Network design is one of the crucial activity in transportation engineering whose goal is to determine an optimal solution to traffic network layout with respect to given objectives and technical and/or economic constraints. In most of the practical problem the input data are not always precisely known as well as the information is not available regarding certain input parameters that are part of a mathematical model. Also constraints can be stated in approximate or ambiguous way. Thus, starting data and/or the problem constraints can be affected by uncertainty. Uncertain values can be represented using of fuzzy values/constraints and then handled in the framework of fuzzy optimization theory. In this paper we present a fuzzy linear programming method to solve the optimal signal timing problem on congested urban. The problem is formulated as a fixed point optimization subject to fuzzy constraints. The method has been applied to a test network for the case of priority corridors that are used for improve transit and emergency services. A deep sensitivity analysis of the signal setting parameters is then provided. The method is compared to classical linear programming approach with crisp constraints
Design of Priority Transportation Corridor Under Uncertainty / Caggiani, L; Ottomanelli, M - In: Soft Computing in Industrial Applications: Proceedings of the 17th Online World Conference on Soft Computing in Industrial Applications / [a cura di] Snášel, V.; Krömer, P.; Köppen, M.; Schaefer, G.. - STAMPA. - Cham, CH : Springer, 2014. - ISBN 978-3-319-00929-2. - pp. 291-303 [10.1007/978-3-319-00930-8_26]
Design of Priority Transportation Corridor Under Uncertainty
Caggiani L;Ottomanelli M
2014-01-01
Abstract
Network design is one of the crucial activity in transportation engineering whose goal is to determine an optimal solution to traffic network layout with respect to given objectives and technical and/or economic constraints. In most of the practical problem the input data are not always precisely known as well as the information is not available regarding certain input parameters that are part of a mathematical model. Also constraints can be stated in approximate or ambiguous way. Thus, starting data and/or the problem constraints can be affected by uncertainty. Uncertain values can be represented using of fuzzy values/constraints and then handled in the framework of fuzzy optimization theory. In this paper we present a fuzzy linear programming method to solve the optimal signal timing problem on congested urban. The problem is formulated as a fixed point optimization subject to fuzzy constraints. The method has been applied to a test network for the case of priority corridors that are used for improve transit and emergency services. A deep sensitivity analysis of the signal setting parameters is then provided. The method is compared to classical linear programming approach with crisp constraintsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.