System-wide Decisions Research Articles

Decentralised protocols for autonomous mobile robots in material handling: inductive learnings from centralised controller

As customer demands for personalised items continue to grow, flexible material handling systems are becoming indispensable in manufacturing to accommodate the increasing product variety and demand fluctuations. Consequently, the adoption of autonomous mobile robots (AMRs) is on the rise, driven by their capability to autonomously respond to changes in demand. However, the myopic nature of AMRs’ autonomous decision-making may limit their ability to consider a system-wide perspective. To address this challenge, we propose an AI-based platform that extracts knowledge from a centralised agent, which makes system-wide decisions offline, and integrates this knowledge into decentralised AMRs operating online. We develop a mixed-integer linear programming model, a genetic algorithm, and a scheduling algorithm to generate centralised solutions. Additionally, we design features to convert these solutions into training instances and employ artificial neural networks to derive knowledge from them. This knowledge is then integrated into each AMR as a protocol. Through experiments, we evaluate the performance of the developed protocol, demonstrating its superiority over other dispatching rules in minimising the total weighted tardiness of transportation requests and the total waiting time of transportation requests at storages.

Intelligent and Efficient IoT Through the Cooperation of TinyML and Edge Computing

The coordinated integration of heterogeneous TinyML-enabled elements in highly distributed Internet of Things (IoT) environments paves the way for the development of truly intelligent and context-aware applications. In this work, we propose a hierarchical ensemble TinyML scheme that permits system-wide decisions by considering the individual decisions made by the IoT elements deployed in a certain scenario. A two-layered TinyML-based edge computing solution has been implemented and evaluated in a real smart-agriculture use case, permitting to save wireless transmissions, reduce energy consumption and response times, at the same time strengthening data privacy and security.

An updatable and comprehensive global cargo maritime network and strategic seaborne cargo routing model for global containerized and bulk vessel flow estimation

The global maritime system provides the backbone of logistics operations for global supply chains and international trade. This paper aims to develop a unifying global network representation and strategic, system-wide decision model, the Strategic Cargo Routing Model, incorporating both liner and bulk shipping markets to estimate real-world traffic flows and study traffic patterns at the global scale. Specifically, taking a shipper's perspective, containerized and bulk movements are jointly modelled within a mixed-integer linear program that includes inbound, outbound, and transshipment cargo flows at ports. An iterative approach that combines heuristic Gradient Descent and Relax-and-Fix Decomposition methods is proposed for the calibration and solution of the Strategic Cargo Routing Model over a proposed joint liner and bulk services Global Cargo Shipping Network representation. The Global Cargo Shipping Network contains 161 seaports covering 52 countries. It is created from updatable, publicly available, data sources, and all data needed for the network representation are made available. Sufficient network details, as well as data sources and methods for extracting needed inputs, are given to allow others to use and update the network. Using the developed maritime network, mathematical model and calibration-solution methodology, 2018 global maritime traffic flow patterns were estimated. The estimates were found to achieve a 91% fit overall to real-world average annual port throughputs. This strategic model provides support to evaluate future, real-world, worldwide changes, such as increased seaborne trade demand, new routes, shipping infrastructure expansion, and transport policies.

University of California Replacement of Cesium Irradiators with Alternative Technologies.

The University of California possesses a large number of Cs irradiators that are used in a wide variety of medical and research applications. The university president made a system-wide decision to reduce the potential threat of malevolent use of Cs by switching wherever feasible to x-ray irradiators over a 3-y period of time. A Radioactive Source Replacement Working Group of involved faculty was formed to study the topic and to make recommendations as to when alternative technologies could offer equivalency. The Working Group concluded that x-ray irradiators could replace Cs irradiators in most applications, with some likely exceptions. They found that the depth dose curve for the 320 kVp x-ray irradiator was found to be nearly identical to that of Cs down to a depth in tissue of 4 cm. It was concluded that x rays (energies ≤320 keV) are more biologically effective than Cs gamma rays, suggesting that lower doses of x rays will be required to achieve the same biological endpoint as Cs gamma rays. A simple conversion factor for equating x-ray effects to Cs effects was not recommended because relative biological effectiveness depends on multiple factors. They concluded that each experiment should be individually calibrated when converting from Cs irradiators to x-ray irradiators. The lessons learned from implementing the project to date have shown the importance of having senior management buy-in, involving the research community in the decision making process and allowing for exceptions where equivalency of Cs to x ray cannot be established.

