Lectures related to SAT Solver: Optimization Techniques

Boolean Satisfiability Problem: Solving Techniques

Explores the Boolean Satisfiability Problem and the Davis-Putnam-Logemann-Loveland algorithm, along with modern SAT solvers and efficient solving techniques.

Optimization Methods: Theory Discussion

Explores optimization methods, including unconstrained problems, linear programming, and heuristic approaches.

Optimisation in Energy Systems

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.

Optimization and Simulation

Explores optimization, simulation, heuristics, and Pareto solutions in multi-objective problems.

The String Game

Delves into the string game, showcasing the limitations of exhaustive testing and the importance of heuristics in problem-solving.

Optimization and Simulation: Heuristics and Neighborhoods

Explores greedy heuristics, neighborhoods in optimization, and local search algorithms.

Thermodynamic Properties: Equations and Models

Explains thermodynamic properties, equations of state, and mixture rules for energy systems modeling.

Optimization and Simulation

Explores transformations into single-objective functions, lexicographic rules, and constrained optimization in optimization and simulation.

Search Algorithms: Abductive Reasoning

Covers search algorithms, focusing on abductive reasoning and heuristic search strategies.

Optimization and Simulation

Explores optimization, simulation, data analysis, and the importance of considering more than just the mean in engineering systems.

Optimal Decision Making: Exercises and Applications

Covers exercises on optimal decision making, including minimizing costs and optimizing transportation networks.

Digitized and Born-Digital Sources in History

Explores the practice of history using digitized and born-digital sources, heuristics, critique, synthesis, and big data for historical analysis.

Search Algorithms: Abductive Reasoning

Explores abductive reasoning, search algorithms, and heuristic search for problem-solving.

Optimization in Large Search Spaces: GPU-Accelerated Join Order

Explores GPU-accelerated join order optimization in large search spaces, leveraging graph topology to reduce computational overheads.

Life Cycle Assessment Uncertainty

Explores the interpretation and limitations of Life Cycle Assessment, emphasizing the importance of addressing uncertainties to support decision-making.

Optimization Techniques: Local Search, VNS, Simulated Annealing

Explores optimization techniques like local search, VNS, and simulated annealing.

Optimization and Simulation: Simulated Annealing

Explores simulated annealing for optimization, emphasizing parameter tuning and diversification to escape local minima.

Deliberative Agents: Planning and Strategies

Covers planning with adversaries, heuristic search algorithms, and strategies for games with chance, emphasizing the significance of deliberative agents.

Solving Parity Games in Practice

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Constraint Satisfaction: Formulation and Algorithms

Covers the formulation of constraint satisfaction problems and systematic algorithms for solving them efficiently.