Optimization of empty container movements using street-turn: Application to Valencia hinterland

Empty maritime container logistics is one of the most relevant costs for shipping companies. In this paper two mathematical models (based on two different container movement patterns, i.e. with and without street-turns) were defined to optimize land empty container movements among shippers, consignees, terminals and depots, along with minimizing storage costs. One of the proposed optimization models was embedded in a simple Decision Support System (DSS) and then tested with real data, based on the operations in Valencia s (Spain) hinterland. The results obtained confirm the benefits of implementing these kinds of models for the company, and additional experiments assess and quantify the advantage of using the more complex approach that is able to implement street-turn patterns.This research has been funded by the Spanish Ministry of Science and Innovation through Grant DPI2010-16201 and FEDER.Furió, S.; Andrés Romano, C.; Adenso Díaz, B.; Lozano Segura, S. (2013). Optimization of empty container movements using street-turn: Application to Valencia hinterland. Computers and Industrial Engineering. 66(4):909-917. https://doi.org/10.1016/j.cie.2013.09.003S90991766

The Realization of a Stochastic Optimization Model for the Empty Container Inventory Based on EDI Information

This paper explores the feasibility of realizing the optimization of the empty container inventory based on EDI information. Firstly the basic structure of the stochastic optimization model for the empty container inventory has been described and two models including the infinite and finite horizon model were constructed. Then several statistical test have been taken and the distribution of the inland turnover time of the empty container, the empty containers\u27 supply and demand identified. Finally we adopt PB to develop the DSS for the stochastic optimization of container inventory based on the shipping EDI information

Real-time Container Transport Planning with Decision Trees based on Offline Obtained Optimal Solutions

Hinterland networks for container transportation require planning methods in order to increase efficiency and reliability of the inland road, rail and waterway connections. In this paper we aim to derive real-time decision rules for suitable allocations of containers to inland services by analysing the solution structure of a centralised optimisation method used offline on historic data. The decision tree can be used in a decision support system (DSS) for instantaneously allocating incoming orders to suitable services, without the need for continuous planning updates. Such a DSS is beneficial, as it is easy to implement in the current practice of container transportation. Earlier proposed centralised methods can find the optimal solution for the intermodal inland transportation problem in retrospect, but are not suitable when information becomes gradually available. The main contributions are threefold: firstly, a structured method for creating decision trees from optimal solutions is proposed. Secondly, an innovative method is used for obtaining multiple equivalent optimal solutions to prevent overfitting of the decision tree. And finally, a structured analysis of three error types is presented for assessing the quality of an obtained tree. A case study illustrates the method’s purpose by comparing the quality of the resulting plan with alternative methods

Priority Control of Berth Allocation Problem in Container Terminals

This paper presents a decision support system for the core problem of berth allocation decision in a container terminal. The allocation of berths to the calling vessels is complex with the fact that different service level requirements are required for different vessels. Terminal managers demand for effective decision support systems that would aid them with the allocation problem considering service priorities. Consequently, this study provides a DSS, built by a dynamic discrete-event simulation model embedded with an optimization tool that determines the priority controls for the berth allocation to the calling vessels. To show the practical application of the DSS, a comprehensive case study from a Turkish container terminal considering the current state and future expansion plans that also provides an indication of the usability aspect of the program on other ports around the world has been conducted. Further experiments are conducted based on data from the Port of Rotterdam. The DSS presented in this study may help port authorities in determining more efficient allocation decisions within a container terminal

A Big-Data-Analytics Framework for Supporting Logistics Problems in Smart-City Environments

