Studies on integer optimization in emergency management have attracted engineers and scientists from various disciplines such as management, mathematics, computer science, and other fields. Although there are a large number of literature reports on integer planning and emergency events, few books systematically explain the combination of the two. Researchers need a clear and thorough presentation of the theory and application of integer programming methods for emergency management. Integer Optimization and its Computation in Emergency Management investigates the computation theory of integer optimization, developing integer programming methods for emergency management and explores related practical applications. Pursuing a holistic approach, this book establishes a fundamental framework for this topic, intended for graduate students who are interested in operations research and optimization, researchers investigating emergency management, and algorithm design engineers working on integer programming or other optimization applications. Investigates computation theory of integer optimization and integer programming methods for emergency management and related practical applications Systematically provides background and potential applications of integer programming in emergency events, providing specific calculation frameworks and examples Provides a clear and thorough presentation of the theory and application of integer programming methods for emergency management through a holistic approach, establishing a fundamental framework of the topic for the audience INDICE: 1. Distributed implementation of the fixed-point method for integer optimization in emergency management 2. Computing all pure-strategy Nash equilibrium using mixed 0-1 linear programming approach 3. Computing all mixed-strategy Nash equilibrium using mixed integer linear programming approach 4. Solving long haul airline disruption problem caused by groundings using a distributed fixed-point approach 5. Solving multiple fleet airline disruption problems using a distributed computation approach 6. A deterministic annealing neural network algorithm for the minimum concave cost transportation problem 7. An approximation algorithm for graph partitioning via deterministic annealing neural network 8. A Logarithmic descent direction algorithm for the Quadratic Knapsack Problem
- ISBN: 978-0-323-95203-3
- Editorial: Academic Press
- Encuadernacion: Rústica
- Páginas: 300
- Fecha Publicación: 01/04/2023
- Nº Volúmenes: 1
- Idioma: Inglés