Integrating X-ray technologies with intelligent transportation systems for enhancing the international maritime security

Over the past decade, the use of X-ray scanning technology for cargo inspection has been on the rise due to its effectiveness in providing clear and unobtrusive views of the contents of items hidden inside containers. Also, it is able to add intelligence and to minimise human intervention in the cargo inspection process without opening up suspected containers. Although X-ray scanning technology is proven to be useful for automatic detection of potential dangers or illicit contents (e.g., narcotics) inside containers, its usefulness may be constrained unless it can be embedded within the system-wide decision support tool. Such a tool includes an intelligent transportation system (ITS) which is designed to improve transportation safety and mobility through the seamless integration of information and communication technology, transportation infrastructure, and shipping vessels. This paper is one of the first to combine X-ray scanning technology with ITS for cargo inspection procedures and gauges its usefulness for enhancing maritime security in global supply chain operations.

Waste not, want not

To achieve optimal performance, garbage-collected applications must balance the sizes of their heaps dynamically. Sizing the heap too small can reduce throughput by increasing the number of garbage collections that must be performed. Too large a heap, however, can cause the system to page and drag down the overall throughput. In today's multicore, multiprocessor machines, multiple garbage-collected applications may run simultaneously. As a result, each virtual machine (VM) must adjust its memory demands to reflect not only the behavior of the application it is running, but also the behavior of the peer applications running on the system. We present a memory management system that enables VMs to react to memory demands dynamically. Our approach allows the applications' heaps to remain small enough to avoid the negative impacts of paging, while still taking advantage of any memory that is available within the system. This memory manager, which we call Poor Richard's Memory Manager , focuses on optimizing overall system performance by allowing applications to share data and make system-wide decisions. We describe the design of our memory management system, show how it can be added to existing VMs with little effort, and document that it has almost no impact on performance when memory is plentiful. Using both homogenous and heterogenous Java workloads, we then show that Poor Richard's memory manager improves average performance by up to a factor 5.5 when the system is paging. We further show that this result is not specific to any garbage collection algorithm, but that this improvement is observed for every garbage collector on which we test it. We finally demonstrate the versatility of our memory manager by using it to improve the performance of a conservative whole-heap garbage collector used in executing .Net applications.

Modelling Market-Based Decentralised Management Systems

A centralised approach to management of distributed systems works well when applied to relatively small-scale systems. As the scale grows, so do the problems of making appropriate system-wide decisions and co-ordinating their execution. As a result, large centrally managed systems tend to be ponderous and rigid. Devolving decision-making responsibility to local units means that locally appropriate responses to changed circumstances can be made rapidly. However, it is quite possible that local decisions in different elements of the system will interfere adversely. How does one co-ordinate local decisions in large systems without re-introducing central control and its associated problems? The decentralised approach adopted here is to craft the interactions between local decision-making elements (agents), in order that effective management of the overall system is an emergent result of repeated local decisions and interactions. The general solution to this problem is an ambitious long-term research goal. This paper presents some results that offer a way forward within a particular class of problem in which the interactions between agents can be modelled as sale and purchase of commodity items.

Methodological Problems In Determining Media Effects On Criminal Justice: A Review And Suggestions For The Future

Arguably, the relationship between the mass media and the criminal justice system is one of the more important, especially regrading the formation of criminal justice policies and general decision-making in the system.1 Criminal justice policy and decision making are both systematic and individual case level phenomena (Doppelt, 1990). That is, criminal justice policy is ultimately determined by both ad hoc decisions made by criminal justice personnel and offenders regarding individual crimes and cases and by system-wide decisions that affect entire classes of offenses and cases.2 In the area of media and criminal justice, two questions arise. The first, "What is the relationship between the media and criminal justice decision making?," has not been answered with any clarity and leads to a second question, "Despite a significant amount of research and interest, why isn't the relationship better understood?" This essay discusses underlying methodological problems that make deciphering the media and criminal justice relationship inherently difficult. Some of these problems are common issues found throughout the social sciences. However, they are exacerbated in the media-criminal justice area. Other problems are unique to the media-criminal justice relationship and arise due to the existence of unusual media relationships with criminal justice policy and decision-making.