Professor Edward Tsang
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Email
edward@essex.ac.uk -
Location
5A.531, Colchester Campus
Teaching and supervision
Previous supervision
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 24/6/2024
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 23/12/2022
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 30/3/2022
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 14/11/2019
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 6/12/2018
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 5/11/2018
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 24/8/2018
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 23/7/2018
Degree subject: Computational Finance
Degree type: Master of Science (by Dissertation)
Awarded date: 23/1/2018
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 28/9/2017
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 2/2/2017
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 3/11/2016
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 6/6/2016
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 25/3/2014
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 8/7/2013
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 29/4/2013
Publications
Journal articles (63)
Tsang, EPK., (2022). Directional change for handling tick-to-tick data. Journal of Chinese Economic and Business Studies. 20 (2), 171-182
Li, S., Tsang, EPK. and O'Hara, J., (2022). Measuring relative volatility in high‐frequency data under the directional change approach. Intelligent Systems in Accounting, Finance and Management. 29 (2), 86-102
Chinthalapati, VLR. and Tsang, E., (2019). Special Issue on Algorithms in Computational Finance. Algorithms. 12 (4), 69-69
Shi, J., Zhang, Q. and Tsang, E., (2018). EB-GLS: an improved guided local search based on the big valley structure. Memetic Computing. 10 (3), 333-350
Bakhach, AM., Tsang, EPK. and Raju Chinthalapati, VL., (2018). TSFDC: A trading strategy based on forecasting directional change. Intelligent Systems in Accounting, Finance and Management. 25 (3), 105-123
Chen, J. and Tsang, EPK., (2018). Classification of Normal and Abnormal Regimes in Financial Markets. Algorithms. 11 (12), 202-202
Bakhach, A., Chinthalapati, V., Tsang, E. and El Sayed, A., (2018). Intelligent Dynamic Backlash Agent: A Trading Strategy Based on the Directional Change Framework. Algorithms. 11 (11), 171-171
Doctor, F., Galvan-Lopez, E. and Tsang, E., (2018). Guest Editorial Special Issue on Data-Driven Computational Intelligence for e-Governance, Socio-Political, and Economic Systems. IEEE Transactions on Emerging Topics in Computational Intelligence. 2 (3), 171-173
Tsang, E. and Chen, J., (2018). Regime Change Detection Using Directional Change Indicators in the Foreign Exchange Market to Chart Brexit. IEEE Transactions on Emerging Topics in Computational Intelligence. 2 (3), 185-193
Tsang, EPK., Tao, R., Serguieva, A. and Ma, S., (2017). Profiling high-frequency equity price movements in directional changes. Quantitative Finance. 17 (2), 217-225
Aloud, M., Fasli, M., Tsang, E., Dupuis, A. and Olsen, R., (2017). Modeling the High-Frequency FX Market: An Agent-Based Approach. Computational Intelligence. 33 (4), 771-825
Wang, P., Tang, K., Weise, T., Tsang, EPK. and Yao, X., (2014). Multiobjective genetic programming for maximizing ROC performance. Neurocomputing. 125, 102-118
Rashidi, H. and Tsang, EPK., (2013). Novel constraints satisfaction models for optimization problems in container terminals. Applied Mathematical Modelling. 37 (6), 3601-3634
