Determining the optimal location of control cabinet components requires the exploration of a large configuration space. For real-world control cabinets it is impractical to evaluate all possible cabinet configurations. Therefore, we need to apply methods for intelligent exploration of cabinet configuration space that enable to find a near-optimal configuration without evaluation of all possible configurations. In this paper, we describe an approach for multi-objective optimization of control cabinet layout that is based on Pareto Simulated Annealing. Optimization aims at minimizing the total wire length used for interconnection of components and the heat convection within the cabinet. We simulate heat convection to study the warm air flow within the control cabinet and determine the optimal position of components that generate heat during the operation. We evaluate and demonstrate the effectiveness of our approach empirically for various control cabinet sizes and usage scenarios.
Drexl and Nikulin @cite_17 use Pareto Simulated Annealing for solving the gate assignment problem in the context of an airport. Various aspects of airport operation are considered, such as, the total passenger walking distance, open flights, connection time, and gate assignment preferences.
@cite_17
2106120336
This paper addresses an airport gate assignment problem with multiple objectives. The objectives are to minimize the number of ungated flights and the total passenger walking distances or connection times as well as to maximize the total gate assignment preferences. The problem examined is an integer program with multiple objectives (one of them being quadratic) and quadratic constraints. Of course, such a problem is inherently difficult to solve. We tackle the problem by Pareto simulated annealing in order to get a representative approximation for the Pareto front. Results of computational experiments are presented. To the best of our knowledge, this is the first attempt to consider the airport gate assignment problem with multiple objectives. An anonymous Bluetooth tracking system was deployed at the new Indianapolis International Airport in Indiana from May 8 to June 2, 2009, to measure the time for passengers (a) to move from the nonsterile side of the airport (presecurity), (b) to clear the security screening checkpoint, and (c) to enter the walkway to Concourse B on the sterile side. The maximum passenger transit time between these checkpoints was observed on Monday mornings at approximately 0600, when it could take passengers up to 20 min to transit the security queue and screening and to walk to Concourse B. Depending on the day of the week, this approach was demonstrated to sample between 5 and 6.8 of passengers. This modest sample size provides a more robust measurement of screening times than the current system of manually distributing time-stamped cards as passengers enter the queue and collecting them where passengers pass through the magnetometer. Furthermore, because the final passenger reference point used in this study is on the sterile concourse, it captures the time associated with passengers repackaging their belongings and redonning their shoes. The data from this pilot study suggest the feasibility of using an automated system to provide quantitative information to managers for more effective allocation of scarce resources, as well as providing the traveling public with necessary information about the amount of time they should allocate for transiting the security screening process. The paper concludes by suggesting that additional pilot studies should be performed at several airports with alternative checkpoint configurations to develop a consensus on best practices for locating sensors to measure passage times at airport security screening. We present an ample description of a socially compliant mobile robotic platform, which is developed in the EU-funded project SPENCER. The purpose of this robot is to assist, inform and guide passengers in large and busy airports. One particular aim is to bring travellers of connecting flights conveniently and efficiently from their arrival gate to the passport control. The uniqueness of the project stems from the strong demand of service robots for this application with a large potential impact for the aviation industry on one side, and on the other side from the scientific advancements in social robotics, brought forward and achieved in SPENCER. The main contributions of SPENCER are novel methods to perceive, learn, and model human social behavior and to use this knowledge to plan appropriate actions in real-time for mobile platforms. In this paper, we describe how the project advances the fields of detection and tracking of individuals and groups, recognition of human social relations and activities, normative human behavior learning, socially-aware task and motion planning, learning socially annotated maps, and conducting empirical experiments to assess socio-psychological effects of normative robot behaviors. Emergency evacuation from airports is an important consideration given the continuing occurrence of both natural and human caused disasters. Unfortunately, the traditional evacuation-drill approach to prepare for emergency situations presents several practical challenges at the scale and magnitude required for airports. In this paper, we present an agent-based model (ABM) called exitus which is capable of determining the extent to which collective behavior and overall evacuation time of passenger groups is affected by changes in the built environment for large, complex structures. The model is unique because it explicitly considers the physical and psychological characteristics of individuals with disabilities. In our first experiment, several bomb simulation scenarios were conducted at an international airport using exitus. Several important findings were revealed including: 1) the importance of stairway and exit configurations; 2) the inherent weaknesses of the pier airport design in affecting timely evacuations; 3) who the most vulnerable groups of people are; 4) the particular risk engendered from crowded or complex building interiors for individuals with disabilities; and 5) the potential problems caused by locating explosive detection system machines near passenger processing areas. The results of a second exploratory experiment also revealed the importance of realistically modeling psychological attributes of individuals with disabilities and their potential impact on collective evacuation performance. Overall the findings demonstrated the model’s ability to generate a common operational picture capable of guiding preparedness efforts for both public and private organizations encompassing a wide variety of professional endeavor.