of Memetic Algorithms, Springer, Germany, pp. 135 - 151, http://dx.doi.org/10.1007/978-3-642-23247-3_9

Sarker RA; Ray T, 2010, 'Agent Based Evolutionary Approach: An Introduction', in Sarker RA; Ray T (ed.), AGENT-BASED EVOLUTIONARY SEARCH, edn. Adaptation Learning and Optimization, SPRINGER-VERLAG BERLIN, pp. 1 - 11, http://dx.doi.org/10.1007/978-3-642-13425-8_1

Ullah ASSMB; Sarker R; Lokan C, 2010, 'An Agent Based Evolutionary Approach for Nonlinear Optimization with Equality Constraints', in Sarker RA; Ray T (ed.), AGENT-BASED EVOLUTIONARY SEARCH, edn. Adaptation Learning and Optimization, SPRINGER-VERLAG BERLIN, pp. 49 - 76, http://dx.doi.org/10.1007/978-3-642-13425-8_3

Sarker R; Ray T, 2010, 'Agent based Evolutionary Approach: An Introduction', in Sarker R; Ray T (ed.), Agent-Based Evolutionary Search (Book series: Adaption, learning and optimization, vol. 5), edn. 1, Springer-Verlag, Berlin / Heidelberg, pp. 1 - 11, http://dx.doi.org/10.1007/978-3-642-13425-8

Barkat Ullah AS; Sarker R; Lokan CJ, 2010, 'An Agent Based Evolutionary Approach for Nonlinear Optimization with Equality Constraints', in Sarker R; Ray T (ed.), Agent-Based Evolutionary Search (Book series: Adaption, learning and optimization, vol. 5), edn. 1, Springer-Verlag, Berlin / Heidelberg, pp. 49 - 76, http://dx.doi.org/10.1007/978-3-642-13425-8

Sarker R, 2009, 'Alternative Mathematical Programming Models: A Case for Coal Blending Decision Process', in Pearce C; Hunt E (ed.), Optimization: Structure and Applications, Springer, Heidelberg, pp. 383 - 399, http://dx.doi.org/10.1007/978-0-387-98096-6_21

Hasan SM; Sarker R; Essam D; Cornforth DJ, 2009, 'A Genetic Algorithm with Priority Rules for Solving Job-Shop Scheduling Problems', in Chiong R; Dhakal S (ed.), Natural Intelligence for Scheduling, Planning and Packing Problems, edn. Studies in Computational Intelligence, Springer, Berlin / Heidelberg, pp. 55 - 88, http://dx.doi.org/10.1007/978-3-642-04039-9_3

Baker S; Bender A; Abbass HA; Sarker R, 2007, 'A Scenario-based Evolutionary Scheduling Approach for Assessing Future Suppy Chain Fleet Capabilities', in Studies in Computational Intelligence - Evolutionary Scheduling, Springer Verlag, pp. 485 - 512, http://dx.doi.org/10.1007/978-3-540-48584-1_18

Ray T; Sarker R, 2007, 'Optimum oil production planning using an evolutionary approach', in Studies in Computational Intelligence - Evolutionary Scheduling, Springer Verlag, pp. 273 - 292, http://dx.doi.org/10.1007/978-3-540-48584-1_10

Kamruzzaman J; Begg R; Sarker R, 2006, 'Artificial Neural Networks: Applications in Finance and Manufacturing', in Kamruzzaman J; Begg R; Sarker R (ed.), Artificial Neural Networks in Finance and Manufacturing, Idea Group Publishing, England, pp. 1 - 27, http://dx.doi.org/10.4018/978-1-59140-670-9.ch001

Sarker R; Begg R; Kamruzzaman J, 2006, 'Modeling and Prediction of Foreign Currency Exchange Markets', in Kamruzzaman J; Begg R; Sarker R (ed.), Artificial Neural Networks in Finance and Manufacturing, Idea Group Publishing, England, pp. 139 - 151, http://dx.doi.org/10.4018/978-1-59140-670-9.ch008