Bernardo, D., Hagras, H. and Tsang, E., (2013). A genetic type-2 fuzzy logic based system for the generation of summarised linguistic predictive models for financial applications. Soft Computing. 17 (12), 2185-2201
Kampouridis, M., Alsheddy, A. and Tsang, E., (2013). On the investigation of hyper-heuristics on a financial forecasting problem. Annals of Mathematics and Artificial Intelligence. 68 (4), 225-246
MASRY, S., DUPUIS, A., OLSEN, RB. and TSANG, E., (2013). Time zone normalization of FX seasonality. Quantitative Finance. 13 (7), 1115-1123
Tsang, E., Olsen, R. and Masry, S., (2013). A formalization of double auction market dynamics. Quantitative Finance. 13 (7), 981-988
Aloud, M., Fasli, M., Tsang, E., Dupuis, A. and Olsen, R., (2013). Stylized Facts of the FX Market Transactions Data: An Empirical Study. Journal of Finance and Investment Analysis. 2 (4), 145-183
Kampouridis, M. and Tsang, E., (2012). Investment Opportunities Forecasting: Extending the Grammar of a GP-based Tool. International Journal of Computational Intelligence Systems. 5 (3), 530-530
Aloud, M., Tsang, E., Olsen, R. and Dupuis, A., (2012). A Directional-Change Event Approach for Studying Financial Time Series. Economics. 6 (1)
KAMPOURIDIS, M., CHEN, S-H. and TSANG, E., (2012). MICROSTRUCTURE DYNAMICS AND AGENT-BASED FINANCIAL MARKETS: CAN DINOSAURS RETURN?. Advances in Complex Systems. 15 (supp02), 1250060-1250060
Kampouridis, M., Chen, S-H. and Tsang, E., (2012). Market fraction hypothesis: A proposed test. International Review of Financial Analysis. 23, 41-54
Rashidi, H. and Tsang, EPK., (2011). A complete and an incomplete algorithm for automated guided vehicle scheduling in container terminals. Computers & Mathematics with Applications. 61 (3), 630-641
Alsheddy, A. and Tsang, EPK., (2011). Empowerment scheduling for a field workforce. Journal of Scheduling. 14 (6), 639-654
Jin, N. and Tsang, E., (2011). Bargaining strategies designed by evolutionary algorithms. Applied Soft Computing. 11 (8), 4701-4712
Alexandrova-Kabadjova, B., Tsang, E. and Krause, A., (2011). Competition is Bad for Consumers: Analysis of an Artificial Payment Card Market. Journal of Advanced Computational Intelligence and Intelligent Informatics. 15 (2), 188-196
Alexandrova-Kabadjova, B., Tsang, E. and Krause, A., (2011). Market structure and information in payment card markets. International Journal of Automation and Computing. 8 (3), 364-370
Qingfu Zhang, Wudong Liu, Tsang, E. and Virginas, B., (2010). Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model. IEEE Transactions on Evolutionary Computation. 14 (3), 456-474
Borenstein, Y., Shah, N., Tsang, E., Dorne, R., Alsheddy, A. and Voudouris, C., (2010). On the partitioning of dynamic workforce scheduling problems. Journal of Scheduling. 13 (4), 411-425
Martinez-Jaramillo, S. and Tsang, EPK., (2009). An Heterogeneous, Endogenous and Coevolutionary GP-Based Financial Market. IEEE Transactions on Evolutionary Computation. 13 (1), 33-55
Jin, N., Tsang, E. and Li, J., (2009). A constraint-guided method with evolutionary algorithms for economic problems. Applied Soft Computing. 9 (3), 924-935
Tsang, E. and Isasi, P., (2009). Editorial Special Issue: Computational Finance and Economics. IEEE Transactions on Evolutionary Computation. 13 (1), 1-2
Tsang, E., (2009). Forecasting — where computational intelligence meets the stock market. Frontiers of Computer Science in China. 3 (1), 53-63
Borrett, JE. and Tsang, EPK., (2009). Adaptive Constraint Satisfaction: The Quickest First Principle. Intelligent Systems Reference Library. 1 (1), 203-230
