An Integrated Network Modeling Framework for Analysis of Multi-line Order Pick Systems

Poster 1

An Integrated Network Modeling Framework for Analysis of Multi-line Order Pick Systems

Due to demanding service levels in E-commerce order fulfillment, modeling and analysis of order picking processes in warehouses deserve special attention. With a particular focus on multi-line E-commerce orders, we develop modeling tools that are necessary to analyze the order consolidation delays in the downstream pick stations. We develop a queuing network modeling framework for integrated analysis of upstream (storage system) and downstream (pick system). We apply our modeling approach to an integrated order-pick system that includes a shuttle-based storage and retrieval system, and a single pick station. Using simulations, we test the effect of the storage system configuration on the order throughput time

Performance Trade-offs in Layouts For Relief Centers

At a disaster affected region, relief centers distribute critical supplies and aid to the affected victims. Unlike traditional distribution centers, relief centers experience significant ‘crowd effects’ due to the sudden influx of victims in a confined space. Using knowledge from studies on pedestrian traffic flow, specialized state dependent queuing models are developed to model the flow of victims along the walkways setup at a relief center. The underlying queuing network model is analyzed to derive expressions for the average times that victims experience before they receive the service at the relief center. The research shows that crowd density effects lead to significant increase in congestion and queuing delays underscoring the importance of developing specialized queuing models that assess the impact of congestion effects on alternative layouts of relief centers

Modeling and Design of Container Terminal Operations

Design of container terminal operations is complex because multiple factors affect the operational perfor- mance. These factors include: topological constraints, a large number of design parameters and settings, and stochastic interactions that interplay among the quayside, vehicle transport, and stackside processes. In this research, we propose new integrated queuing network models for rapid design evaluation of container terminals with Automated Lift Vehicles (ALVs) and Automated Guided Vehicles (AGVs). These models offer the flexibility to analyze alternate design variations and develop insights. For instance, the effect of alternate vehicle dwell point policy is analyzed using state-dependent queues, whereas the efficient terminal layout is determined using variation in the service time expressions at the stations. Further, using embedded Markov chain analysis, we develop an approximate procedure for analyzing bulk container arrivals. These models form the building block for design and analysis of large-scale terminal operations. We test the model efficacy using detailed in-house simulation experiments and real-terminal validation by partnering with an external party

Stochastic Modeling of Unloading and Loading Operations at a Container Terminal using Automated Lifting Vehicles

With growing worldwide trade, container terminals have grown in number and size. Many new terminals are now automated to increase operational efficiency. The key focus is on improving seaside processes, where a distinction can be made between single quay crane operations (all quay cranes are either loading or unloading containers) and overlapping quay crane operations (some quay cranes are loading while others are unloading containers). From existing studies, it is not clear if the design insights obtained from analyzing single operations, such as optimal stack layout, are consistent with the insights obtained from analyzing overlapping operations. In this paper, we develop new integrated stochastic models for analyzing the performance of overlapping loading and unloading operations that capture the complex stochastic interactions among quayside, vehicle, and stackside processes. Using these integrated models, we are able to show that that there are stack layout configurations that are robust for both single (either loading or unloading) and for overlapping (both loading and unloading) operations

A Two-level Stochastic Model to Estimate Vessel Throughput Time

A good estimate of the vessel sojourn time is essential for better planning and scheduling Of container terminal resources,such as berth scheduling,quay crane(qc)assignment And scheduling,and fleet size planning. However,estimating the expected vessel so journ Time is a complex exercise because the time is dependent on several terminal operating Parameters such as the size of the vessel,the number of containers to be loaded and Unloaded,and the through put of the qcs. The through put of the qcs in turn depends On the type and number of transport vehicles,number of stack blocks,the topology of The vehicle travel path,the layout of the terminal,and several event uncertainties. To Address the modelling complexity, we propose a two-level stochastic model to estimate The expected vessel so journ time. The higher level model consists of a continuous-time Markovchain(ctmc)that captures the effect of qc assignment and scheduling on vessel Sojourn time. The lower level model is a multi class closed queuing network(cqn)that Models the dynamic interactions among the terminal resources and provides an estimate Of the transition rate input parameters to the higher level ctmc model. We estimate the Expected vessel sojourn times for several container load and unload profiles and discuss The effect of terminal layout parameters on vessel so journ times

A Fluid Flow Queuing Network Model for Performance Analysis of Bulk Liquid Terminals

Bulk liquid terminals play a crucial role in enabling the timely discharge and loading of liquid from the tankers and also facilitating oil transport to the hinterland via pipelines and external trucks. However, the speed of operations (and demurrage costs in the likely event of vessel handling delays) depends on the capacities of all terminal resources including berth, loading arms, and storage tank farms. Today, there is a limited understanding of how the interactions among the resources affect the overall vessel sojourn time performance. Using an integrated fluid flow simulation model of a bulk liquid terminal, we are able to gain much insight into the discharge operations of a tanker, in particular, implications of storage tank capacity feedback on the loading arm utilization and vessel sojourn times

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