Multi-Level Route-Optimization Computer Application

This report provides a detailed analysis on how to optimize driving routes by creating a computer application. There are many different route-optimization issues that logistical companies consistently face, as well as many different solutions and algorithms. With technology on the rise, pick-up, delivery, and transportation services are become a huge part of our everyday lives. When optimizing routes, reducing transportation costs by minimizing travel distance is always ideal, but other factors must be considered such as arriving at a location before or after a certain time. Our objective is to optimize driving routes based on travel distance and priorities. We approached this project by using SQL as our main source of determining the route order based on the given distances and priorities of each destination in the projected route. We also used VBA as a tool to support the calculations and ASP.net to insert Javascript and HTML code, which allows us to visualize the Google Maps route once the order has been determined

Revisión del estado del arte del problema de ruteo de vehículos con recogida y entrega (VRPPD)

This paper presents a literature review of the state of the art vehicle routing problem with deliveries and collections (VRPPD: Vehicle Routing Problem with pickups and deliveries). Is performed a classification of the different variants of the problem, and the work and conducted research on the subject according to its authors, according to the models and the solution methods used. Also are analyzed future trends in modeling and solution techniques. The VRPPD is a problem of type MILP (Mixed Integer Linear Programming) involving whole and continuous quantities, and that turns out to be NP-Hard problems with a medium or large number of customers. The research does emphasis on variants of the problem involving variables associated with the environment, and in particular reducing the impact of greenhouse gases. The review notes that published until 2016.En este trabajo se realiza una revisión bibliográfica del estado del arte del problema de ruteo de vehículos con entregas y recogidas (VRPPD: Vehicle routing problem with pickups and deliveries). Se presenta una clasificación de las diferentes variantes del problema, y de los trabajos e investigaciones realizados sobre el tema según sus autores, los modelos utilizados y los métodos de solución usados. También se analizan las tendencias futuras en modelamiento y técnicas de solución. El VRPPD es un problema del tipo MILP (programación lineal entera mixta) que involucra cantidades enteras y continuas, y que resulta ser NP-Hard en problemas con un número mediano o grande de clientes. En la búsqueda se hace énfasis en las variantes del problema que involucran variables asociadas al medio ambiente, y en particular con la reducción del impacto de gases de efecto invernadero. La revisión observa lo publicado hasta el año 2016

A stochastic hybrid algorithm for multi-depot and multi-product routing problem with heterogeneous vehicles

Abstract. A mathematical model and heuristic method for solving multi-depot and multi-product vehicle routing problem (MD-MPVRP) with heterogeneous vehicles have been proposed in this article. Customers can order eclectic products and depots are supposed to deliver customers' orders before the lead time, using vehicles with diverse capacities, costs and velocities. Hence, mathematical model of multi-depot vehicle routing problem has been developed to mirror these conditions. This model is aimed at minimizing the serving distances which culminates in a reduction in prices and also serving time. As the problem is so complex and also solving would be too time-taking, a heuristic method has been offered. The heuristic method, at first, generates an initial solution through a three-step procedure which encompasses grouping, routing and vehicle selection, scheduling and packaging. Then it improves the solution by means of simulated annealing. We have considered the efficiency of offered algorithm by comparing its solutions with the optimum solutions and also during a case study. [V. Mahdavi Asl, S.A. Sadeghi, MR. Ostadali Makhmalbaf. A stochastic hybrid algorithm for multi-depot and multi-product routing problem with heterogeneous vehicles

Particle Swarm Optimization Algorithm to Solve Vehicle Routing Problem with Fuel Consumption Minimization

The Conventional Vehicle Routing Problem (VRP) has the objective function of minimizing the total vehicles’ traveling distance. Since the fuel cost is a relatively high component of transportation costs, in this study, the objective function of VRP has been extended by considering fuel consumption minimization in the situation wherein the loading weight and traveling time are restricted. Based on these assumptions, we proposed to extend the route division procedure proposed by Kuo and Wang [4] such that when one of the restrictions can not be met the routing division continues to create a new sub-route to find an acceptable solution. To solve the formulated problem, the Particle Swarm Optimization (PSO) algorithm is proposed to optimize the vehicle routing plan. The proposed methodology is validated by solving the problem by taking a particular day data from a bottled drinking water distribution company. It was revealed that the saving of at best 13% can be obtained from the actual routes applied by the company

Two-step Meta-heuristic Approach for a Vehicle Assignment Problem – Case from İstanbul/Turkey

In this paper, a two-step meta-heuristic approach is proposed for vehicle assignment problem with geometric shape-based clustering and genetic algorithm. First, the geometric shape-based clustering method is used and then the solution of this method is given to the genetic algorithm as initial solution. The solution process is continued by genetic algorithm. There are 282 bus lines in İstanbul European side. Those buses should be assigned to six bus garages. The proposed method is used to determine the minimum distance between the bus lines and garages by assigning buses to garages. According to the computational results, the proposed algorithm has better clustering performance in terms of the distance from each bus-line start point to each bus garage in the cluster. The crossover rate changing method is also applied as a trial in order to improve the algorithm performance. Finally, the outputs that are generated by different crossover rates are compared with the results of the k-Nearest Neighbour algorithm to prove the effectiveness of the study.</p

