Miguel Mujica Mota

Large Neighbourhood Search and Simulation for Disruption Management in the Airline Industry

The airline industry is one of the most affected by operational disruptions, defined as deviations from originally planned operations. Due to airlines network configuration, delays are rapidly propagated to connecting flights, substantially increasing unexpected costs for the airlines. The goal in these situations is therefore to minimise the impact of the disruption, reducing delays and the number of affected flights, crews and passengers. In this chapter, we describe a methodology that tackles the Stochastic Aircraft Recovery Problem, which considers the stochastic nature of air transportation systems. We define an optimisation approach based on the Large Neighbourhood Search metaheuristic, combined with simulation at different stages in order to ensure solutions’ robustness. We test our approach on a set of instances with different characteristics, including some instances originating from real data provided by a Spanish airline. In all cases, our approach performs better than a deterministic approach when system’s variability is considered.

Simulation-based capacity analysis for a future airport

The current article deals with the problem of assessing the practical capacity of an airport network. This problem is approached using simulation techniques taking into account not only the different mandatory variables which are imposed by the current legislation but also other factors that affect the practical capacity of the airport such as weather conditions. The model will be used for assessing the potential capacity problems that will be faced by the future airport. The article put focus on one airport of the North Holland region which is a good example of a region that struggles for allocating the growing traffic in the coming years.

Applied Simulation and Optimization 2

Presenting techniques, case-studies and methodologies that combine the use of simulation approaches with optimization techniques for facing problems in manufacturing, logistics, or aeronautical problems, this book provides solutions to common industrial problems in several fields, which range from manufacturing to aviation problems, where the common denominator is the combination of simulations flexibility with optimization techniques robustness.Providing readers with a comprehensive guide to tackle similar issues in industrial environments, this text explores novel ways to face industrial problems through hybrid approaches (simulation-optimization) that benefit from the advantages of both paradigms, in order to give solutions to important problems in service industry, production processes, or supply chains, such as scheduling, routing problems and resource allocations, among others.

Allocation of Airport Check-in Counters Using a Simulation-Optimization Approach

The aviation industry is expected to grow at a pace of 4 % per annum in the coming years, therefore it is necessary to have techniques that support the management of the resources at hand in the best possible way so that facility expansion is delayed as much as possible with the corresponding capital savings. This chapter presents a methodology that combines evolutionary algorithms and simulation for performing the allocation of the check-in desks in such a way that the different stochastic and deterministic variables are taken into account for a more robust solution. The evolutionary algorithm is developed to satisfy the different mandatory restrictions for the allocation problem such as minimum and maximum number of check-in desks per flight, load balance at the counters, opening times of check-in desks, and other restrictions imposed by the level of service agreement. Once the solutions are obtained, a second evaluation is performed using a simulation model of the terminal that takes into account the stochastic aspects of the problem such as passenger arrival profiles, passenger profile, layout of the facility, among others, with the purpose of determining an airport terminal’s check-in area which allocation is the most efficient in real situations to keep the quality indicators at the desired level. The example presented is for an airport terminal’s check-in area, but the methodology can be used for similar allocation problems in the aviation industry and in other industries such as logistics or manufacturing.

The Coupling of Coloured Petri Nets with SIMIO

This chapter is probably the one that makes the book different from others focused in Petri nets or Coloured Petri nets, since it introduces concepts and the methodology of how to integrate the Coloured Petri Nets (CPN) formalism with a discrete event-based simulation program like SIMIO.

Improving Airport Performance Through a Model-Based Analysis and Optimization Approach

Traditionally airport systems have been studied using an approach in which the different elements of the system are studied independently. Until recently scientific community has put attention in developing models and techniques that study the system using holistic approaches for understanding cause and effect relationships of the integral system. This chapter presents a case of an airport in which the authors have implemented an approach for improving the turnaround time of the operation. The novelty of the approach is that it uses a combination of simulation, parameter analysis and optimization for getting to the best amount of vehicles that minimize the turnaround time of the airport under study. In addition, the simulation model is such that it includes the most important elements within the aviation system, such as terminal manoeuvring area, runway, taxi networks, and ground handling operation. The results show clearly that the approach is suitable for a complex system in which the amount of variables makes it intractable for getting good solutions in reasonable time.

Optimization and simulation based approach for an arrival and departure manager tool

This work proposes a methodology for developing an airport arrival and departure manager tool. This methodology employs optimization together with simulation techniques for improving the robustness of the solution. An arrival and departure manager tool is intended to help air traffic controllers in managing the inbound and outbound traffic without incurring in conflicts or delays. In this context, air traffic controllers need to have a tool able to help them to make the right decisions in a short time horizon. The main decisions taken in the present methodology for each aircraft are: entry time and entry speed in the airspace and push back time at the gate. The objective of this methodology is to have a smooth flow of aircraft both in the airspace and on the ground. Preliminary tests were made using Paris Charles de Gaulle Airport as case study, and the results show that conflicts were sensibly reduced.

Specification of CPN models into MAS platform for the modelling of social policy issues: FUPOL project

Simulation transparency is becoming more crucial in the decision making process when quantitative computer tools are used to justify some strategies. The coloured petri net (CPN) formalism is a promising modelling approach to foster simulation transparency by means of state space traceability tools, which have been proven to be useful for modelling system dynamics with conflict patterns. E-governance is one of these areas in which the use of a multi agent system (MAS) to represent social dynamics in a certain urban context could be used to engage citizens in the design of urban policies that affects their habitat environment. In this paper a modelling methodology to represent and analyse a context-aware multi agent-based system, which tends to be highly complex is proposed. CPN models are used to specify citizen’s preferences and affinities in front of an urban contextual change, while MAS is used to evaluate the social dynamics by translating the CPN semantic rules into agent’s rules in NetLogo.