This thesis is aimed on time frame distribution task. In the theoretical part is described the mathematical model of this task and introduced in detail two concrete heuristics: greedy look-ahead and AKRed. In the practical part of the thesis has been a real situation solved with using of sophisticated optimalization software and through own implemented heuristic. These two solution are then compared each other and applicability of each heuristics for the given real problem is evaluated.

Cette thèse porte sur la résolution de problèmes de transport qui intègrent des contraintes temporelles considérant les fenêtres de temps, la synchronisation des visites et l’équilibrage des services. Ces problèmes trouvent plusieurs applications dans le monde réel.L’objectif de nos recherches est l’élaboration de nouvelles méthodes de résolution pour les problèmes considérés en examinant leur performance avec une étude comparative par rapport aux différentes approches de la littérature. Deux variantes sont traitées. Le premier cas étudie le Problème de Tournées de Véhicules avec Fenêtres de Temps (VRPTW). Nous proposons de nouveaux prétraitements et bornes inférieures pour déterminer le nombre de véhicules nécessaires en s’inspirant de travaux menés en ordonnancement (raisonnement énergétique) et d’autres problèmes combinatoires comme la clique maximum et les problèmes de bin-packing. Nous présentons également un algorithme d’optimisation par essaim particulaire qui traite de la minimisation du nombre de véhicules puis de celle du temps de trajet total. Le deuxième cas étudie le Problème de Tournées de Véhicules avec des Fenêtres de Temps et des Visites Synchronisées (VRPTWSyn). Nous proposons plusieurs méthodes basées sur des approches heuristiques et des formulations linéaires avec l’incorporation d’inégalités valides pour tenir compte de la contrainte de synchronisation. / This dissertation focuses on vehicle routing problems, one of the major academic problems in logistics. We address NP-Hard problems that model some realworld situations particularly those with different temporal constraints including time windows, visit synchronization and service balance.The aim of this research is to develop new algorithms for the considered problems,investigate their performance and compare them with the literature approaches.Two cases are carried out. The first case studies the Vehicle Routing Problem with Time Windows (VRPTW). We propose new lower bound methods for the number of vehicles. Then we present a Particle Swarm Optimization algorithm dealing with the Solomon objective. The second case studies the VehicleRouting Problem with Time Windows and Synchronized Visits (VRPTWsyn).Both exact methods and heuristics are proposed and compared to the literature approaches.

This thesis is continuation of the bachelor thesis "Model of delivery routes and placement logistics centers with opportunities of their optimization". It is about distribution problems and specifically a vehicle routing problem. The aim of this thesis is finding a solution of the vehicle routing problem which will be used repeatedly in the firm. The main task is achieving the lowest costs (total kilometers) with maximum utilization of vehicle capacity; in such conditions that all requirements of logistics centers will be satisfied and maximal capacity of vehicle will be tolerated. For calculation was used a solver Gurobi 6.0.3 in system MPL for Windows 4.2, which won't, however, provide the optimal solution and problem solving takes too long time. Next for calculation was used heuristics insert method and is written by VBA (Visual Basic for Applications) in MS Excel. Finally, there is a comparison of these methods with the original solution of the vehicle routing plan and solution of the bachelor thesis. Then the computational experiment was done, which tested effect to result, if other distribution center (starting point) will be bulit. The computational experiment was consist from heuristic insert method, solver Gurobi and heuristic saving algorithm from bachelor thesis.

In this paper,we propose an adaptive large neighborhood search heuristic for the Two-Echelon Vehicle Routing Problem (2E-VRP) and the Location Routing Problem (LRP).The 2E-VRP arises in two-level transportation systems such as those encountered in the context of city logistics. In such systems, freight arrives at a major terminal and is shipped through intermediate satellite facilities to the final customers. The LRP can be seen as a special case of the 2E-VRP in which vehicle routing is performed only at the second level. We have developed new neighborhood search operators by exploiting the structure of the two problem classes considered and have also adapted existing operators from the literature. The operators are used in a hierarchical scheme reflecting the multi-level nature of the problem. Computational experiments conducted on several sets of instances from the literature show that our algorithm out performs existing solution methods for the 2E-VRP and achieves excellent results on the LRP.

