Search

Robustness of optimal solutions when solving network design problems is of great importance because of uncertainty in future demand. In this research the optimization of infrastructure planning in a multimodal passenger transportation network is defined as a multiobjective network design problem, with accessibility, use of urban space by parking, operating deficit and climate impact as objectives. In a case study in the city region of Amsterdam in The Netherlands, the location of park and ride facilities, train stations and the frequency of public transport lines are decision variables. The Pareto set is approximated by the Epsilon Non-dominated Sorting Genetic Algorithm (ε-NSGAII). In this case study, a demand forecast for 2030 is used, but the underlying demand model always contains uncertainty to a certain extent. Therefore, the differences are analyzed between Pareto sets resulting from solving the network design problem using two other demand scenarios as well: a 2020 demand prediction and a Transit-Oriented Development scenario. The Pareto solutions resulting from one demand scenario are assessed based on a different demand scenario to test whether they are still Pareto optimal under this different demand scenario. Furthermore, the values of the decision variables of the solutions in the sets are compared. Results indicate that a different transportation demand has a strong influence on the Pareto optimal performance of solutions in the set: 70% of the solutions do not perform Pareto optimal any more if assessed using a different transportation demand. However, the loss in objective function values is small (a 2% decrease in hypervolume value), so although performance is not optimal any more in most cases, loss in performance is limited. In addition, the resulting decision variables are relatively insensitive for transportation demand.

In recent years, simulation has become an essential tool for planning, designing, and managing terminal operations. Simulation modeling of various aspects related to the dynamic nature of the pedestrian/passenger behavior within a transport terminal can effectively assist in the analysis, evaluation, emergency response planning, and decision support phases of the terminal's operation. In this paper, the development of an object-oriented environment that enables both the graphical description and simulation of pedestrian traffic flows at the microscopic level is discussed. The simulation environment provides generation capabilities so that a terminal station model is directly formed on the basis of preconstructed component models. Essential experimentation capabilities, including graphical representation, are provided for pedestrian-oriented and system-oriented measures of interest with explicit emphasis on the level of service. A case study for a 4-level station in the new Athens subway system is also used to demonstrate the potential and functionality of the simulation environment.

Conference of 1st International Conference on Engineering and Applied Sciences Optimization, OPT-i 2014 ; Conference Date: 4 June 2014 Through 6 June 2014; Conference Code:108723; International audience; The design of Micro Electro Mechanical Systems (MEMS) is often based on the use of costly trial and error method which depends highly on the technical skills of the involved engineers. The drawback of such a procedure is to lead to sub-optimal designs and poor performance at the end. Some research works on dedicated optimization tools have begun a few years ago. The present paper deals with the development of a dedicated optimal design tool for monolithic MEMS, fabricated using the Silicon On Insulator (SOI) process. This tool is an evolution of a previously developed heuristic method, using a multi-objective evolutionary algorithm and a compliant building blocks library. It has been adapted and implemented in the MEMS design software called FlexIn SOI (Flexible Innovation for SOI), which account for the anisotropic elastic behavior of the Single Cristal Silicon material for the Finite Element evaluation of the fitness functions involved in the optimization process. To illustrate the usefulness of this tool, the automatic optimal design of a monolithic microgripper has been investigated. Here, the micro-fabrication process resolution is defined as an optimization constraint. Five dedicated objective functions have been considered to quantify real performances of the gripper, and also to be able to consider the use recommendations of associated inter-digital actuators and sensors. At the end of the optimization process, the nonlinear comb-drive actuator stiffness has been considered to select an electromechanically stable solution among Pareto front. This solution has been prototyped and characterized. It showed very outstanding performances regarding state-of-the-art micro-grippers [1], thus validating the proposed optimal design method.

In this paper topology optimization for cooling by finned heat sinks is studied. To this end, a two-layer model is elaborated based on the full 3D Navier-Stokes and heat conduction equations. The optimization is performed using the MMA method with gradients computed based on a continuous adjoint approach. Results reveal a reduction of the thermal resistance by more than a factor of 10 in comparison with a heat sink without fins. ispartof: pages:562-577 ispartof: OPT-i 2014 - 1st International Conference on Engineering and Applied Sciences Optimization, Proceedings pages:562-577 ispartof: International Conference on Engineering and Applied Sciences Optimization location:Kos Island (Greece) date:4 Jun - 6 Jun 2014 status: published