Using artificial neural networks for transport decisions: Managerial guidelines

One information technology that may be considered by transportation managers, and which is included in the portfolio of technologies that encompass TMS. is artificial neural networks (ANNs). These artificially intelligent computer decision support software provide solutions by finding and recognizing complex patterns in data. ANNs have been used successfully by transportation managers to forecast transportation demand, estimate future transport costs, schedule vehicles and shipments, route vehicles and classify earners for selection. Artificial neural networks excel in transportation decision environments that are dynamic, complex and unstructured. This article introduces ANNs to transport managers by describing ANN technological capabilities, reporting the current status of transportation neural network applications, presenting ANN applications that offer significant potential for future development and offering managerial guidelines for ANN development

Visualizing the influence of geography, oil and geopolitics on civil wars in the Arab world: A novel application of self-organizing maps and duration models

The aim of this paper is to investigate why some internal conflicts are terminated quickly, while others linger for several decades without a looming resolution in the horizon. In an attempt to achieve this objective, the role played by geopolitical factors in the Arab world's internal conflicts was investigated. More specifically, we used Kohonen self-organizing maps, an artificial intelligence-based neural network technique, along with event duration models to investigate the role played by distance from the capital, access to international borders, terrain, valuable natural resources such as oil, and rebels fighting capability in civil wars in the Arab world. Using recently validated data spanning more than 50 years of Arab civil wars (1948–2003), our findings indicate that previously ignored geopolitical factors seem to play an important role in the duration of internal conflicts in the Arab World

Meta-Heuristics for the Multiple Trip Vehicle Routing Problem with Backhauls

With the growing and more accessible computational power, the demand for robust and sophisticated computerised optimisation is increasing for logistical problems. By making good use of computational technologies, the research in this thesis concentrates on efficient fleet management by studying a class of vehicle routing problems and developing efficient solution algorithms. The literature review in this thesis looks at VRPs from various development angles. The search reveals that from the problem modelling side clear efforts are made to bring the classical VRP models closer to reality by developing various variants. However, apart from the real VRP applications (termed as 'rich' VRPs), it is also noticeable that these classical VRP based variants address merely one or two additional characteristics from the real routing problem issues, concentrating on either operational (fleet management) or tactical (fleet acquisition) aspects. This thesis certainly hopes to add to one of those good efforts which have helped in bringing the VRPs closer to reality through addressing both the operational as well as the tactical aspects. On the solution methodologies development side, the proposed research noted some considerable and impressive developments. Although, it is well established that the VRPs belong to the NP-hard combinatorial class of problems, there are considerable efforts on the development of exact methods. However the literature is full of a variety of heuristic methodologies including the classical and the most modern hybrid approaches. Among the hybrid approaches, the most recent one noted is mat-heuristics that combine heuristics and mathematical programming techniques to solve combinatorial optimisation problems. The mat-heuristics approaches appear to be comparatively in its infant age at this point in time. However this is an exciting area of research which seeks more attention in the literature. Hence, a good part of this research is devoted to the development of a hybrid approach that combines heuristics and mathematical programming techniques. When reviewing the specific literature on the VRP problems focused in this thesis, the vehicle routing problem with backhauls (VRPB) and the multiple trip vehicle routing problem (MT-VRP), there is not sufficient development on the problem modelling side in terms of bringing these two problems closer to the reality. Hence, to fill the gap this thesis introduces and investigates a new variant, the multiple trip vehicle routing problem with backhauls (MT-VRPB) that combines the above two variants of the VRP. The problem is first described thoroughly and a new ILP (Integer Linear Programming) mathematical formulation of the MT-VRPB along with its possible variations is presented. The MT-VRPB is then solved optimally by using CPLEX along with providing an illustrative example showing the validation of the mathematical formulation. As part of the contribution, a large set of MT-VRPB data instances is created which is made available for future benchmarking. The CPLEX implementation produced optimal solutions for a good number of small and medium size data instances of the MT-VRPB and generated lower bounds for all instances. The CPLEX success may be considered as modest, but the produced results proved very important for the validation of the heuristic results produced in the thesis. To solve the larger instances of the MT-VRPB, a two level VNS algorithm called 'Two-Level VNS' is developed. It was noticed from the literature that the choice of using VNS for the VRPs has increased in recent literature due to its simplicity and speed. However our initial experiments with the classical VNS indicated that the algorithm is more inclined towards the intensification side. Hence, the Two-Level VNS is designed to obtain a maximum balance of the diversification and the intensification during the search process. It is achieved by incorporating a sub-set of neighbourhood structures and a sus-set of local search refinement routines and hence, a full set of neighbourhood structures and a full set of local search refinement routines at two levels of the algorithm respectively. The algorithm found very encouraging results when compared with the solutions found by CPLEX. These findings in this thesis demonstrate the power of VNS yet again in terms of its speed, simplicity and efficiency. To investigate this new variant further, we developed an algorithm belonging to the new class of the hybrid methodologies, i.e., mat-heuristics. A hybrid collaborative sequential mat-heuristic approach called the CSMH to solve the MT-VRPB is developed. The exact method approach produced in Chapter 4 is then hybridised with the Two-Level VNS algorithm developed in Chapter 5. The overall performance of the CSMH remained very encouraging in terms of the solution quality and the time taken on average compared with the CPLEX and the Two-Level VNS meta-heuristic. To demonstrate the power and effectiveness of our methodologies, we tested the designed algorithms on the two special versions of the VRP (i.e., VRPB and MT-VRP) to assess whether they are efficient and dynamic enough to solve a range of VRP variants. Hence the Two-Level VNS and the CSMH algorithms developed to solve the MT-VRPB are adapted accordingly and implemented to solve the two above variants separately. The algorithms produced very competitive results for the benchmark data sets when compared to the best known solutions from the literature. The successful implementations of these algorithms on the three VRP models with only minor amendments prove their generalizability and their robustness. The results in this research show that significant cost savings could be obtained by choosing the right fleet size and better vehicle utilisations with multiple trips and backhauling. Hence, the research proved the justification of studying this interesting combination. Moreover, the problem modelling, efficient algorithm design and implementation, and the research results reveal some vital information and implications from the managerial point of view in terms of making the tactical (fleet acquisition) and the operational (fleet management) decisions in a more informative manner