Virginas, B., Ursu, M., Tsang, E., Owusu, G. and Voudouris, C., (2008). Intelligent resource exchanges: Solutions and pathways in a workforce allocation problem. Journal of Universal Computer Science. 14 (14), 2343-2358
Tsang, EPK., Gosling, T., Virginas, B., Voudouris, C., Owusu, G. and Liu, W., (2008). Retractable contract network for empowerment in workforce scheduling. Multiagent and Grid Systems. 4 (1), 25-44
Tsang, EPK., (2008). Computational intelligence determines effective rationality. International Journal of Automation and Computing. 5 (1), 63-66
Garcia-Almanza, AL. and Tsang, EPK., (2008). Evolving decision rules to predict investment opportunities. International Journal of Automation and Computing. 5 (1), 22-31
Abbas, AM., Tsang, EPK. and Nasri, AH., (2008). DEPICT: A high-level formal language for modeling constraint satisfaction problems. International Journal of Automation and Computing. 5 (2), 208-216
Garcia-Almanza, AL. and Tsang, EPK., (2007). Detection of stock price movements using chance discovery and genetic programming. International Journal of Knowledge-based and Intelligent Engineering Systems. 11 (5), 329-344
Zhang, Q., Sun, J., Xiao, G. and Tsang, E., (2007). Evolutionary Algorithms Refining a Heuristic: A Hybrid Method for Shared-Path Protections in WDM Networks Under SRLG Constraints. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics). 37 (1), 51-61
Tsang, E., Ford, J., Mills, P., Bradwell, R., Williams, R. and Scott, P., (2007). Towards a practical engineering tool for rostering. Annals of Operations Research. 155 (1), 257-277
Zhang, Q., Sun, J. and Tsang, E., (2007). Combinations of estimation of distribution algorithms and other techniques. International Journal of Automation and Computing. 4 (3), 273-280
Zhang, Q., Sun, J., Tsang, E. and Ford, J., (2006). Estimation of Distribution Algorithm with 2-opt Local Search for the Quadratic Assignment Problem. Studies in Fuzziness and Soft Computing. 192, 281-292
SUN, J., ZHANG, Q. and TSANG, E., (2005). DE/EDA: A new evolutionary algorithm for global optimization. Information Sciences. 169 (3-4), 249-262
Zhang, Q., Sun, J. and Tsang, E., (2005). An Evolutionary Algorithm With Guided Mutation for the Maximum Clique Problem. IEEE Transactions on Evolutionary Computation. 9 (2), 192-200
TSANG, EDWARD., MARKOSE, SHERI. and HAKAN, ER., (2005). CHANCE DISCOVERY IN STOCK INDEX OPTION AND FUTURES ARBITRAGE. New Mathematics and Natural Computation. 01 (03), 435-447
Tsang, E., Markose, SM. and Er, H., (2005). Chance Discovery In Stock Index Option And Futures Arbitrage. New Mathematics and Natural Computation. 1 (03), 435-447
TSANG, E., MARKOSE, S. and HAKAN, E., (2005). CHANCE DISCOVERY IN STOCK INDEX OPTION AND FUTURES ARBITRAGE. New Mathematics and Natural Computation. 01 (03), 435-447
Abbas, A. and Tsang, EPK., (2004). Software engineering aspects of constraint-based timetabling—a case study. Information and Software Technology. 46 (6), 359-372
Tsang, E., Yung, P. and Li, J., (2004). EDDIE-Automation, a decision support tool for financial forecasting. Decision Support Systems. 37 (4), 559-565
Zhang, Q., Sun, J., Tsang, E. and Ford, J., (2004). Hybrid estimation of distribution algorithm for global optimization. Engineering Computations. 21 (1), 91-107
Mills, P., Tsang, E. and Ford, J., (2003). Applying an Extended Guided Local Search to the Quadratic Assignment Problem. Annals of Operations Research. 118 (1/4), 121-135
Borrett, JE. and Tsang, EPK., (2001). A context for constraint satisfaction problem formulation selection. Constraints. 6 (4), 299-327
Lau, TL. and Tsang, EPK., (2001). Guided genetic algorithm and its application to radio link frequency assignment problems. Constraints. 6 (4), 373-398
