8,789 research outputs found

    Interaction between intelligent agent strategies for real-time transportation planning

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    In this paper we study the real-time scheduling of time-sensitive full truckload pickup-and-delivery jobs. The problem involves the allocation of jobs to a fixed set of vehicles which might belong to dfferent collaborating transportation agencies. A recently proposed solution methodology for this problem is the use of a multi-agent system where shipper agents other jobs through sequential auctions and vehicle agents bid on these jobs. In this paper we consider such a multi-agent system where both the vehicle agents and the shipper agents are using profit maximizing look-ahead strategies. Our main contribution is that we study the interrelation of these strategies and their impact on the system-wide logistical costs. From our simulation results, we conclude that the system-wide logistical costs (i) are always reduced by using the look-ahead policies instead of a myopic policy (10-20%) and (ii) the joint effect of two look-ahead policies is larger than the effect of an individual policy. To provide an indication of the savings that might be realized with a central solution methodology, we benchmark our results against an integer programming approach

    Interaction between intelligent agent strategies for real-time transportation planning

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    In this paper we study the real-time scheduling of time-sensitive full truckload pickup-and-delivery jobs. The problem involves the allocation of jobs to a fixed set of vehicles which might belong to different collaborating transportation agencies. A recently proposed solution methodology for this problem is the use of a multi-agent system where shipper agents offer jobs through sequential auctions and vehicle agents bid on these jobs. In this paper we consider such a system where both the vehicle agents and the shipper agents are using profit maximizing look-ahead strategies. Our main contribution is that we study the interrelation of these strategies and their impact on the system-wide logistical costs. From our simulation results, we conclude that the system-wide logistical costs (i) are always reduced by using the look-ahead strategies instead of a myopic strategy (10–20%) and (ii) the joint effect of two look-ahead strategies is larger than the effect of an individual strategy. To provide an indication of the savings that might be realized under centralized decision making, we benchmark our results against an integer programming approach

    Single-machine scheduling with stepwise tardiness costs and release times

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    We study a scheduling problem that belongs to the yard operations component of the railroad planning problems, namely the hump sequencing problem. The scheduling problem is characterized as a single-machine problem with stepwise tardiness cost objectives. This is a new scheduling criterion which is also relevant in the context of traditional machine scheduling problems. We produce complexity results that characterize some cases of the problem as pseudo-polynomially solvable. For the difficult-to-solve cases of the problem, we develop mathematical programming formulations, and propose heuristic algorithms. We test the formulations and heuristic algorithms on randomly generated single-machine scheduling problems and real-life datasets for the hump sequencing problem. Our experiments show promising results for both sets of problems

    Carbon Responder: Coordinating Demand Response for the Datacenter Fleet

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    The increasing integration of renewable energy sources results in fluctuations in carbon intensity throughout the day. To mitigate their carbon footprint, datacenters can implement demand response (DR) by adjusting their load based on grid signals. However, this presents challenges for private datacenters with diverse workloads and services. One of the key challenges is efficiently and fairly allocating power curtailment across different workloads. In response to these challenges, we propose the Carbon Responder framework. The Carbon Responder framework aims to reduce the carbon footprint of heterogeneous workloads in datacenters by modulating their power usage. Unlike previous studies, Carbon Responder considers both online and batch workloads with different service level objectives and develops accurate performance models to achieve performance-aware power allocation. The framework supports three alternative policies: Efficient DR, Fair and Centralized DR, and Fair and Decentralized DR. We evaluate Carbon Responder polices using production workload traces from a private hyperscale datacenter. Our experimental results demonstrate that the efficient Carbon Responder policy reduces the carbon footprint by around 2x as much compared to baseline approaches adapted from existing methods. The fair Carbon Responder policies distribute the performance penalties and carbon reduction responsibility fairly among workloads

    Work-life balance and family friendly policies

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    Abstract This paper presents Australian and international research on work-life interaction. We review the work-life policies and practices that are likely to have the greatest impact on work-life outcomes, specifically reducing the negative impact of work on other life domains (work-life interference), and enhancing the positive effect (worklife facilitation). The review addresses four policy areas common in work-life studies of the general workforce: employee-centered flexible work practices; working hours (e.g. access to part-time work); paid and unpaid leave (e.g. parental leave); and access to childcare. It then considers the work-life literature related to two specific industries – the Australian public sector, and health and social services – to identify work-life issues and practices specific to each industry. We then conclude with a general discussion of challenges associated with the policy-practice gap, focusing particularly on work intensification and the role of organisational culture as the catalyst for policy uptake and effectiveness

    Engineering coordination : eine Methodologie für die Koordination von Planungssystemen