An Application of Self-Organizing Map for Multirobot Multigoal Path Planning with Minmax Objective

In this paper, Self-Organizing Map (SOM) for the Multiple Traveling Salesman Problem (MTSP) with minmax objective is applied to the robotic problem of multigoal path planning in the polygonal domain. The main difficulty of such SOM deployment is determination of collision-free paths among obstacles that is required to evaluate the neuron-city distances in the winner selection phase of unsupervised learning. Moreover, a collision-free path is also needed in the adaptation phase, where neurons are adapted towards the presented input signal (city) to the network. Simple approximations of the shortest path are utilized to address this issue and solve the robotic MTSP by SOM. Suitability of the proposed approximations is verified in the context of cooperative inspection, where cities represent sensing locations that guarantee to “see” the whole robots’ workspace. The inspection task formulated as the MTSP-Minmax is solved by the proposed SOM approach and compared with the combinatorial heuristic GENIUS. The results indicate that the proposed approach provides competitive results to GENIUS and support applicability of SOM for robotic multigoal path planning with a group of cooperating mobile robots. The proposed combination of approximate shortest paths with unsupervised learning opens further applications of SOM in the field of robotic planning

Algoritmos de solución para el problema multidepósito y multiobjetivo de ruteo de vehículos considerando recogida de productos y restricción de precedencia

En esta tesis se presenta la aplicación de diferentes técnicas heurísticas y metaheurísticas para la solución del problema de ruteo de vehículos con restricción de precedencia, heurísticas como el vecino más cercano y la del ahorro con inserción secuencial, y metaheurísticas como búsqueda tabú y optimización por colonia de hormigas son utilizadas y ajustadas para resolver eficientemente diferentes variantes del problema de ruteo de vehículos con entrega y recogida de paquetes con restricción de precedencia, considerando el caso monodepósito y multidepósito, mono y multiobjetivo. Cada ruta realizada consta de una sub-ruta en la que se realiza sólo la tarea de entrega y otra sub-ruta en la que se realiza sólo el proceso de recolección, esta última se inicia solo cuando el vehículo está vacío. Los algoritmos y metaheurísticas propuestas tratan de encontrar el mejor orden para visitar a los clientes en cada ruta realizada. Además, el enfoque propuesto determina la mejor conexión entre los sub-rutas de entrega y recogida, con el fin de obtener una solución global minimizando el número de vehículos, la distancia recorrida, el tiempo empleado y la cantidad de energía consumida por los vehículos. El estudio multiobjetivo permitió encontrar un conjunto de soluciones ordenadas en los frentes de Pareto considerando el concepto de dominancia. Adicionalmente, para el modelo multiobjetivo, se plantea la metodología de ponderaciones de los valores de cada función objetivo se selecciona una alternativa de solución con dominancia en el número de vehículos usados. La eficacia del enfoque propuesto se examina teniendo en cuenta un conjunto de casos adaptados de la literatura. También, se propone un modelo exacto, el cual es resuelto mediante la técnica de rutas abiertas con enlace óptimo. Los resultados computacionales muestran resultados de alta calidad en tiempos de procesamiento competitivos. Los resultados computacionales se comparan con los existentes en la literatura especializada y entre los diferentes algoritmos propuestos. Por último, se presentan las conclusiones y sugerencias para trabajos futuros

Algoritmos de solución para el problema multidepósito y multiobjetivo de ruteo de vehículos considerando recogida de productos y restricción de precedencia