Sarker R; Abbass HA, 2006, 'Simultaneous Evolution of Network Architectures and Connection Weights in Artificial Neural Networks', in Kamruzzaman J; Begg R; Sarker R (ed.), Artificial Neural Networks in Finance and Manufacturing, Idea Group Publishing, England, pp. 28 - 41, http://dx.doi.org/10.4018/978-1-59140-670-9.ch002

Sarker R; Begg R; Kamruzzaman J, 2006, 'Movement Pattern Recognition Using Neural Networks', in Potter M; Roth K; Appicello A; Neidig J; Schmidt A (ed.), Neural Networks in Healthcare - Potential and Challenges, Idea Group Publishing, England, pp. 217 - 237, http://dx.doi.org/10.4018/978-1-59140-848-2.ch010

Sarker R; Begg R; Kamruzzaman J, 2006, 'Overview of Artificial Neural Networks and their Applications in Healthcare', in Potter M; Roth K; Appicello A; Neidig J; Schmidt A (ed.), Neural Networks in Healthcare - Potential and Challenges, Idea Group Publishing, England, pp. 1 - 19, http://dx.doi.org/10.4018/978-1-59140-848-2.ch001

Yang A; Abbass HA; Curtis N; Sarker R; Barlow MG, 2006, 'WISDOM-II: A Network Centric Model for Warfare', in Perez P; Batten D (ed.), Complex Science for a Complex World - Exploring Human Ecosystems with Agents, ANU E Press, Canberra, ACT Australia, pp. 149 - 174, http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000291158700011&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a

Abbass HA; Sarker R; Yang A, 2006, 'Chapter III: How Hard Is It To Red Team?', in Abbass H; Essam D (ed.), Applications of Information Systems to Homeland Security and Defense, edn. Original, Idea Group Publishing, Hershey PA, USA: London, UK, pp. 46 - 78

Yang A; Abbass HA; Sarker R, 2005, 'How hard is it to red team?', in Applications of Information Systems to Homeland Security and Defense, pp. 46 - 78, http://dx.doi.org/10.4018/978-1-59140-640-2.ch003

Yang A; Abbass HA; Barlow MG; Sarker R; Curtis N, 2005, 'Evolving Capability Requirements in WISDOM-II', in Abbass HA; Bossmaier T; Wiles J (ed.), Recent Advances in Artificial Life - Advances in Natural Computation - Vol. 3, edn. Original, World Scientific Publishing, Singapore, pp. 335 - 348, http://dx.doi.org/10.1142/9789812701497_0025

Sarker R; Abbass HA; Newton CS, 2003, 'Solving Two Multi-Objective Optimizatin Problems Using Evolutionary Algorithm', in Mohammadian M (ed.), Computational Intelligence in Control, edn. First, Idea Group Publishing, Hershey USA, pp. 218 - 232

Sarker R; Coello CA, 2002, 'Assessment Methodologies for Multiobjective Evolutionary Algorithms', in Sarker R; Mohammadian M; Yao X (ed.), Evolutionary Optimization, edn. Original, Kluwer Academic Publishers, Norwell, USA, pp. 177 - 195

Sarker R; Abbass HA; Newton CS, 2002, 'Introducing Data Mining and Knowledge Discovery', in Sarker R; Abbass H; Newton C (ed.), Heuristics and Optimization for Knowledge Discovery, edn. Original, Idea Group Publishing, Hershey, USA, pp. 1 - 11

Sarker R; Newton CS, 2000, 'Determination of Optimal Batch Size for a Manufacturing System', in Yang X; Mees AI; Fisher M; Jennings L (ed.), Progress in Oprimization: Contributions from Australasia, edn. APPLIED OPTIMIZATION, Kluwer Academic Publishers, The Netherland, pp. 315 - 327, http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000167757800021&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a

Sarker R; Runarsson T; Newton CS, 2000, 'Evolutionary Computation and Constrained Oprimization', in Mohammadian M (ed.), New Frontiers in Computational Intelligence and its Applications, edn. FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS, IOS Press, Amsterdam, pp. 144 - 157, http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000086824400016&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a

Sarker R; Rahman SS, 2000, 'Economics of EDI Investments', in Electronic Commerce: Opportunity and Challenges, edn. Original, Idea Group Publishing, USA, pp. 152 - 170