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The thesis focuses on how to optimize vehicle routes for distributing logistics. This vehicle route optimization is known as a vehicle routing problem (VRP). The VRP has been extended in numerous directions for instance by some variations that can be combined. One of the extension forms of VRP is a capacitated VRP with stochastics demands (CVRPSD), where the vehicle capacity limit has a non-zero probability of being violated on any route. So, a failure to satisfy the amount of demand can appear. A strategy is required for updating the routes in case of such an event. This strategy is called as recourse action in the thesis. The main objective of the research is how to design the model of CVRPSD and find the optimal solution. The EEV (Expected Effective Value) and FCM (Fuzzy C-Means) – TSP (Travelling Salesman Problem) approaches are described and used to solve CVRPSD. Results have confirmed that the EEV approach has given a better performance than FCM-TSP for solving CVRPSD in small instances. But EEV has disadvantage, that the EEV is not capable to solve big instances in an acceptable running time because of complexity of the problem. In the real situation, the FCM –TSP approach is more suitable for implementations than the EEV because the FCM – TSP can find the solution in a shorter time. The disadvantage of this algorithm is that the computational time depends on the number of customers in a cluster.

The following work concerns the study of the evolutionary algorithm, which optimizes freight transport planning. The demand for freight transport is constantly increasing nowadays and with creating, implementing and using proper route planning we are able to significantly reduce transportation costs. However, it is preferably to implement it in companies with large numbers of served customers and with a sufficiently large fleet of vehicles.   The study starts by defining what fright transport planning problem is and by characterizing its existing specifications and variants. My work proceeds to give a background of the possible solutions to the multifaceted aspects of the problem. The specific subproblem I choose to focus on is the Vehicle routing problem with Pickup and Delivery for which I apply the optimization solution. In the main body of my thesis, I will elaborate on the chosen optimization solution which encompasses the genetic algorithm and evolutionary strategy. The aim of the study is to measure the suitability of the algorithms and techniques used, for which reason the final part of my work will deal with the analysis and evaluation of the experiments.

This thesis deals with portation of the OptaPlanner tool to the Android operating system. The OptaPlanner is used for solving planning problems and it is completely written in the Java programming language which is also used for application development of the Android operating system. However, Android does not contain all of the Java Standard Edition Application Programming Interface libraries and porting of OptaPlanner to Android thus causes dependency problems. The result of the thesis is solution design and implementation of the problems mentioned above and model Android Vehicle Routing Problem application which uses ported OptaPlanner tool.

El presente estudio versa sobre la ejecución proyectos eléctricos en baja tensión, los cuales son ejecutados por una empresa de servicios cuyas operaciones se realizan en Lima. El capítulo 1 presenta la literatura asociada a la solución del problema, en donde se desarrolla el marco teórico de las metodologías propuestas. El capítulo 2 muestra el uso de las herramientas de la ingeniería industrial a efectos de identificar el problema: “retrasos en la ejecución de proyectos de baja tensión con reforma”. Esta problemática genera una pérdida anual de 381 miles de soles y un déficit de capital de trabajo de 11,500 miles de soles correspondiente al año 2017. El capítulo 3 plantea la solución de la problemática expuesta, para lo cual se definen dos etapas. La primera permite la eliminación del backlog acumulado hasta el mes de setiembre de 2018. La segunda se refiere al desarrollo de las metodologías: Last Planner System, Vehicle Routing Problem y Workforce Management. En el capítulo 4 se realiza la validación de las propuestas de las mejoras planteadas. En la primera etapa se contrataron 210 personas para eliminar el backlog y se validó una utilidad de 104 miles de soles. Para la segunda etapa, se implementó el proyecto cuadrillas propias y se utilizaron las metodologías Last Planner System y Vehicle Routing Problem.. Finalmente, se integró ambas metodologías con la incorporación de tecnología del tipo Workforce Management. Los resultados muestran una TIR del 20% y un VAN de 229 miles de soles. / The present research is about the implementation of low voltage electrical projects, which are performed by an utility company whose area of operations is the city of Lima. Chapter 1 describes the literature associated with the solution of the problem, where the theoretical framework of the above mentioned methodologies is developed. Chapter 2 describes the results obtained through the utilization of industrial engineering tools, with which the problem is identified as: "delays in the implementation of low voltage projects with reform". This problem generates an annual loss of 381 thousand soles and a working capital deficit of 11,500 thousand soles corresponding to year 2017. Chapter 3 proposes the solution of the exposed problem, for which two stages are defined. The first one allows the elimination of the accumulated backlog until September 2018. The second one refers to the development of the methodologies: Last Planner System, Vehicle Routing Problem and Workforce Management. Chapter 4 validates the proposed improvements. In the first stage, 210 people were hired to eliminate the backlog and as a result there was a profit of 104 thousand soles for the period within July and September. For the second stage, the project of own crews was implemented and there were used Last Planner System and the Vehicle Routing Problem as methodologies in order to optimize the route of the crews. Finally, both methodologies were integrated with the incorporation of the Workforce Management technology. The results show an IRR of 20% and a NPV of 229 thousand soles. / Trabajo de Suficiencia Profesional

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