Methods to increase the productivity of container terminals based on lean service

This article aims to demonstrate the relationship between the actions planned and executed by the company studied to increase port productivity and the Lean Service theory, which comes to be the adaptation of lean principles that have emerged from manufacturing to the service sector. The company cited in this article is one of the major container terminals affiliated to the Brazilian Association of Container Terminals for Public Use. The main purpose of this segment is related to the speed of operations, driven by customer requirement to maintain your boat moored in the shortest time in port due to high costs of late completion of their routes. The main findings indicate that the actions taken by the company to improve productivity indicators are directly related to process optimization, and consequently to increase the speed of the containers loading and unloading operations

Sea Container Terminals

Due to a rapid growth in world trade and a huge increase in containerized goods, sea container terminals play a vital role in globe-spanning supply chains. Container terminals should be able to handle large ships, with large call sizes within the shortest time possible, and at competitive rates. In response, terminal operators, shipping liners, and port authorities are investing in new technologies to improve container handling infrastructure and operational efficiency. Container terminals face challenging research problems which have received much attention from the academic community. The focus of this paper is to highlight the recent developments in the container terminals, which can be categorized into three areas: (1) innovative container terminal technologies, (2) new OR directions and models for existing research areas, and (3) emerging areas in container terminal research. By choosing this focus, we complement existing reviews on container terminal operations

Otimização de rotas de distribuição marítima

Mestrado em Engenharia e Gestão IndustrialA presente dissertação tem como objetivo apresentar um modelo matemático exato para a gestão de porta-contentores sem rotas pré-definidas, considerando as procuras dos portos marítimos e datas de entrega. O short sea shipping é um problema complexo que pertence à classe dos problemas de rotas, especificamente ao problema de rotas de veículos com restrições de carga e datas de entrega. Neste problema duas importantes decisões são tomadas: quais os portos a visitar por cada porta-contentor e qual a sua sequência de visita e onde alocar os contentores nos porta-contentores de forma a prevenir descargas/cargas desnecessárias. Um modelo de programação inteira mista é apresentado e resolvido. A formulação matemática desenvolvida contribui para uma melhor gestão das frotas de pequenos porta-contentores de forma a reduzir os custos de transporte e os tempos de entrega. Por forma a validar o modelo desenvolvido, este foi testado através da resolução de vários problemas de teste baseados em dados reais.This work aims to provide a mathematical model for the short sea shipping problem, without pre-defined routes, considering demands of seaports and cargo delivery deadlines. The short sea shipping is a complex problem that belongs to the class of routing problems, in particular to the vehicle routing problem with capacity constraints (load restrictions and deadlines). In this problem two important decisions have to be made: which ports should be visited by each vessel and in which sequence and where should the containers be placed in. In the containers in the vessel so as to prevent overstowing. A mixed integer programming model is presented and solved. The mathematical formulation developed contributes to the better management of fleets of small vessels to reduce transport costs and delivery times. In order to validate the developed model, we solve it using a set of problems instances based on real problems

Optimization-Based Simulation of Container Terminal Productivity using Yard Truck Double Cycling

ABSTRACT The growth of global trade transiting over the ocean has been continually increasing. A new generation of large vessels has recently been introduced to the transhipment system. These large vessels can carry more than 16000 twenty-foot equivalent container units (TEUs), maximizing shipping productivity. Container terminals must improve their productivity to meet the rapid increases in trade demand and to keep pace with developments in the shipbuilding industry. Reducing vessel turnaround time in container terminals increases the capacity for world trade. This time reduction can be achieved by improving one or more container terminal major resources or factors. The objective of this research is to maximize container terminal productivity by minimizing vessel turnaround time within reasonable hourly and unit costs. A new strategy is introduced, employing double cycling to reduce the empty travel of yard trucks. This double-cycling strategy still requires the use a single-cycle strategy before the trucks can be incorporated into double-cycle scheduling. The single-cycle start-up is necessary in order to create enough space to begin loading a vessel if there is no other space. The strategy is based on combining the efforts of two quay cranes (Unloading and Loading quay cranes) to work as a unit. The technique optimizes the number of trucks in terms of time and cost, minimizing yard truck cycles by minimizing single cycle routes and maximizing double cycle trips. This requires five steps. First, a good knowledge base of a container terminal’s operation and of the behaviours of the Quay cranes (QCs), Yard trucks, and Yard cranes needs to be constructed. Second, analysis of the collected data is required to simulate the container terminal operation and to implement the Genetic algorithm. Third, the double cycling truck strategy is simulated, tested and verified. Fourth, sensitivity analysis is performed to rank and select the best alternatives. Optimization of the selected alternatives in terms of productivity and cost as well as verifying the results using real case studies comprises the fifth step. Genetic Algorithm is used to optimize the results. Some selection approaches are implemented on the set of the nearest optimum solutions to rank and select the best alternative. The research offers immediate value by improving container terminal productivity using existing facilities and resources. Simulating the yard truck double cycling strategy provides container terminal mangers and decision makers with a clear overview of their handling container operations. Optimizing fleet size is a key factor in minimizing container handling costs and time. The simulation model reveals a productivity improvement of about 19% per QC. A reasonable cost savings in terms of the cost index in unit cost was achieved using yard truck double cycling operation. The genetic algorithm corroborates the achievements thus gained and determines the optimal fleet size that will result in the maximum terminal productivity (quickest vessel turnaround time) with the minimal cost. A time reduction of more than 26% was achieved in most cases, compared to previous research efforts