1. Edward Tsang Research Business applications of Artificial Intelligence Constraint satisfaction & optimization research –A branch of combinatorial optimisation –Applied to decision support and scheduling Computational finance & economics –Computational intelligence + finance and economics –Applied to forecasting, bargaining, wind-tunnel testing Enabling technology: heuristic search, evolutionary computation, inferences 13 October 2015Edward Tsang (Copyright)

2. Edward Tsang Profile BBA (Finance & Marketing) + PhD (Computing) Business applications of Artificial Intelligence Constraint satisfaction & optimization research –Professor, Computer Science Computational finance & economics research –Founder, IEEE CFETCCFETC –Co-founder, CCFEA and CICCCFEA CIC Technologies: heuristic search, evolutionary computation, data mining 13 October 2015Edward Tsang (Copyright)

3. Constraint Satisfaction & Optimization Core technologies for transportation optimization –Guided Local Search was used in ILOG Solver’s vehicle routing package, Dispatcher. –BT: work force scheduling problem.work force scheduling problem –Honda: Multi-objective optimization Sponsors: BT, Honda Europe

4. Computational Finance & Economics Advanced computer science applied to finance –More than using spreadsheets or computerisation of accounting systems Research at Essex: –Forecasting –Automated Bargaining (game theory) –Economic Wind-tunnel testing (market design) Affiliated Centre: Centre for Computational Finance & Economic Agents (CCFEA)CCFEA Sponsors: Sharescope, BT, OANDA

5. Research Profile, Edward Tsang ApplicationTechnology Finite Choices Decision Support, e.g. Assignment, Scheduling, Routing Constraint Satisfaction, Optimisation, Heuristic Search (Guided Local Search) Financial ForecastingGenetic Programming Automated BargainingGenetic Programming Wind Tunnel Testing for designing markets and finding winning strategies Mathematical Modelling, Machine Learning, Experimental Design Portfolio OptimisationMulti-objectives Optimisation Business Applications of Artificial Intelligence

6. Supplementary Information Edward Tsang

7. Current Activities – Edward Tsang Current Projects: EDDIE for Forecasting – towards more complex trading strategiesEDDIE for Forecasting Automated bargaining – finding Nash equilibrium strategiesAutomated bargaining Artificial markets – conditions for stylised factsArtificial markets Credit cards market – designing bank strategies and Government policiesCredit cards market Market-based scheduling – for BT work force schedulingMarket-based scheduling Evolving middlemen strategies – for simple supply chains (BT sponsored)Evolving middlemen strategies Chance discovery – data mining for scarce opportunitiesChance discovery Port automated – vehicles schedulingPort automated Multi-objective optimisation – for Honda’s industrial design Portfolio optimisation by heuristic search Constraint Satisfaction & Optimisation Computational Finance Research Groups: Affiliations: Professor Director 1/8/2009

8. Background, Edward Tsang Education: BSc in Business Administration, Chinese University of Hong Kong MSc, PhD in Computer Science, University of Essex Commonwealth Secretariat Past employments: Consultancy: Selected external positions: Editorialship, including: –IEEE Transactions on Evolutionary ComputationIEEE Transactions on Evolutionary Computation –Journal of SchedulingJournal of Scheduling –CONSTRAINTSCONSTRAINTS Chair, IEEE Computational Finance and Economics Technical Committee, 2004 & 2005Computational Finance and Economics Technical Committee Co-chair, IEEE Taskforce on Portfolio Optimisation, 2006-

9. The Constraint Satisfaction Problem Constraint satisfaction is a decision problem Task: make decisions without violating constraints Sometimes you want the “best” solution Main techniques: constraint propagation + heuristics Variables (Decisions) Domains (Values available) Constraints On assignments x1x1 x2x2 x3x3 x4x4 X X X X

10. BT’s Workforce Scheduling BT has many jobs to be done in UK every day. It has to schedule a large number of teams to serve these jobs, subject to time, skill and other constraints. Saving of 0.5% could mean Millions of Pounds per year. Guided Local Search achieved the best results in one of BT’s challenge problems. Technicians Jobs

11. Foundations of Constraint Satisfaction First book to define the scope of constraint satisfaction –Published 1993 Arguably the most rigorous book in constraint satisfaction All major concepts defined in First Order Predicate Calculus –Precise, unambiguous –Little room for error