Mills, P. and Tsang, E., (2000). Guided local search for solving SAT and weighted MAX-SAT problems. Journal of Automated Reasoning. 24 (1/2), 205-223
Voudouris, C. and Tsang, E., (1999). Guided local search and its application to the traveling salesman problem. European Journal of Operational Research. 113 (2), 469-499
Tsang, E., (1999). A glimpse of constraint satisfaction. Artificial Intelligence Review. 13 (3), 215-227
Tsang, EPK., Li, J. and Butler, JM., (1998). EDDIE beats the bookies. Software: Practice and Experience. 28 (10), 1033-1043
Howarth, RJ. and Tsang, EPK., (1998). Spatio-temporal conflict detection and resolution. Constraints. 3 (4), 343-361
Tsang, E., (1998). No more “Partial” and “Full Looking Ahead”. Artificial Intelligence. 98 (1-2), 351-361
Kwan, ACM., Tsang, EPK. and Borrett, JE., (1998). Predicting Phase Transitions of Binary Constraint Satisfaction Problems with Constraint Graph Information. Intelligent Data Analysis. 2 (1), 45-62
Tsang, E. and Voudouris, C., (1997). Fast local search and guided local search and their application to British Telecom's workforce scheduling problem. Operations Research Letters. 20 (3), 119-127
Books (5)
Tsang, EPK., (2023). AI for Finance. CRC Press
Rashidi, H. and Tsang, E., (2015). Vehicle scheduling in port automation: Advanced algorithms for minimum cost flow problems, second edition
Alexandrova-Kabadjova, B., Martinez-Jaramillo, S., Garcia-Almanza, AL. and Tsang, E., (2012). Simulation in Computational Finance and Economics Tools and Emerging Applications. IGI Global. 1466620110. 9781466620117
(2008). Service Chain Management. Springer Berlin Heidelberg. 9783540755036
(2003). Genetic Programming. Springer Berlin Heidelberg. 9783540009719
Book chapters (7)
Alsheddy, A., Voudouris, C., Tsang, EPK. and Alhindi, A., (2018). Guided Local Search. In: Handbook of Heuristics. Editors: . Springer International Publishing. 261- 297. 9783319071237
Aloud, M., Tsang, E. and Olsen, R., (2015). Modeling the FX Market Traders' Behavior. In: Banking, Finance, and Accounting. IGI Global. 350- 384. 9781466662681
Kampouridis, M., Chen, S-H. and Tsang, E., (2011). Market Microstructure: A Self-Organizing Map Approach to Investigate Behavior Dynamics under an Evolutionary Environment. In: Studies in Computational Intelligence. Editors: . Springer Berlin Heidelberg. 181- 197. 9783642233357
Alexandrova-Kabadjova, B., Tsang, E. and Krause, A., (2008). Evolutionary Learning of the Optimal Pricing Strategy in an Artificial Payment Card Market. In: Studies in Computational Intelligence. Editors: . Springer Berlin Heidelberg. 233- 251. 9783540774761
Jin, Y., Zhou, A., Zhang, Q., Sendhoff, B. and Tsang, E., (2008). Modeling Regularity to Improve Scalability of Model-Based Multiobjective Optimization Algorithms. In: Natural Computing Series. Editors: . Springer Berlin Heidelberg. 331- 355. 9783540729631
Tsang, E., Markose, S., Garcia, A. and Er, H., (2007). EDDIE for discovering arbitrage opportunities. In: Numerical Methods for Finance. 281- 284
Hoos, HH. and Tsang, E., (2006). Local Search Methods. In: Foundations of Artificial Intelligence. Editors: . Elsevier. 135- 167. 978-0-444-52726-4
Conferences (77)
Ao, H. and Tsang, E., (2019). Trading Algorithms Built with Directional Changes
Chen, J. and Tsang, EPK., (2019). Tacking Regime Changes in the Markets
Bakhach, A., Tsang, EPK. and Jalalian, H., (2017). Forecasting directional changes in the FX markets
Tsang, EPK., (2017). Directional Changes: A New Way to Look at Price Dynamics
Ye, A., Chinthalapati, VLR., Serguieva, A. and Tsang, E., (2017). Developing sustainable trading strategies using directional changes with high frequency data
