Optimization for Decision Making II

In the current context of the electronic governance of society, both administrations and citizens are demanding the greater participation of all the actors involved in the decision-making process relative to the governance of society. This book presents collective works published in the recent Special Issue (SI) entitled “Optimization for Decision Making II”. These works give an appropriate response to the new challenges raised, the decision-making process can be done by applying different methods and tools, as well as using different objectives. In real-life problems, the formulation of decision-making problems and the application of optimization techniques to support decisions are particularly complex and a wide range of optimization techniques and methodologies are used to minimize risks, improve quality in making decisions or, in general, to solve problems. In addition, a sensitivity or robustness analysis should be done to validate/analyze the influence of uncertainty regarding decision-making. This book brings together a collection of inter-/multi-disciplinary works applied to the optimization of decision making in a coherent manner

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

ATC work shift scheduling using multistart simulated annealing and regular expressions

In this paper, we propose a new approach for solving the air traffic controller (ATC) work shift scheduling problem, which minimizes the number of ATCs required to cover a given airspace sectoring, while satisfying a set of ATC labor conditions. This optimization problem belongs to the class of timetabling problems. The size and complexity of these combinatorial problems make them hard or even impossible to solve with exact methods. In the proposed approach, initial feasible solutions are first built using a heuristic based on optimized templates, and then multistart simulated annealing is used to reach optimal solutions. In the search process, we use regular expressions to check the feasibility of the generated solutions. This provides high testing speed and modularity for a clear and maintainable implementation of the optimization model. Once the optimal ATC number is reached in one or more solutions, they are used as the initial solutions for a new optimization process aimed at balancing the ATC workloads. The proposed approach is illustrated using a real example, and the optimal solution reached outperforms the reference solution, i.e. a real solution derived from the currently used tools based on templates. Indeed, one less ATC is needed to cover the airspace sectoring, and the ATC workloads are more balanced

ATC work shift scheduling using multistart simulated annealing and regular expressions

In this paper, we propose a new approach for solving the air traffic controller (ATC) work shift scheduling problem, which minimizes the number of ATCs required to cover a given airspace sectoring, while satisfying a set of ATC labor conditions. This optimization problem belongs to the class of timetabling problems. The size and complexity of these combinatorial problems make them hard or even impossible to solve with exact methods. In the proposed approach, initial feasible solutions are first built using a heuristic based on optimized templates, and then multistart simulated annealing is used to reach optimal solutions. In the search process, we use regular expressions to check the feasibility of the generated solutions. This provides high testing speed and modularity for a clear and maintainable implementation of the optimization model. Once the optimal ATC number is reached in one or more solutions, they are used as the initial solutions for a new optimization process aimed at balancing the ATC workloads. The proposed approach is illustrated using a real example, and the optimal solution reached outperforms the reference solution, i.e. a real solution derived from the currently used tools based on templates. Indeed, one less ATC is needed to cover the airspace sectoring, and the ATC workloads are more balanced