Edited Books

Sarker R; Ray T, (ed.), 2010, Agent-Based Evolutionary Search, Springer, Hieidelberg, Germay, http://dx.doi.org/10.1007/978-3-642-13425-8

Gen M; Green D; Katai O; Namatame A; Mckay RI; Sarker R; Zhang B, (eds.), 2009, Intelligent and Evolutionary Systems, Springer, Berlin /Heidelberg

Kamruzzaman J; Begg RK; Sarker RA, 2006, Artificial neural networks in finance and manufacturing, http://dx.doi.org/10.4018/978-1-59140-670-9

Begg R; Kamruzzaman J; Sarker R, 2006, Neural networks in healthcare: Potential and challenges, http://dx.doi.org/10.4018/978-1-59140-848-2

Sarker R; Mohammadian M; Yao X, (eds.), 2002, Evolutionary Optimization, Kluwer Academic Publishers, Norwell, USA

Abbass HA; Sarker R; Newton CS, (eds.), 2002, Data Mining: A Heuristic Approach, Idea Group Publishing, Hershey USA

Sarker RA; Abbass HA; Newton C, 2002, Heuristics and optimization for knowledge discovery, IGI Global

Abbass HA; Sarker RA; Newton CS, 2002, Data Mining: A Heuristic Approach, IGI Global

Mckay RI; Sarker R; Yao X, (eds.), 2000, International Journal of Knowledge - Based Intelligent Engineering Systems, University of South Australia, Adelaide

Journal articles

Ahrari A; Elsayed S; Sarker R; Essam D; Coello Coello CA, 2021, 'Weighted pointwise prediction method for dynamic multiobjective optimization', Information Sciences, vol. 546, pp. 349 - 367, http://dx.doi.org/10.1016/j.ins.2020.08.015

Haque M; Paul SK; Sarker R; Essam D, 2020, 'Managing decentralized supply chain using bilevel with Nash game approach', Journal of Cleaner Production, vol. 266, http://dx.doi.org/10.1016/j.jclepro.2020.121865

Zaman F; Elsayed S; Sarker R; Essam D, 2020, 'Hybrid evolutionary algorithm for large-scale project scheduling problems', Computers and Industrial Engineering, vol. 146, http://dx.doi.org/10.1016/j.cie.2020.106567

Elsayed S; Sarker R; Essam D; Coello Coello CA, 2020, 'Evolutionary approach for large-Scale mine scheduling', Information Sciences, vol. 523, pp. 77 - 90, http://dx.doi.org/10.1016/j.ins.2020.02.074

Samavati M; Essam D; Nehring M; Sarker R, 2020, 'Production planning and scheduling in mining scenarios under IPCC mining systems', Computers and Operations Research, vol. 115, http://dx.doi.org/10.1016/j.cor.2019.05.019

Zaman F; Elsayed SM; Saker R; Essam D, 2020, 'Resource Constrained Project Scheduling with Dynamic Disruption Recovery', IEEE Access, vol. 8, pp. 144866 - 144879, http://dx.doi.org/10.1109/ACCESS.2020.3014940

Hamza N; Sarker R; Essam D, 2020, 'Sensitivity-Based Change Detection for Dynamic Constrained Optimization', IEEE Access, vol. 8, pp. 103900 - 103912, http://dx.doi.org/10.1109/ACCESS.2020.2999161

Rana MJ; Zaman F; Ray T; Sarker R, 2020, 'Heuristic enhanced evolutionary algorithm for community microgrid scheduling', IEEE Access, vol. 8, pp. 76500 - 76515, http://dx.doi.org/10.1109/ACCESS.2020.2989795

Harrison KR; Elsayed S; Garanovich I; Weir T; Galister M; Boswell S; Taylor R; Sarker R, 2020, 'Portfolio Optimization for Defence Applications', IEEE Access, vol. 8, pp. 60152 - 60178, http://dx.doi.org/10.1109/ACCESS.2020.2983141

Liu C; Zhao Q; Yan B; Elsayed S; Sarker R, 2019, 'Transfer learning-assisted multi-objective evolutionary clustering framework with decomposition for high-dimensional data', Information Sciences, vol. 505, pp. 440 - 456, http://dx.doi.org/10.1016/j.ins.2019.07.099

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