Chen, J. and Tsang, EPK., (2017). Constructing a bellwether theory: Regime change detection using directional change
Bakhach, A., Tsang, E., Wing Lon Ng and Chinthalapati, VLR., (2016). Backlash Agent: A trading strategy based on Directional Change
Alhindi, A., Zhang, Q. and Tsang, E., (2014). Hybridisation of decomposition and GRASP for combinatorial multiobjective optimisation
Aluko, B., Smonou, D., Kampouridis, M. and Tsang, E., (2014). Combining different meta-heuristics to improve the predictability of a Financial Forecasting algorithm
Shao, M., Smonou, D., Kampouridis, M. and Tsang, E., (2014). Guided Fast Local Search for speeding up a financial forecasting algorithm
Bernardo, D., Hagras, H. and Tsang, E., (2013). A Genetic Type-2 fuzzy logic based system for financial applications modelling and prediction
Smonou, D., Kampouridis, M. and Tsang, E., (2013). Metaheuristics application on a financial forecasting problem
Shaghaghi, AR., Glover, T., Kampouridis, M. and Tsang, E., (2013). Guided Local Search for Optimal GPON/FTTP Network Design
Bernardo, D., Hagras, H. and Tsang, E., (2012). An interval type-2 Fuzzy Logic based system for model generation and summarization of arbitrage opportunities in stock markets
Bernardo, D., Hagras, H. and Tsang, E., (2012). An Interval Type-2 Fuzzy Logic System for the Modeling and Prediction of Financial Applications
Kampouridis, M., Glover, T., Shaghaghi, AR. and Tsang, E., (2012). Using a genetic algorithm as a decision support tool for the deployment of Fiber Optic Networks
Kampouridis, M., Chen, S-H. and Tsang, E., (2011). Investigating the effect of different GP algorithms on the non-stationary behavior of financial markets
Wang, P., Tang, K., Tsang, EPK. and Yao, X., (2011). A Memetic Genetic Programming with decision tree-based local search for classification problems
Aloud, M., Tsang, E., Dupuis, A. and Olsen, R., (2011). Minimal agent-based model for the origin of trading activity in Foreign exchange market
Kampouridis, M. and Tsang, E., (2011). Using Hyperheuristics under a GP Framework for Financial Forecasting
Chen, S-H., Kampouridis, M. and Tsang, E., (2011). Microstructure Dynamics and Agent-Based Financial Markets
Kampouridis, M., Chen, S-H. and Tsang, E., (2011). Market Microstructure: Can Dinosaurs Return? A Self-Organizing Map Approach under an Evolutionary Framework
Masry, S. and Tsang, EK., (2011). Simulating market clearance dynamics under a simple event calculus market model
Aloud, M. and Tsang, E., (2011). Modelling the trading behaviour in high-frequency markets
Alsheddy, A. and Tsang, EEPK., (2010). Guided Pareto Local Search based frameworks for biobjective optimization
Kampouridis, M. and Tsang, E., (2010). EDDIE for investment opportunities forecasting: Extending the search space of the GP
Zhang, Q., Li, H., Maringer, D. and Tsang, E., (2010). MOEA/D with NBI-style Tchebycheff approach for portfolio management
Tsang, E., (2010). Constraint-Directed Search in Computational Finance and Economics
Wang, P., Tsang, EPK., Weise, T., Tang, K. and Yao, X., (2010). Using GP to evolve decision rules for classification in financial data sets
Kampouridis, M., Chen, S-H. and Tsang, E., (2010). Testing the Dinosaur Hypothesis under Empirical Datasets
Alsheddy, A. and Tsang, EPK., (2010). A guided local search based algorithm for the multiobjective empowerment-based field workforce scheduling
Kampouridis, M., Chen, S-H. and Tsang, E., (2010). Testing the Dinosaur Hypothesis under different GP algorithms
Masry, S., Aloud, M., Tsang, E., Dupuis, A. and Olsen, R., (2010). A novel approach for studying the high-frequency FOREX market