Abstract Containers delivery management is a problem widely studied. Typically, it concerns the container movement on a truck from ships to factories or wholesalers and vice-versa. As there is an increasing interest in shipping goods by container, and that delivery points can be far from railways in various areas of interest, it is important to evaluate techniques for managing container transport that involves several days. The time horizon considered is a whole working week, rather than a single day as in classical drayage problems. Truck fleet management companies are typically interested in such optimization, as they plan how to match their truck to the incoming transportation order. This planning is a relevant both for strategical consideration and operational ones, as prices of transportation orders strictly depends on how they are fulfilled. It is worth noting that, from a mathematical point of view, this is an NP-Hard problem. In this paper, a Decision Support System for managing the tasks to be assigned to each truck of a fleet is presented, in order to optimize the number of transportation order fulfilled in a week. The proposed system implements a hybrid optimization algorithm capable of improving the performances typically presented in literature. The proposed heuristic implements an hybrid genetic algorithm that generate chains of consecutive orders that can be executed by a truck. Moreover, it uses an assignment algorithm based to evaluate the optimal solution on the selected order chains

New Concept of Container Allocation at the National Level: Case Study of Export Industry in Thailand

This paper presents container allocation technique of which minimizing the total opportunity loss of an export industry in Thailand. This new allocation concept applies as a strategic management tools at the national level since it is consistent to the characteristics of the container supply chain management in Thailand. The first section of this paper presents the review of facts and problems of container supply chain management. It reveals that containerization system is significant to the international trade as it holds good characteristics of sea transportation. It can transport a lot of products while minimize the damage of goods. Supply chain management of the containerization system presents and shows that there are four main players in managing the container – principal, port, container depot, and customer. After an intensive review of containerization system’s problem, the most common problem that all parties have encountered is an imbalance between demand and supply of container. The well-known solution to the stated problem is relocation of containers between various places using optimization technique, which aims to minimize operation cost. Indeed, those solutions are unable solve the containerization system’s problem in Thailand: lacking their own fleets: having no bargaining power in relocating container between areas as needed. In the present, many of Thai exporters face with losses of sales or profit because they cannot find enough or proper containers to transport their goods to the customer. The authors, therefore, have seen that those problems need to be strategically solved by the government. The limited number of containers must be properly allocated to the exporter with regard to the minimum losses to the economics of the country. The main contributions of this paper are two folds. First, the opportunity losses of the various export industry are indicated when lack of containers, Second, the mathematical model has been formulated using linear programming technique with several constraints, such as, demand, supply, obsolete time, operating cost, lead time etc. The authors hope that the new concept presented in this paper will provide the great contribution for other countries, which face the same problem of Thailand. Keywords: Container Management, Opportunity Loss, Allocation Problem, Optimization, International Trad

An artificial neural network based decision support system for energy efficient ship operations

Reducing fuel consumption of ships against volatile fuel prices and greenhouse gas emissions resulted from international shipping are the challenges that the industry faces today. The potential for fuel savings is possible for new builds, as well as for existing ships through increased energy efficiency measures; technical and operational respectively. The limitations of implementing technical measures increase the potential of operational measures for energy efficient ship operations. Ship owners and operators need to rationalise their energy use and produce energy efficient solutions. Reducing the speed of the ship is the most efficient method in terms of fuel economy and environmental impact. The aim of this paper is twofold: (i) predict ship fuel consumption for various operational conditions through an inexact method, Artificial Neural Network ANN; (ii) develop a decision support system (DSS) employing ANN based fuel prediction model to be used on-board ships on a real time basis for energy efficient ship operations. The fuel prediction model uses operating data -‘Noon Data’ - which provides information on a ship’s daily fuel consumption. The parameters considered for fuel prediction are ship speed, revolutions per minute (RPM), mean draft, trim, cargo quantity on board, wind and sea effects, in which output data of ANN is fuel consumption. The performance of the ANN is compared with multiple regression analysis (MR), a widely used surface fitting method, and its superiority is confirmed. The developed DSS is exemplified with two scenarios, and it can be concluded that it has a promising potential to provide strategic approach when ship operators have to make their decisions at an operational level considering both the economic and environmental aspects

Reverse logistics

This paper gives an overview of scientific literature that describes and discusses cases of reverse logistics activities in practice. Over sixty case studies are considered. Based on these studies we are able to indicate critical factors for the practice of reverse logistics. In addition we compare practice with theoretical models and point out research opportunities in the field