En esta tesis se presenta la aplicación de diferentes técnicas heurísticas y metaheurísticas para la solución del problema de ruteo de vehículos con restricción de precedencia, heurísticas como el vecino más cercano y la del ahorro con inserción secuencial, y metaheurísticas como búsqueda tabú y optimización por colonia de hormigas son utilizadas y ajustadas para resolver eficientemente diferentes variantes del problema de ruteo de vehículos con entrega y recogida de paquetes con restricción de precedencia, considerando el caso monodepósito y multidepósito, mono y multiobjetivo. Cada ruta realizada consta de una sub-ruta en la que se realiza sólo la tarea de entrega y otra sub-ruta en la que se realiza sólo el proceso de recolección, esta última se inicia solo cuando el vehículo está vacío. Los algoritmos y metaheurísticas propuestas tratan de encontrar el mejor orden para visitar a los clientes en cada ruta realizada. Además, el enfoque propuesto determina la mejor conexión entre los sub-rutas de entrega y recogida, con el fin de obtener una solución global minimizando el número de vehículos, la distancia recorrida, el tiempo empleado y la cantidad de energía consumida por los vehículos. El estudio multiobjetivo permitió encontrar un conjunto de soluciones ordenadas en los frentes de Pareto considerando el concepto de dominancia. Adicionalmente, para el modelo multiobjetivo, se plantea la metodología de ponderaciones de los valores de cada función objetivo se selecciona una alternativa de solución con dominancia en el número de vehículos usados. La eficacia del enfoque propuesto se examina teniendo en cuenta un conjunto de casos adaptados de la literatura. También, se propone un modelo exacto, el cual es resuelto mediante la técnica de rutas abiertas con enlace óptimo. Los resultados computacionales muestran resultados de alta calidad en tiempos de procesamiento competitivos. Los resultados computacionales se comparan con los existentes en la literatura especializada y entre los diferentes algoritmos propuestos. Por último, se presentan las conclusiones y sugerencias para trabajos futuros

Dynamic incentive scheme for rental vehicle fleet management

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 47-49).Mobility on Demand is a new transportation paradigm aimed to provide sustainable transportation in urban settings with a fleet of electric vehicles. Usage scenarios prpopsed by Mobility on Demand systems must allow one-way rentals. However, one-way rentals bring significant challenges to fleet management because areas of high demand will tend to lose their inventory, whereas areas of low demand will tend to accumulate inventory. Dynamic incentives can be provided to encourage different usage patterns and alleviate the problem of demand asymmetry. This thesis proposes a dynamic incentive scheme for rental vehicle fleet management in the context of Mobility on Demand. Simulation using Vienna taxi data shows the scheme to be effective at maintaining the equalibrium state of the fleet. It holds great promise to be incorporated in a real-world deployment of Mobility on Demand system.by SiZhi Zhou.M.Eng

Optimização de uma rede de transportes : aplicação a um caso real

Mestrado em Gestão e Estratégia IndustrialNos dias que correm, existe cada vez mais a tendência para a competição e combatividade de melhores e maiores sucessos e os clientes são cada vez mais rigorosos. O avanço enquanto oferta e a redução de despesas, passam por uma boa escolha nos diversos recursos logísticos. Nesta linha de pensamento, a logística desempenha um cargo fulcral no que respeita à optimização de operações concernentes ao armazenamento e transporte de matérias e produtos, pautando-se sempre, por uma aposta superior do nível de serviço prestado e por uma oferta de redução dos custos. Devido ao avançar dos tempos, nos quais os produtos e serviços se tornam mais complexos e evoluídos no mercado, é indispensável planearem-se processos de negócio modernos que visem, sobretudo, o desenvolvimento, a produção, a venda e a conservação dos produtos, para que estes possam ser adquiridos e utilizados eficazmente. Desta forma, a organização e gestão dos supramencionados processos de negócios são extremamente importantes, tendo em conta o seu objectivo final. Para que se mantenha o bom funcionamento das empresas num meio altamente competitivo, é fundamental existir uma boa gestão logística, permitindo, desta maneira, alcançar metas vantajosas, no mercado. É nesta perspectiva que se realiza um estudo que recai sobre a empresa portuguesa MNM.SA. Este, visa compreender o modo como a utilização de um algoritmo definidor de rotas de distribuição e optimizador da utilização de veículos, pode contribuir para a optimização superior das operações logísticas da referida empresa.In These days, there is an increasing tendency for the competition and combativeness of the best and biggest hits and the customers are becoming more demanding. The progress as and supply are reducing the expenses, they have been a good choice in the various logistical resources. With this in mind, logistics plays a key position with regard to optimization of operations concerning the storage and transportation of materials and products, guided always by a bet higher level of service and an offer to reduce costs. Because of the advance of the times in which products and services become more complex and evolved in the market, planning is essential to modern business processes which focus on the development, production, sale and storage of products, so that can be purchased and used effectively. Thus, the mentioned above organization and administration processes are extremely important, having regard to its ultimate goal. In order to maintain the proper functioning of enterprises in a highly competitive environment, it is essential to have a good logistics management, allowing, thus, achieve goals advantageous market. From this perspective, a study takes place lies with the Portuguese company MNM.SA. This aims to understand how the use of an algorithm defining the distribution routes and optimized the use of vehicles, can contribute to higher optimization of logistics operations of the company