Tractor and Semitrailer Routing Problem of Highway Port Networks under Unbalanced Demand

In China, highway port networks are essential in carrying out tractor and semitrailer transportation operations. To analyze the characteristics of tractor and semitrailer routing in highway port networks, this study examined the situation in which the demands at both ends of the operation might be unbalanced and multiple requirements might be raised in the operation of tractor and semitrailer transportation. An optimal tractor and semitrailer routing model for an entire network was established to reduce the total transportation costs and the number of towing vehicles in the network. Moreover, a heuristic algorithm was designed to solve the model. The comparisons of Strategy 1 and Strategy 2 for a two-stage network swap trailer show that the number of pure network swaps trailer tractors decreases by 21.6% and 18.6%, respectively; and that the cost drops by 7.8% and 7.9%, respectively. In other words, swap trailer transport enterprises can abandon the original swap trailer transportation mode for a two-stage network and adopt a routing optimization strategy for an entire network to achieve superior operation performance, reduce costs, and enhance profits. The study provides a reference for optimizing tractor and semitrailer routing in highway port networks with balanced and multiple demands

Multi-Criteria Optimization for Fleet Size with Environmental Aspects

[EN] This research concerns multi-criteria vehicle routing problems. Mathematical models are formulated with mixed-integer programming. We consider maximization of capacity of truck vs. minimization of utilization of fuel, carbon emission and production of noise. The problems deal with green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country and La Rioja, Spain. We consider heterogeneous fleet of trucks. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Companies planning delivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, utilization of fuel, carbon emission and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution.This work has been partially supported by the National Research Center (NCN), Poland (DEC2013/11/B/ST8/04458), by AGH, and by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180- C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grants CAN2014-3758 and CAN2015-70473). The authors are grateful to anonymous reviewers for their comments.Sawik, B.; Faulin, J.; Pérez-Bernabeu, E. (2017). Multi-Criteria Optimization for Fleet Size with Environmental Aspects. Transportation Research Procedia. 27:61-68. https://doi.org/10.1016/j.trpro.2017.12.05661682

Routing of hazardous material carrying vehicles

A number of accidents in the last two decades have increased public awareness of potential risks associated with hazardous material transport. Consequently, the safety management of this activity has become an issue of major importance. This paper presents a methodology and case study of Rourkela, which is to contribute a national action plan for hazardous material transport for Rourkela Steel Plant (RSP) .The main objective, is to develop a planning system for hazardous material transport. The planning system considers both economic and risk values. Risk assessment for the route system is discussed. Firstly, hazardous material identification and classification is studied and international norms for accidents of hazardous material carrying vehicle and their influence on routing decision are briefly described. . The consequences of the hazardous material accident are explosion, heat radiation, and toxicity. Secondly, intelligence phase is mainly used to understand the problem. GIS played an important role in risk assessment. The elements at risk include population, buildings and economic activitiesThirdly, Buffer analysis is done to identify the potentially hazardous road locations and necessary preventive measures are suggested for this. Accident rate is calculated from Crossthwaite, Fitzpatrick, TNO, and Gaussian equation considering the preventive measures for hazardous material carrying vehicles. The new accident rate calculated by using the above mentioned formula was compared with the previous 7 years data sets obtained from different police stations. The results obtained from the present method are promising. The buffer analysis will be helpful for traffic planners to take decisions correctly in case of any future research in that area

Container Swap Trailer Transportation Routing Problem Based on Genetic Algorithm

In swap trailer transportation routing problems, trucks and trailers conduct swap operations at special positions called trailer points. The parallelization of stevedoring and transportation can be achieved by means of these trailer points. This logistics organization mode can be more effective than the others. In this paper, an integer programming model with capacity and time-window constraints was established. A repairing strategy is embedded in the genetic algorithm (GA) to solve the model. The repairing strategy is executed after the crossover and mutation operation to eliminate the illegal routes. Furthermore, a parameter self-adaptive adjustment policy is designed to improve the convergence. Then numerical experiments are implemented based on the generated datasets; the performance and robustness of the algorithm parameter self-adaptive adjustment policy are discussed. Finally, the results show that the improved algorithm performs better than elementary GA

Evolutionary computing for routing and scheduling applications

Ph.DDOCTOR OF PHILOSOPH

Municipal solid-waste collection and disposal management using geospatial techniques in Maseru City, Lesotho