Managing Advanced Synchronization Aspects in Logistics Systems

In this thesis, we model various complex logistics problems and develop appropriate techniques to solve them. We improve industrial practices by introducing synchronized solutions to problems that were previously solved independently. The first part of this thesis focuses on cross-docks. We simultaneously optimize supplier orders and cross-docking operations to either reduce the storage space required or evenly distribute workload over the week. The second part of this thesis is devoted to transport problems in which two types of vehicles are synchronized, one of which can be transported by the other. The areas of application range from home services to parcel delivery to customers. After analyzing the complexity associated with these synchronized solutions (i.e., largescale problems for which the decisions depend on each other), we design algorithms based on the "destroy-and-repair" principle to find efficient solutions. We also introduce mathematical programs for all the considered problems. The problems under study arose directly from collaborations with various industrial partners. In this respect, our achieved solutions have been benchmarked with current industrial practice. Depending on the problem, we have been able to reduce the environmental impact generated by the industrial activities, the overall cost, or the social impact. The achieved gains compared to current industrial practice range from 10 to 70%, depending on the application. -- Dans cette thèse, nous modélisons divers problèmes logistiques complexes et développons des techniques appropriées pour les résoudre. Nous cherchons à améliorer certaines pratiques industrielles en introduisant des solutions synchronisées à des problèmes qui étaient auparavant résolus indépendamment. La première partie de cette thèse porte sur les cross-docks. Nous optimisons simultanément les commandes fournisseurs et les opérations au sein de la plateforme de logistique pour réduire l’espace de stockage requis ou répartir uniformément la charge de travail sur la semaine. La deuxième partie de cette thèse est consacrée aux problèmes de transport dans lesquels deux types de véhicules sont synchronisés, l’un pouvant être transporté par l’autre. Les domaines d’application vont du service à domicile à la livraison de colis chez des clients. Après avoir analysé la complexité des solutions synchronisées (c’est-à-dire des problèmes de grandes dimensions pour lesquels les décisions dépendent les unes des autres), nous concevons des algorithmes basés sur le principe de "destruction / reconstruction" pour trouver des solutions efficaces. Nous modélisons également les problèmes considérés avec la programmation mathématique. Les problèmes à l’étude viennent de collaborations avec divers partenaires industriels. A cet égard, les solutions que nous présentons sont comparées aux pratiques industrielles actuelles. En fonction du problème, nous avons pu réduire l’impact environnemental généré par les activités industrielles, le coût global, ou l’impact social des solutions. Les gains obtenus par rapport aux pratiques industrielles actuelles varient de 10 à 70%, selon l’application. Mot-clefs: Logistique, Synchronisation, Problème de transport, Tournée de véhicules, Plateforme de Cross-dock (transbordement), Programmation Mathématiques, Métaheuristiques, Matheuristiques, Instances Réelle

Driver helper dispatching problems: Three essays

The driver helper dispatching problems (DHDPs) have received scant research attention in past literature. In this three essay format dissertation, we proposed two ideas: 1) minimizing of the total cost as the new objective function to replace minimizing the total distance cost that is mostly used in past traveling salesman problem (TSP) and vehicle routing problem (VRP) algorithms and 2) dispatching vehicle either with a helper or not as part of the routing decision. The first study shows that simply separating a single with-helper route into two different types of sub-routes can significantly reduce total costs. It also proposes a new dependent driver helper (DDH) model to boost the utilization rate of the helpers to higher levels. In the second study, a new hybrid driver helper (HDH) model is proposed to solve DHDPs. The proposed HDH model provides the flexibility to relax the constraints that a helper can only work at one predetermined location in current-practice independent driver helper (IDH) model and that a helper always travels with the vehicle in the current-practice DDH model. We conducted a series of full-factorial experiments to prove that the proposed HDH model performs better than both two current solutions in terms of savings in both cost and time. The last study proposes a mathematical model to solve the VRPTW version of DHDPs and conducts a series of full factorial computational experiments. The results show that the proposed model can achieve more cost savings while reducing a similar level of dispatched vehicles as the current-practice DDH solution. All these three studies also investigate the conditions under which the proposed models would work most, or least, effectively

Driver helper dispatching problems: Three essays

The driver helper dispatching problems (DHDPs) have received scant research attention in past literature. In this three essay format dissertation, we proposed two ideas: 1) minimizing of the total cost as the new objective function to replace minimizing the total distance cost that is mostly used in past traveling salesman problem (TSP) and vehicle routing problem (VRP) algorithms and 2) dispatching vehicle either with a helper or not as part of the routing decision. The first study shows that simply separating a single with-helper route into two different types of sub-routes can significantly reduce total costs. It also proposes a new dependent driver helper (DDH) model to boost the utilization rate of the helpers to higher levels. In the second study, a new hybrid driver helper (HDH) model is proposed to solve DHDPs. The proposed HDH model provides the flexibility to relax the constraints that a helper can only work at one predetermined location in current-practice independent driver helper (IDH) model and that a helper always travels with the vehicle in the current-practice DDH model. We conducted a series of full-factorial experiments to prove that the proposed HDH model performs better than both two current solutions in terms of savings in both cost and time. The last study proposes a mathematical model to solve the VRPTW version of DHDPs and conducts a series of full factorial computational experiments. The results show that the proposed model can achieve more cost savings while reducing a similar level of dispatched vehicles as the current-practice DDH solution. All these three studies also investigate the conditions under which the proposed models would work most, or least, effectively