Application of an Open Source Spreadsheet Solver in Single Depot Routing Problem

The VRP has been broadly developed with additional feature such as deliveries, selective pickups time windows. This paper presents the application of an open source spreadsheet solver in single depot routing problem. This study focuses on Fast Moving Consumer Goods (FMCG) Company as a case study. The objective of this research is to minimize the distance travel. This research begins by collecting data from a respective FMCG Company. An FMCG company based in Jakarta, Indonesia provides drinking water packaged in the gallon. This FMCG Company has two distributions characteristic. Head office distribution was used in this case study due to highest internally rejected by the company such as un-routed order, no visit, not enough time to visit and transportation issue. Based on computational results, overall solutions to delivered 214 gallons to 26 customers having total distance traveled 56.76 km, total driving time 2 hour and 49 minutes, the total driver working time 7 hours and 57 minutes. Total savings of distances traveled between current route and the proposed solutions using open source spreadsheet solver is 7.25 km. As a result, by using open source spreadsheet solver in single depot routing problem can be implemented in FMCG Company

Estado del arte para la resolución de enrutamiento de vehículos con restricciones de capacidad

[ESP] El propósito del presente documento es el de realizar una revisión e investigación en la literatura científica para conocer el estado del arte referente a un problema real de optimización. Dicho problema emana de un proyecto de investigación en el que se estudia la aplicación de métodos de Investigación Operativa para la optimización y mejora de los Sistemas de Transporte Intermodal1. Se pretende, en definitiva, evaluar el conocimiento científico, así como las técnicas y métodos que son investigados y empleados para problemas o situaciones que guarden relación con el problema objeto. Este consiste en la optimización de la operativa de una empresa logística que se dedica a la distribución de vehículos por carretera (transporte rodado). Dicha distribución, se realiza en base a una serie de pedidos que son recibidos en unos almacenes/depósitos repartidos por toda la geografía española. En función de una serie de objetivos y restricciones se configura la carga que deben contener los camiones disponibles y la planificación de la ruta a seguir. Una vez que estos camiones han repartido la carga, se encontrarán disponibles para volver a realizar una recogida de carga y comenzar un nuevo reparto. Por lo tanto, los camiones no siguen un esquema en el que se realiza un reparto de manera centralizada sino que, de manera descentralizada, los camiones viajan por toda la geografía recogiendo y entregando las cargas

OPTIMAL REASSIGNMENT OF FLIGHTS TO AIRPORT BAGGAGE UNLOADING CAROUSELS IN RESPONSE TO TEMPORARY MALFUNCTIONS

Being able to efficiently reassign outbound flights to baggage unloading carousels (BUCs) following temporary malfunctions is very important for airport operators. This study proposes an optimization model with a heuristic to solve the carousel reassignment problem. The objective is to minimize the total disturbance and overlapping time caused by the reassignment of outbound flights. A heuristic is developed to efficiently solve large-sized instances. The proposed approach is then applied to solve real-world instances of the problem at a major international airport in Taiwan. The computation time is about two minutes. The objective value obtained with the heuristic is more than 15% better than that obtained by the manual approach currently used by the operator. The improvement is gained mostly from the reduction in total temporal disturbance and overlapping time. The proposed approach could assist the operator in reassigning outbound flights to BUCs in response to malfunctions

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

OPTIMIZATION MODEL FOR SCHOOL TRANSPORTATION DESIGN BASED ON ECONOMIC AND SOCIAL EFFICIENCY

[EN] The purpose of this paper is to design a model that allows to suggest new planning proposals on school transport, so that greater efficiency operational will be achieved. It is a multiobjective optimization problem including the minimization of the cost of busing and minimizes the total travel time of all students. The foundation of the model is the planning routes made by bus due to changes in the starting time in schools, so the buses are able to perform more than one route. The methodology is based on the School Bus Routing Problem, so that routes from different schools within a given time window are connected, and within the restrictions of the problem, the system costs are minimized. The proposed model is programmed to be applied in any generic case. This is a multi-objective problem, in which there will be several possible solutions, depending on the weight to be assigned to each of the variables involved, economic point of view versus social point of view. Therefore, the proposed model is helpful for policy planning school transportation, supporting the decision making under conditions of economic and social efficiency. The model has been applied in some schools located in an area of Cantabria (Spain), resulting in 71 possible optimal options that minimize the cost of school transport between 2,7% and 35,1% regarding to the current routes of school transport, with different school start time and minimum travel time for students.Ezquerro Eguizábal, S.; Moura Berodia, JL.; Ibeas Portilla, A.; Benavente Ponce, J. (2016). OPTIMIZATION MODEL FOR SCHOOL TRANSPORTATION DESIGN BASED ON ECONOMIC AND SOCIAL EFFICIENCY. En XII Congreso de ingeniería del transporte. 7, 8 y 9 de Junio, Valencia (España). Editorial Universitat Politècnica de València. 926-944. https://doi.org/10.4995/CIT2016.2015.4074OCS92694

