Optimization Of Complex Operations In Railway Marshalling Yards

Railroad yards,i.e.marshaling or shunting yards,play an important role as consolidation nodes in rail freight transportation networks.The performance of railroad yard operations is extremely important for railroad industries to consolidate and redistribute shipments efficiently.In this complex process,a critical technical document called railroad yard operations plan determines the schedule of various tasks within a railroad yard.A typical railway marshalling yard contains multiple layers of complex operations,which involve not only a large number of stationary facilities and motive equipments,but also the interaction with the trains outside the marshalling yard.The railcars coming with inbound trains through the yard need to be humped into different classification tracks according to the destination,and then assembled to generate the desired outbound trains.During this complex procedure,the processing time of railcars and various resource constraints at different railroad yard facilities could significantly affect the overall performance of yard operations,individually and in combination.It is theoretically challenging to represent a large number of practical operation rules through tractable mathematical programming models.In practice,the processing time of freight railcars in a railroad yard represents a large proportion of the total railroad end-to-end transportation or trip time,so continuously improving the efficiency of railroad yard operations has received significant attention by decision makers and operations researchers in the rail industry.The railroad yard operations plan problem(YOP)aims to design an optimal tactical task schedule of critical activities subject to different practical rules.Typically,the number of railcars processed during a certain period and the average waiting time(i.e.processing time)of railcars are important measures of effectiveness(MOE)of a railroad yard.There are a number of important practical constraints,e.g.,the maximum number of cars that can be stored in each track,or specific requirements related to the humping sequence for inbound trains and the combination of destinations for outbound trains.Moreover,the yard operation problem has to consider multiple types of commodities,e.g.,railcars,inbound trains and outbound trains,as well as the schedule sequences for two layers of servers:humping engines and pull-back engines.Thus,how to seamlessly integrate different layers of flow and activities has been a very challenging question,especially with respect to theoretically rigorous optimization models.Uncertain disturbances to a given yard operation plan are unavoidable to affect the performance of yard operation system,which may cause more waiting time costs of railcars or insufficient railcars for outbound train at scheduled departure time.Another challenge of YOP peoblem is how to optimize the robustness of the operation plan under uncertain disturbances according to the YOP objective function before the system starts to operate.This dissertation presents a comprehensive cumulative-flow based modelling framework for typical marshalling yard systems from a perspective of the space-time network.Based on the integrated modelling framework,a deterministic mixed integer programming model is developed to optimize YOP in railway marshalling yards.Considering a variety of random disturbance factors in the process of marshalling yard operations,a scenario-based stochastic programming model of yard operation plan is developed based on the robustness of critical decision-making plan under the impact of the uncertaint factors.Based on the analysis of the characteristics of the two integrated optimization models,solving methods and heuristic solving enhancement techniques were designed respectively.The dissertation covers the following contents:1.Analyze the complexity of railway marshalling yard operations and give the problem statement of yard operation plan.The dissertation analyzes the importantance of the railway marshalling yard in railway transportation network and highlight the complexity and significance of the comprehensive yard operation plan for railway marshalling yards.The first chapter gives the detailed problem statements for YOP and an overview of methods,optimization models,simulation techniques and practical applications in railway yard operation.The challenges,objectives,organizing sturture of the dissertation are also introduced in detail.2.Present a cumulative flow-based modeling framework for railway marshalling yards.Based on the systematic analysis of the multi-level operations process in railway marshalling yards,the railway yard system and operation requirements are illustrated from the perspective of time-space characteristics.An integrated modeling framework based on cumulative flow is introduced to describe the moving process of railcars passing through the railway yard system,the dynamic state of railway yard operation system,and the key requirements of the various operation activities.The operation mechanism of railway yard system and the continuous moving process of railcars are expressed by mathematical formulations.3.Present a deterministic integrated model for optimizing multi-level operations in railway marshalling yards.Based on the integrated modeling framework of railway yard operations,a deterministic mathematical optimization model for the integrated operation process is developed to to design an efficient operation schedule that can minimize the total processing time of railcars passing through the yard subject to different types of processing time constraints regarding the arrival operation of inbound trains,humping tasks for inbound train,sorting tasks for railcars,assembling task for railcars and departure operation for outbound trains.4.Develop a valid inequality-based solving method for relaxed models and an aggregated flow assignment model-based heuristic algorithm.From the perspective of mathematical characteristics in the proposed integer programming model,a novel lot-sizing modeling framework and related valid inequality formulations are introduced to model the assembling jobs for outbound trains,and the valid inequality based on lot-sizing problem is used to construct an optimization method for the model.From the perspective of railway yard operations,an aggregated now assignment model and earliest due date-based heuristic rules are developed to determine the humping jobs sequence for reducing the search space.5.Present a scenario-based stochastic programming model for yard operation plan under uncertainty.The marshalling yard operation plan is often interfered by various random factors,which may causes more waiting time costs or insufficient railcars for outbound trains departing from the marshalling yard.The outbound train may be delayed to depart or even cancelled.A strategic planning method based on discrete scenarios is applied to describe the uncertainty of yard technical parameters from a perspective of the robustness of decision-making plans.Under the strategic planning method,a stochastic programming optimization model for railway marshalling yard operations is developed to optimize the expected waiting time cost of railcars passing through the marshalling yard considering the discrete uncertainty scenarios of yard technical parameters.6.Numerical experiments are conducted to examine the solution quality and computational efficiency under different types of formulation strategies.An integrated data set of railway marshalling yard operations provided by INFORMS RAS 2013 is applied to test the deterministic optimization model and the stochastic mathematical model,and the performance effectiveness of proposed solving methods are demonstrated by the computational results and comparisons.