The Complexity of Integrating Routing Decisions in Public Transportation Models

To model and solve optimization problems arising in public transportation, data about the passengers is necessary and has to be included in the models in any phase of the planning process. Many approaches assume a two-step procedure: in a first step, the data about the passengers is distributed over the public transportation network using traffic-assignment procedures. In a second step, the actual planning of lines, timetables, etc. takes place. This approach ignores that for most passengers there are many possible ways to reach their destinations in the public transportation network, thus the actual connections the passengers will take depend strongly on the decisions made during the planning phase. In this paper we investigate the influence of integrating the traffic assignment procedure in the optimization process on the complexity of line planning and aperiodic timetabling. In both problems, our objective is to maximize the passengers\u27 benefit, namely to minimize the overall travel time of the passengers in the network. We present new models, analyze NP-hardness results arising from the integration of the routing decisions in the traditional models, and derive polynomial algorithms for special cases

Integrated Optimization of Service-Oriented Train Plan and Schedule on Intercity Rail Network with Varying Demand

For a better service level of a train operating plan, we propose an integrated optimization method of train planning and train scheduling, which generally are optimized, respectively. Based on the cost analysis of both passengers travelling and enterprises operation, and the constraint analysis of trains operation, we construct a multiobjective function and build an integrated optimization model with the aim of reducing both passenger travel costs and enterprise operating costs. Then, a solving algorithm is established based on the simulated annealing algorithm. Finally, using as an example the Changzhutan intercity rail network, as an example we analyze the optimized results and the influence of the model parameters on the results

The capacitated Lot Sizing model: A powerful tool for logistics decision making

Starting from the seminal intuitions that led to the developments of the Economic Order Quantity model and of the formulation of the Dynamic Lot Sizing Problem, inventory models have been widely employed in the academic literature and in corporate practice to solve a wide range of theoretical and real-world problems, as, through simple modifications to the original models, it is possible to accommodate and describe a broad set of situations taking place in complex supply chains and logistics systems. The aim of this paper is to highlight, once more, the powerfulness of these seminal contributions by showing how the mathematical formulation of the Capacitated Lot Sizing Problem can be easily adapted to solve some further practical logistics applications (mainly arising in the field of coordination of transportation services) not strictly related to manufacturing and production environment. Mathematical formulations and computational experiences will be provided to support these statements. © 2014 Elsevier B.V. All rights reserved