A Multi Objective Evolutionary Algorithm for Solving a Real Health Care Fleet Optimization Problem

The problem of the transportation of patients from or to some health care center given a number of vehicles of different kinds can be considered as a common Vehicle Routing Problem (VPR). However, in our particular case, the logistics behind the generation of the vehicle itineraries are affected by a high number of requirements and constraints such as the enterprise benefits, the satisfaction of the patients, and the respect of certain law regulations regarding the patients and the employees. In this work, we discuss the main aspects of the implementation of a Multi Objective Evolutionary Algorithm focused on providing a set of valid solutions to the end users of Patient Transport Services. We provide a detailed description of the process of integrating all the information on different genetic operators and multiple fitness functions. Finally, we present the preliminary results on a real-life problem from an small company that provides transport service and we compare the results that our implementation gets with the itineraries proposed by human experts

Roulette-Wheel Selection-Based PSO Algorithm for Solving the Vehicle Routing Problem with Time Windows

The well-known Vehicle Routing Problem with Time Windows (VRPTW) aims to reduce the cost of moving goods between several destinations while accommodating constraints like set time windows for certain locations and vehicle capacity. Applications of the VRPTW problem in the real world include Supply Chain Management (SCM) and logistic dispatching, both of which are crucial to the economy and are expanding quickly as work habits change. Therefore, to solve the VRPTW problem, metaheuristic algorithms i.e. Particle Swarm Optimization (PSO) have been found to work effectively, however, they can experience premature convergence. To lower the risk of PSO's premature convergence, the authors have solved VRPTW in this paper utilising a novel form of the PSO methodology that uses the Roulette Wheel Method (RWPSO). Computing experiments using the Solomon VRPTW benchmark datasets on the RWPSO demonstrate that RWPSO is competitive with other state-of-the-art algorithms from the literature. Also, comparisons with two cutting-edge algorithms from the literature show how competitive the suggested algorithm is

Modelo de roteamento para coleta de leite cru utilizando algoritmos genéticos

The article examines the use of a metaheuristic method – genetic algorithms – for evaluating a model of routes for raw milk collection. A model was implemented based on real data, collected through fieldwork, following the method of the «traveling agent’s problem», using the toolbox of Matlab® genetic algorithm. The results show that the routes obtained with the implementation of the genetic algorithm are feasible in terms of time and visited nodes, demonstrating the potential of this tool. The costs obtained by this method differ from the current methods by about 3%, which is within the range reported in the literature.El artículo presenta la utilización de un método metaheurístico –algoritmos genéticos– para la evaluación de un modelo de rutas de recolección de leche cruda. Se implementó un modelo a partir de datos reales, recolectados por medio de trabajo de campo, siguiendo el método del «problema del agente viajero», usando el toolbox de algoritmos genéticos de Matlab®. Los resultados evidencian que las rutas obtenidas con la implementación del algoritmo genético son viables en cuanto a tiempo y nodos visitados, lo que demuestra el potencial de esta herramienta. Los costos obtenidos por este método difieren de los actuales en alrededor de 3%, valor que está dentro de los márgenes reportados en la literatura.O artigo mostra o uso de um método meta heurístico - algoritmos genéticos - para avaliar um padrão de rotas de coleta de leite cru. Foi implementado um modelo baseado em dados reais, coletados por meio de trabalho de campo, seguindo o método do "Problema do Caixeiro Viajante", usando os algoritmos genéticos da caixa de ferramentas Matlab®. Os resultados mostram que as rotas obtidas com a implementação do algoritmo genético são viáveis em termos de tempo e de nós visitados, demonstrando assim o potencial desta ferramenta. Os custos obtidos por este método diferem dos atuais em aproximadamente 3%, o que está dentro do intervalo referido na literatura

Algorithms for the multi-objective vehicle routing problem with hard time windows and stochastic travel time and service time

This paper introduces a multi-objective vehicle routing problem with hard time windows and stochastic travel and service times. This problem has two practical objectives: minimizing the operational costs, and maximizing the service level. These objectives are usually conflicting. Thus, we follow a multi-objective approach, aiming to compute a set of Pareto-optimal alternatives with different trade-offs for a decision maker to choose from. We propose two algorithms (a Multi-Objective Memetic Algorithm and a Multi-Objective Iterated Local Search) and compare them to an evolutionary multi-objective optimizer from the literature. We also propose a modified statistical method for the service level calculation. Experiments based on an adapted version of the 56 Solomon instances demonstrate the effectiveness of the proposed algorithms