Liu, W., Zhang, Q., Tsang, E. and Virginas, B., (2009). Fuzzy clustering based Gaussian Process Model for large training set and its application in expensive evolutionary optimization
Shah, N., Tsang, E., Borenstein, Y., Dorne, R., Liret, A. and Voudouris, C., (2009). Intelligent Agent Based Workforce Empowerment
Martinez-Jaramillo, S. and Tsang, EPK., (2009). Evolutionary Computation and Artificial Financial Markets
Borenstein, Y., Alsheddy, A., Tsang, E. and Shah, N., (2009). The degree of dynamism for workforce scheduling problem with stochastic task duration
Wudong Liu, Qingfu Zhang, Tsang, E. and Virginas, B., (2008). Tchebycheff approximation in Gaussian Process model composition for multi-objective expensive black box
Borenstein, Y., Shah, N., Tsang, E., Dorne, R., Alsheddy, A. and Voudouris, C., (2008). On the partitioning of dynamic scheduling problems -
(2008). Message from PDCoF-08 Workshop Chairs
Garcia-Almanza, AL. and Tsang, EPK., (2007). Repository method to suit different investment strategies
Liu, W., Zhang, Q., Tsang, E., Liu, C. and Virginas, B., (2007). On the Performance of Metamodel Assisted MOEA/D
Virginas, B., Ursu, M., Tsang, E., Owusu, G. and Voudouris, C., (2007). Intelligent Resource Allocation–Solutions and Pathways in a Workforce Planning Problem
Alexandrova-Kabadjova, B., Krause, A. and Tsang, E., (2007). An Agent-Based Model of Interactions in the Payment Card Market
Zhou, A., Zhang, Q., Jin, Y., Sendhoff, B. and Tsang, E., (2007). Global multiobjective optimization via estimation of distribution algorithm with biased initialization and crossover
Zhou, A., Jin, Y., Zhang, Q., Sendhoff, B. and Tsang, E., (2007). Prediction-Based Population Re-initialization for Evolutionary Dynamic Multi-objective Optimization
Garcia-Almanza, AL. and Tsang, EPK., (2006). The Repository Method for Chance Discovery in Financial Forecasting
Garcia-Almanza, AL. and Tsang, EPK., (2006). Simplifying decision trees learned by genetic programming
Gosling, T. and Tsang, E., (2006). Tackling the simple supply chain model
Jin, N. and Tsang, E., (2006). Co-adaptive strategies for sequential bargaining problems with discount factors and outside options
Tsang, E., (2006). Wind-Tunnel Testing for strategy and market design
Abbas, A., Tsang, E. and Nasri, A., (2006). DEPICT: A High-Level Formal Language For Modeling Constraint Satisfaction Problems
Zhou, A., Jin, Y., Zhang, Q., Sendhoff, B. and Tsang, E., (2006). Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion
Tsang, E. and Jin, N., (2006). Incentive Method to Handle Constraints in Evolutionary Algorithms with a Case Study
Zhou, A., Zhang, Q., Jin, Y., Sendhoff, B. and Tsang, E., (2006). Modelling the Population Distribution in Multi-objective Optimization by Generative Topographic Mapping
Gosling, T., Jin, N. and Tsang, E., (2005). Population based incremental learning with guided mutation versus genetic algorithms: Iterated prisoners dilemma
Zhou, A., Zhang, Q., Jin, Y., Tsang, E. and Okabe, T., (2005). A model-based evolutionary algorithm for Bi-objective optimization
Jin, N. and Tsang, E., (2005). Co-evolutionary strategies for an alternating-offer bargaining problem
Jin, N. and Tsang, E., (2005). Relative Fitness and Absolute Fitness for Co-evolutionary Systems
Markose, S., Tsang, E. and Jaramillo, SM., (2005). The Red Queen principle and the emergence of efficient financial markets: An agent based approach
Li, H., Zhang, Q., Tsang, E. and Ford, JA., (2004). Hybrid Estimation of Distribution Algorithm for Multiobjective Knapsack Problem