The use of geospatial techniques plays a crucial role in solid waste management. Collection and transportation of solid waste must be done in an efficient manner to avoid negative environmental impacts. At the time of study, there are no collection and routing system in Maseru City, leading to haphazard collection and disposal of Municipal Solid Waste (MSW). The aims of the study are: (i) To get an understanding and address the challenges faced by relevant stakeholders in solid waste management for Maseru City, (ii) To minimize adverse environmental impacts due to unscientific location of a disposal site and (iii) To minimize transportation costs and time during collection. The objectives of this study are summarized in the following: assess the current solid waste management, model suitable disposal/dump sites, determine MSW collection points and develop an optimal route for MSW collection and disposal in Maseru City. To assess the current solid waste management, 130 households, 73 community waste pickers, 15 Maseru City Council (MCC) management staff and 3 drivers were interviewed, and relevant data collected. Both primary and secondary data collection methods were used. Primary data collection methods included interviews, questionnaires and observations and creating feature classes in a geo database. Secondary data collection was done from relevant government repositories, digitization, and internet web sites. Simple random, area, cluster, and convenience sampling techniques were applied. Geographical Information Systems (GIS) and Remote sensing techniques were used to carry out suitability and network analysis, and location of MSW collection points. The study found out that the dump site (Ts'osane) was used by MCC and was not suitably located, hence more suitable alternative dump sites have been proposed. However, Ts'osane dump site was adopted in the analysis as it is the one used by MCC at the time of study. The researcher also found out that there were no designated MSW collection points and optimal routes, and that solid waste collection was done by both MCC and CBOs. In this regard, 334 collection points have been determined based on population and generated solid waste per Constituency and were randomly located in the study area. However, due to the policy that within 25m from the road no development could take place, only collection points which fell v within 25m from the road were selected and used in the routing analysis. One truck was used in the analysis, although more trucks could be used as it was at the time of study. For future research, there is a need to research on policy so that criteria for locating solid waste disposal and location of collection points is explicitly specified in the law to be able to conduct scientific analyses. A multi modal network analysis that would include all the vehicles used by MCC and the CBOs to develop a comprehensive network analysis that would also include necessary attributes such as road names, type, class, and length is needed

Revisión de la literatura del problema de ruteo de vehículos en un contexto de transporte verde

In the efficient management of the supply chain the optimal management of transport of consumables and finished products appears. The costs associated with transport have direct impact on the final value consumers must pay, which in addition to requiring competitive products also demand that they are generated in environmentally friendly organizations. Aware of this reality, this document is intended to be a starting point for Master’s and Doctoral degree students who want to work in a line of research recently proposed: green routing. The state of the art of the vehicle routing problem is presented in this paper, listing its variants, models and methodologies for solution. Furthermore, the proposed interaction between variants of classical routing problems and environmental effects of its operations, known in the literature as Green- VRP is presented. The goal is to generate a discussion in which mathematical models and solution strategies that can be applied within organizations that consider within their objectives an efficient and sustainable operation are posed.En el gerenciamiento eficiente de la cadena de suministro aparece la gestión óptima del transporte de insumos y productos terminados. Los costos asociados al transporte tienen impacto directo sobre el valor final que deben pagar los consumidores, que además de requerir productos competitivos también exigen que los mismos sean generados en organizaciones amigables con el medioambiente. Consientes de esa realidad este documento pretende ser un punto de partida para estudiantes de maestría y doctorado que quieran trabajar en una línea de investigación propuesta recientemente: el ruteo verde. En este trabajo se muestra un estado del arte del problema de ruteo de vehículos, enumerando sus variantes, modelos y metodologías de solución. Además, se presenta la interacción que se ha propuesto entre variantes clásicas de los problemas de ruteo y los efectos ambientales de su operación, denominados en la literatura como Green-VRP. El objetivo es generar una discusión donde se planteen modelos matemáticos y estrategias de solución que puedan ser aplicadas en organizaciones que consideren dentro de sus objetivos una operación eficiente y sustentable

Hybrid metaheuristics for solving multi-depot pickup and delivery problems

In today's logistics businesses, increasing petrol prices, fierce competition, dynamic business environments and volume volatility put pressure on logistics service providers (LSPs) or third party logistics providers (3PLs) to be efficient, differentiated, adaptive, and horizontally collaborative in order to survive and remain competitive. In this climate, efficient computerised-decision support tools play an essential role. Especially, for freight transportation, e efficiently solving a Pickup and Delivery Problem (PDP) and its variants by an optimisation engine is the core capability required in making operational planning and decisions. For PDPs, it is required to determine minimum-cost routes to serve a number of requests, each associated with paired pickup and delivery points. A robust solution method for solving PDPs is crucial to the success of implementing decision support tools, which are integrated with Geographic Information System (GIS) and Fleet Telematics so that the flexibility, agility, visibility and transparency are fulfilled. If these tools are effectively implemented, competitive advantage can be gained in the area of cost leadership and service differentiation. In this research, variants of PDPs, which multiple depots or providers are considered, are investigated. These are so called Multi-depot Pickup and Delivery Problems (MDPDPs). To increase geographical coverage, continue growth and encourage horizontal collaboration, efficiently solving the MDPDPs is vital to operational planning and its total costs. This research deals with designing optimisation algorithms for solving a variety of real-world applications. Mixed Integer Linear Programming (MILP) formulations of the MDPDPs are presented. Due to being NP-hard, the computational time for solving by exact methods becomes prohibitive. Several metaheuristics and hybrid metaheuristics are investigated in this thesis. The extensive computational experiments are carried out to demonstrate their speed, preciseness and robustness.Open Acces