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

April 19, 2023Edward Tsang (Copyright)

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.

– Honda: Multi-objective optimization

Sponsors: BT, Honda Europe

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)

Sponsors: Sharescope, BT, OANDA

Research Profile, Edward Tsang

Application Technology

Finite Choices Decision Support, e.g. Assignment, Scheduling, Routing

Constraint Satisfaction, Optimisation, Heuristic Search (Guided Local Search)

Financial Forecasting Genetic Programming

Automated Bargaining Genetic Programming

Wind Tunnel Testing for designing markets and finding winning strategies

Mathematical Modelling, Machine Learning, Experimental Design

Portfolio Optimisation Multi-objectives Optimisation

Business Applications of Artificial Intelligence

Supplementary Information

Edward Tsang

Current Activities – Edward Tsang

Current Projects:• EDDIE for Forecasting – towards more complex trading strategies

• Automated bargaining – finding Nash equilibrium strategies

• Artificial markets – conditions for stylised facts

• Credit cards market – designing bank strategies and Government policies

• Market-based scheduling – for BT work force scheduling

• Evolving middlemen strategies – for simple supply chains (BT sponsored)

• Chance discovery – data mining for scarce opportunities

• Port automated – vehicles scheduling

• Multi-objective optimisation – for Honda’s industrial design

• Portfolio optimisation by heuristic search

Constraint Satisfaction & Optimisation Computational FinanceResearch Groups:

Affiliations: Professor Director 1/8/2009

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 Computation – Journal of Scheduling – CONSTRAINTS

• Chair, IEEE Computational Finance and Economics Technical Committee, 2004 & 2005

• Co-chair, IEEE Taskforce on Portfolio Optimisation, 2006-

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

x1

x2

x3

x4

X

X

X

X

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

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