Dongbing Gu, Huosheng Hu, Reynolds, J. and Tsang, E., (2003). GA-based learning in behaviour based robotics
Abbas, AM. and Tsang, EPK., (2001). Constraint-based timetabling-a case study
Markose, S., Tsang, E., Er, H. and Salhi, A., (2001). Evolutionary arbitrage for FTSE-100 index options and futures
Markose, S., Tsang, E., Hakan Er and Salhi, A., (2001). Evolutionary arbitrage for FTSE-100 index options and futures
Tsang, EPK. and Li, J., (2000). Combining Ordinal Financial Predictions with Genetic Programming
Jin Li and Tsang, EPK., (1999). Investment decision making using FGP: a case study
Lau, TL. and Tsang, EPK., (1998). Solving large processor configuration problems with the guided genetic algorithm
Lau, TL. and Tsang, EPK., (1998). The guided genetic algorithm and its application to the generalized assignment problem
Kwan, ACM. and Tsang, EPK., (1996). Minimal forward checking with backmarking and conflict-directed backjumping
Lau, TL. and Tsang, EPK., (1996). Applying a mutation-based genetic algorithm to processor configuration problems
Tsang, EPK., (1995). Scheduling techniques - a comparative study
Freuder, EC., Dechter, R., Ginsberg, ML., Selman, B. and Tsang, E., (1995). Systematic Versus Stochastic Constraint Satisfaction
Warwick, T. and Tsang, E., (1994). Using a genetic algorithm to tackle the processors configuration problem
Davenport, A., Tsang, E., Wang, CJ. and Zhu, K., (1994). GENET: a connectionist architecture for solving constraint satisfaction problems by iterative improvement
Wang, CJ. and Tsang, EPK., (1991). Solving constraint satisfaction problems using neural networks
Tsang, EPK., (1987). TIME STRUCTURES FOR AI
Reports and Papers (8)
Gosling, T. and Tsang, E., CSM-392 PhD in Open Constraint Satisfaction Technical Report 1: The Simple Supply Chain Model (SSCM)
Kampouridis, M., Chen, S. and Tsang, E., (2011). CES-511 The Market Fraction Hypothesis under different GP algorithms
Kampouridis, M., Chen, S. and Tsang, E., (2010). CES-509 Market Microstructure: Can Dinosaurs Return? A Self-Organizing Map Approach under an Evolutionary Framework
Kampouridis, M., Chen, S. and Tsang, E., (2010). The Market Fraction Hypothesis under different GP algorithms
Mills, P., Tsang, E., Zhang, Q. and Ford, JA., (2004). CSM-416 A survey of AI-based meta-heuristics for dealing with local optima in local search
Gosling, T., Jin, N. and Tsang, E., (2004). CSM-401 - Population based Incremental Learning vesus Genetic Algorithms: Iterated Prisoners Dilemma
Tsang, E., (2003). CSM-385 Cooperation in Competitions - Constraint Propagation Strategies in Chain-bargaining
Tsang, E. and Kwan, A., (1993). CSM-198 Mapping Constraint Satisfaction Problems to Algorithms and Heuristics
Scholarly Editions (1)
Serafin, MJ., Tsang, EPK. and Markose, S., Co evolution of Genetic Programming Based Agents in an Artificial Stock Market
Grants and funding
2016
The Translab Power Dial(2)
Transfaction Ltd
2013
Trans Mash
General
Optimum Labour Scheduling in Container Ports - 50%
Technology STrategy Board
Optimum Labour Scheduling in Container Ports - 50%
Hutchison Ports (UK) Limited
2011
Backhaul Network Optimisation
British Telecommunications Plc
2010
Real time scheduling algorithm and tuning of FieldSchedule application
British Telecommunications Plc
67% To develop embedded systems for intelligent process control
Technology STrategy Board
33% To develop embedded systems for intelligent process control
Sanctuary Personnel Ltd
Network Optimisation for NGA and NGN Networks
British Telecommunications Plc
Forecasting Demand for Fibre-based Networks
British Telecommunications Plc
2008
Workforce Dynamics Simulator
British Telecommunications Plc