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Advanced Constraint Programming with Java

Master constraint programming techniques to solve complex optimization problems in scheduling, routing, and resource allocation.

Master constraint programming techniques to solve complex optimization problems in scheduling, routing, and resource allocation.

This advanced course provides comprehensive training in constraint programming, focusing on solving complex combinatorial optimization problems. Students will develop a custom constraint programming solver in Java, learning to implement various constraints and search strategies. The course covers essential topics from basic backtracking to advanced concepts like global constraints, scheduling, and vehicle routing problems. Through hands-on projects, participants will gain practical experience in designing efficient algorithms for resource optimization, making this course valuable for those seeking to tackle complex computational challenges.

Instructors:

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Advanced Constraint Programming with Java

This course includes

14 Weeks

Of Self-paced video lessons

Advanced Level

Completion Certificate

awarded on course completion

8,441

What you'll learn

  • Understand the constraint programming paradigm and its applications

  • Design and implement a modern constraint programming library

  • Develop efficient modeling techniques using constraint programming

  • Implement new global constraints and extend solver capabilities

  • Create custom and black-box search strategies

  • Solve complex scheduling and vehicle routing problems

Skills you'll gain

Constraint Programming
Java Development
Algorithm Design
Optimization
Scheduling
Vehicle Routing
Search Strategies
Resource Allocation

This course includes:

PreRecorded video

Graded assignments, exams

Access on Mobile, Tablet, Desktop

Limited Access access

Shareable certificate

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There are 10 modules in this course

This comprehensive course delves into the principles and applications of constraint programming for solving complex optimization problems. The curriculum progressively builds from fundamental concepts to advanced techniques, teaching students to design and implement their own constraint programming library in Java. Through a project-based approach, participants learn about global constraints, search strategies, and practical applications in scheduling and vehicle routing. The course emphasizes both theoretical understanding and practical implementation, providing students with hands-on experience in developing efficient solutions for real-world optimization challenges.

From Backtracking Search to the Constraint Programming Paradigm

Module 1

Introduction to Mini-CP

Module 2

The sum and element global constraints

Module 3

The extensional table constraint

Module 4

The alldifferent constraint

Module 5

The Circuit constraint and Vehicle Routing Problems (VRP)

Module 6

Cumulative Scheduling Problems

Module 7

Disjunctive Scheduling Problems

Module 8

Blackbox Search

Module 9

Modeling

Module 10

Fee Structure

Instructors

Distinguished Computer Science Expert and Optimization Specialist

Pierre Schaus serves as Professor of Computer Science at UCLouvain, where he specializes in artificial intelligence, optimization, constraint programming, and machine learning. His research focuses on developing efficient algorithms for scheduling, vehicle routing, and combinatorial optimization problems. As the instructor of UCLouvain's constraint programming course, he teaches advanced concepts in solver architecture, search techniques, and practical applications. His contributions include pioneering work in solving over-constrained problems through the Variable Objective Large Neighborhood Search (VO-LNS) framework. He maintains an active research program developing practical approaches to complex optimization challenges while leading the development of educational resources including the minicp.org platform. His expertise spans theoretical foundations and practical applications of constraint programming, particularly in areas of scheduling and resource allocation.

Distinguished Computer Science Expert and Optimization Specialist

Laurent Michel serves as Professor of Computer Science at the University of Connecticut and co-Director of the Connecticut Advanced Computing Center. After completing his education at Notre-Dame de la Paix (Belgium) and Brown University, where he earned his PhD in 1999, he has established himself as a leading researcher in constraint programming and optimization. His research focuses on developing domain-specific languages for combinatorial optimization, with significant contributions to constraint-based local search and optimization modeling. His work includes pioneering publications in constraint programming, including "Constraint-based Local Search" and "Numerica: A Modeling Language for Global Optimization" published by MIT Press. As an educator and researcher since joining UConn in 2002, he has contributed to various fields including power systems optimization, warehouse location problems, and transparent parallelization of constraint programming. His research has garnered over 5,000 citations, demonstrating his significant impact on the field of computer science and optimization

Advanced Constraint Programming with Java

This course includes

14 Weeks

Of Self-paced video lessons

Advanced Level

Completion Certificate

awarded on course completion

8,441

Testimonials

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Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.