Ngoc Anh Dung Do

A simulation-based genetic algorithm approach for reducing emissions from import container pick-up operation at container terminal

Emissions from idle truck engines are a main source of pollution at container terminals. In this study, we focus on reducing such emission from waiting trucks as well as the related crane operations with a new truck arrival control method that gives individual truck limited time slots for entry. We develop a method to optimize the time slot assignment for individual trucks, aiming at minimizing total emissions from trucks and cranes at import yards. The method applies discrete event simulation to estimate total truck waiting times and crane moving distance, and then applies a genetic algorithm to minimize the generated emissions from these trucks and cranes. The experiment result shows that the truck arrivals should be controlled based on the stacking of import containers, and that such control is necessary for reducing truck idling emissions at a congested container terminal.

An Empirical Investigation of Lead Time Distributions

This paper proposes a methodology for analyzing lead time behavior. The method focuses on identifying whether lead times are in fact identically independently distributed (i.i.d.). The method uses a combination of time series analysis, Kolmogorov-Smirnov’s test for similar distributions and data sampling to arrive at its result. The method is applied to data obtained from a manufacturing company. The conclusions are that while the lead time to customers can for some products be assumed to be i.i.d. this is not uniformly true. Some products’ lead times are in fact neither independently nor identically distributed.

Production and Resource Scheduling in Mass Customization with Dependent Setup Consideration

Mass customization has been implemented in services and manufactures to increase the competitiveness of companies. In a manufacturing company, the procedure for production and resource scheduling has to be changed to adapt to mass customization. A good production and resource scheduling will contribute to the success of mass customization. This paper addresses the problem of production and resource scheduling for a production system with dependent setup and internal transportation such as AGVs in a mass customization environment. A constraint-programming-based methodology is developed to satisfy the customer demands on-time. An example is presented to illustrate the performance of the proposed methodology.

Towards an Analysis Methodology for Identifying Root Causes of Poor Delivery Performance

Abstract This paper presents an analysis methodology for establishing the demand stability of the planning environment faced by a company and the impact on the stability from changes to sales order. The methodology focuses on three critical planning parameters derived from customer orders: product mix, volume, and order sizes. Furthermore, the methodology links the delivery performance of a company to the changes made to sales orders. Based on a test case application of the methodology, it is concluded that by accepting changes, the demand faced by the case company has become more unstable on product mix, volume, and the number of order lines per period, while some added stability has been achieved with regards to the order size distributions. Ultimately, by applying the methodology to the case company, it is found that by changing the sales orders, the company does not improve the delivery performance.

Quantifying the Bullwhip Effect of Multi-echelon System with Stochastic Dependent Lead Time

Considering a multi-echelon system, the bullwhip effect is recognized as a significant factor with regards to the inventory management. This paper focuses on the effect of stochastic dependent lead time on the bullwhip effect. Simulation based approach is used to quantify the bullwhip effect with different demand and lead time distributions. The experiment results show that the dependent lead time has much effect on the 2nd echelon (from the downstream to the upstream) and bullwhip effect decrease significantly if the variance of this echelon decreases.

Lead Times and Order Sizes—A not so Simple Relationship

Order quantity and lead time are two critical aspects of inventory management. In literature, lead time is considered as a constant or an uncontrollable stochastic variable. Theoretically, the order size has linear relationship with lead time meaning that order size increases when lead time increases. A data analysis from a Danish company reveals that the relationship between lead time and order size are not so simple. This paper focuses on analyzing the relationship between lead time and order size in order to answer two questions: (1) whether lead time is affected by order size or not; and (2) whether lead time and order size has linear relationship or not.

Reducing Truck Emissions in Import Operations at Container Terminal—A Case Study in a Singaporean Port

Emissions from idle truck engines are a main source of pollution from transportation, and emission reduction from idle truck engines at container terminal has for this reason become a priority. At the import yard of a container terminal, an incoming truck has to wait for its turn to be loaded with containers which are then to be delivered to a customer. Reducing waiting time of trucks means that truck emissions are decreased as well as the competition of port increases. In this study, the emission from idle truck engines at the import yard is considered. The goal of this study is to develop a methodology for reducing emissions generated by trucks idling at import yards. The proposed method includes a mathematical model for minimizing truck emissions. In the model, total truck waiting time in the yard is estimated using discrete event simulation. To solve this model, a genetic algorithm is proposed. A case study in a Singaporean port is used for conducting experiments. The experiment result shows that the manager of a container terminal should control truck arrivals based on the stacking of import containers in order to reduce the truck idling time and thereby the truck emissions in the import yard.

RT-PLG: Real Time Process Log Generator

Streaming process mining has been rising as an emergent tool to analyze industrial practices. Obviously, the advance of streaming process mining requires the availability of a suite of real-world business processes and the execution logs in the real time manner. Literally, it is hard to obtain it. This paper aims to develop a real time process log generator for the usage of streaming process mining tool. The real time process log generator (RT-PLG) is constructed in an independent tool. Afterward, the RT-PLG is utilized to generate a synthetic log for streaming process mining. The tool has been evaluated using an existing simulation model.