The Tractor and Semitrailer Routing Considering Carbon Dioxide Emissions

The incorporation of the minimization of carbon dioxide (CO2) emissions in the VRP is important to logistics companies. The paper deals with the tractor and semitrailer routing problem with full truckload between any two depots of the network; an integer programming model with the objective of minimizing CO2 emissions per ton-kilometer is proposed. A two-stage approach with the same core steps of the simulated annealing (SA) in both stages is designed. The number of tractors is provided in the first stage and the CO2 emissions per ton-kilometer are then optimized in the second stage. Computational experiments on small-scale randomly generated instances supported the feasibility and validity of the heuristic algorithm. To a practical-scale problem, the SA algorithm can provide advice on the number of tractors, the routes, and the location of the central depot to realize CO2 emissions decrease

A evolutionary algorithm for dynamically optimisation of drayage operations

Proper planning of drayage operations is fundamental in the quest for the economic viability of intermodal freight transport. The work we present here is a dynamic optimization model which uses real-time knowledge of the fleet's position, permanently enabling the planner to reallocate tasks as the problem conditions change. Stochastic trip times are considered, both in the completion of each task and between tasks

Heterogeneous truck routing policies with tour routing time restriction

We study a heterogeneous full-truckload vehicle routing problem based on the case of a trucking company in Malaysia, where trucks originate from a depot and are dispatched to various parts of the service area. Each order defines an origin-destination pair for pickup and delivery locations. Goods have to be picked up or delivered within the pre-specified pickup and delivery time windows. Besides, we consider a restriction on tour routing time, i.e. the total time taken from the time each truck leaves the depot, servicing a number of orders, to the time it returns to the depot. Our objective is to minimize total deadhead costs. Four integer programming solution policies are proposed. Three of the policies identify the set of homebound trucks before assigning jobs to trucks, while the last policy is a one-off algorithm that assigns job routes to all the trucks and makes sure that each truck will not exceed the total route time limit when it returns to the depot. Crosssectional computation results show that the one-off policy is the best amongst the four. Cumulative analysis results show that all four policies do better than the company’s original assignment in terms of deadhead costs and truck utilization

Waste Collection Vehicle Routing Problem: Literature Review

Waste generation is an issue which has caused wide public concern in modern societies, not only for the quantitative rise of the amount of waste generated, but also for the increasing complexity of some products and components. Waste collection is a highly relevant activity in the reverse logistics system and how to collect waste in an efficient way is an area that needs to be improved. This paper analyzes the major contribution about Waste Collection Vehicle Routing Problem (WCVRP) in literature. Based on a classification of waste collection (residential, commercial and industrial), firstly the key findings for these three types of waste collection are presented. Therefore, according to the model (Node Routing Problems and Arc Routing problems) used to represent WCVRP, different methods and techniques are analyzed in this paper to solve WCVRP. This paper attempts to serve as a roadmap of research literature produced in the field of WCVRP

Impacto del conocimiento en tiempo real de la posición de una flota de vehículos sobre la mejora de acarreo intermodal

Este artículo resuelve el problema del acarreo en una red con enlaces cuya duración es estocástica. Y pone de relieve la importancia del conocimiento en tiempo real de la posición exacta de los vehículos de la flota para llevar a cabo una correcta asignación de tareas a la misma. El modelo tiene un carácter dinámico al ser capaz de reasignar tareas a medida que se conocen datos con mayor certeza

A Genetic Algorithm for Real-Time Optimisation of Drayage Operations

Proper planning of drayage operations is fundamental in the quest for the economic viability of intermodal freight transport. The work we present here is a dynamic optimization model which uses real-time knowledge of the fleet’s position, permanently enabling the planner to reallocate tasks as the problem conditions change. Stochastic trip times are considered, both in the completion of each task and between tasks

Knowledge of Real Time Position of Vehicles and Its Impact on the Improvement of Intermodal Drayage Operations

Libro de abstracts en la web del congreso: http://www.civil.ist.utl.pt/wctr12_lisboa/int_04_program_conference.htmThe intermodal transport chain can become more efficient by means of a good organization of the drayage movements. Drayage in intermodal container terminals involves the pick up or delivery of containers at customer locations. There are some works on centralised drayage management, but most of them consider the problem only from a static and deterministic perspective. The main objective is normally the assignment of transportation tasks to the different vehicles, often with the presence of time windows. The work we present here considers the knowledge of the vehicles’ real-time position, which permanently enables the planner to reassign tasks in case the problem conditions change. This exact knowledge of position of the vehicles is possible thanks to a geographic positioning system by satellite (GPS, Galileo, Glonass). This additional data are used to dynamically improve the solution

Dynamic optimisation of urban intermodal freight transport with random transit times, flexible tasks and time windows

Es una ponencia de The Sixth International Conference on City Logistics, en Puerto Vallarta, México http://toc.proceedings.com/18996webtoc.pdfAn improvement on drayage operations is necessary for intermodal freight transport to become competitive. When drayage takes place in cities or urban centres transit times are usually random, as a consequence finding the optimal fleet schedule is very difficult, and this schedule can even change during the day. The work we present here is a dynamic optimisation model which uses real-time knowledge of the fleet’s position, permanently enabling the planner to reallocate tasks as the problem conditions change. Stochastic trip times are considered, both in the completion of each task and between tasks. Tasks can also be flexible or well-defined. We describe the algorithm in detail for a test problem and then apply it to a set of random drayage problems of different size and characteristics, obtaining significant cost reductions with respect to initial estimates.Junta de Andalucía SR0197/200

The Effects of the Tractor and Semitrailer Routing Problem on Mitigation of Carbon Dioxide Emissions

The incorporation of CO2 emissions minimization in the vehicle routing problem (VRP) is of critical importance to enterprise practice. Focusing on the tractor and semitrailer routing problem with full truckloads between any two terminals of the network, this paper proposes a mathematical programming model with the objective of minimizing CO2 emissions per ton-kilometer. A simulated annealing (SA) algorithm is given to solve practical-scale problems. To evaluate the performance of the proposed algorithm, a lower bound is developed. Computational experiments on various problems generated randomly and a realistic instance are conducted. The results show that the proposed methods are effective and the algorithm can provide reasonable solutions within an acceptable computational time