People

Professor Edward Tsang

Emeritus Professor
School of Computer Science and Electronic Engineering (CSEE)
Professor Edward Tsang

Teaching and supervision

Previous supervision

Kam Yoon Chong
Kam Yoon Chong
Thesis title: Lie Symmetry Analysis on Pricing Power Options Under the Heston Dynamic and Some Fractional Financial Models
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 24/6/2024
Chen Chen
Chen Chen
Thesis title: Stock Market Investment Using Machine Learning
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 23/12/2022
Shuai Ma
Shuai Ma
Thesis title: Tracking and Nowcasting Directional Changes in the Forex Market
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 30/3/2022
Jun Chen
Jun Chen
Thesis title: Studying Regime Change Using Directional Change
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 14/11/2019
Amer Bakhach
Amer Bakhach
Thesis title: Developing Trading Strategies Under the Directional Changes Framework with Application in the Fx Market
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 6/12/2018
Ran Tao
Ran Tao
Thesis title: Using Directional Changes for Information Extraction in Financial Market Data
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 5/11/2018
Jorge Faleiro
Jorge Faleiro
Thesis title: Supporting Large Scale Collaboration and Crowd-Based Investigation in Economics: A Computational Representation for Description and Simulation of Financial Models
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 24/8/2018
Han Ao
Han Ao
Thesis title: A Directional Changes Based Study on Stock Market
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 23/7/2018
Shengnan Li
Shengnan Li
Thesis title: Searching for Head and Shoulders Bottom Patterns Under Directional Changes
Degree subject: Computational Finance
Degree type: Master of Science (by Dissertation)
Awarded date: 23/1/2018
Manuel Kleinknecht
Manuel Kleinknecht
Thesis title: Improving Regulatory Market Risk Management with Heuristic Algorithms
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 28/9/2017
Vincent Vella
Vincent Vella
Thesis title: Improving Risk-Adjusted Performance in High Frequency Trading: The Role of Fuzzy Logic Systems
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 2/2/2017
David Norman
David Norman
Thesis title: Human Traders Need New Tools: The Potential for Assistive/Interventionist Trading Tools in Trading Financial Markets
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 3/11/2016
Hamid Reza Jalalian
Hamid Reza Jalalian
Thesis title: Decomposition Evolutionary Algorithms for Noisy Multiobjective Optimization
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 6/6/2016
Collether Nyalusi John
Collether Nyalusi John
Thesis title: Portfolio Optimization By Heuristic Algorithms
Degree subject: Computing and Electronic Systems
Degree type: Doctor of Philosophy
Awarded date: 25/3/2014
Shaimaa Masry Hussein Masry
Shaimaa Masry Hussein Masry
Thesis title: Event-Based Microscopic Analysis of the Fx Market
Degree subject: Computational Finance
Degree type: Doctor of Philosophy
Awarded date: 8/7/2013
Monira Essa M Aloud
Monira Essa M Aloud
Thesis title: Modelling the High-Frequency Fx Market: An Agent-Based Approach
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

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

Contact

edward@essex.ac.uk

Location:

5A.531, Colchester Campus