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    Planning problems, like real-world planning and scheduling problems, are complex tasks. As an efficient strategy for handing such problems is the ‘divide and conquer’ strategy has been identified. Each sub problem is then solved independently. Typically the sub problems are solved in a linear way. This approach enables the generation of sub-optimal plans for a number of real world problems. Today, this approach is widely accepted and has been established e.g. in the organizational structure of companies. But existing interdependencies between the sub problems are not sufficiently regarded, as each problem are solved sequentially and no feedback information is given. The field of coordination has been covered by a number of academic fields, like the distributed artificial intelligence, economics or game theory. An important result is, that there exist no method that leads to optimal results in any given coordination problem. Consequently, a suitable coordination mechanism has to be identified for each single coordination problem. Up to now, there exists no process for the selection of a coordination mechanism, neither in the engineering of distributed systems nor in agent oriented software engineering. Within the scope of this work the ECo process is presented, that address exactly this selection problem. The Eco process contains the following five steps. • Modeling of the coordination problem • Defining the coordination requirements • Selection / Design of the coordination mechanism • Implementation • Evaluation Each of these steps is detailed in the thesis. The modeling has to be done to enable a systemic analysis of the coordination problem. Coordination mechanisms have to respect the given situation and the context in which the coordination has to be done. The requirements imposed by the context of the coordination problem are formalized in the coordination requirements. The selection process is driven by these coordination requirements. Using the requirements as a distinction for the selection of a coordination mechanism is a central aspect of this thesis. Additionally these requirements can be used for documentation of design decisions. Therefore, it is reasonable to annotate the coordination mechanisms with the coordination requirements they fulfill and fail to ease the selection process, for a given situation. For that reason we present a new classification scheme for coordination methods within this thesis that classifies existing coordination methods according to a set of criteria that has been identified as important for the distinction between different coordination methods. The implementation phase of the ECo process is supported by the CoPS process and CoPS framework that has been developed within this thesis, as well. The CoPS process structures the design making that has to be done during the implementation phase. The CoPS framework provides a set of basic features software agents need for realizing the selected coordination method. Within the CoPS process techniques are presented for the design and implementation of conversations between agents that can be applied not only within the context of the coordination of planning systems, but for multiagent systems in general. The ECo-CoPS approach has been successfully validated in two case studies from the logistic domain.Reale Planungsprobleme, wie etwa die Produktionsplanung in einer Supply Chain, sind komplex Planungsprobleme. Eine übliche Strategie derart komplexen Problemen zu lösen, ist es diese Probleme in einfachere Teilprobleme zu zerlegen und diese dann separat, meist sequentiell, zu lösen (divide-and-conquer Strategie). Dieser Ansatz erlaubt die Erstellung von (suboptimalen) Plänen für eine Reihe von realen Anwendungen, und ist heute in den Organisationsstrukturen von größeren Unternehmen institutionalisiert worden. Allerdings werden Abhängigkeiten zwischen den Teilproblemen nicht ausreichend berücksichtigt, da die Partialprobleme sequentiell ohne Feedback gelöst werden. Die erstellten Teillösungen müssen deswegen oft nachträglich koordiniert werden. Das Gebiet der Koordination wird in verschiedenen Forschungsgebieten, wie etwa der verteilten Künstlichen Intelligenz, den Wirtschaftswissenschaften oder der Spieltheorie untersucht. Ein zentrales Ergebnis dieser Forschung ist, dass es keinen für alle Situationen geeigneten Koordinationsmechanismus gibt. Es stellt sich also die Aufgabe aus den zahlreichen vorgeschlagenen Koordinationsmechanismen eine Auswahl zu treffen, die für die aktuelle Situation den geeigneten Mechanismus identifiziert. Für die Auswahl eines solchen Mechanismus existiert bisher jedoch kein strukturiertes Verfahren für die Entwicklung von verteilten Systems und insbesondere im Bereich der Agenten orientierter Softwareentwicklung. Im Rahmen dieser Arbeit wird genau hierfür ein Verfahren vorgestellt, der ECo-Prozess. Mit Hilfe dieses Prozesses wird der Auswahlprozess in die folgenden Schritte eingeteilt: • Modellierung der Problemstellung und des relevante Kontextes • Formulierung von Anforderungen an einen Koordinationsmechanismus (coordination requirements) • Auswahl/Entwurf eines Koordinationsmechanismuses • Implementierung des Koordinationsverfahrens • Evaluation des Koordinationsverfahrens Diese Schritte werden im Rahmen der vorliegenden Arbeit detailliert beschrieben. Die Modellierung der Problemstellung stellt dabei den ersten Schritt dar, um die Problemstellung analytisch zugänglich zu machen. Koordinationsverfahren müssen die Gegebenheiten, den Kontext und die Domäne, in der sie angewendet werden sollen hinreichend berücksichtigen um anwendbar zu sein. Dieses kann über Anforderungen an den Koordinationsprozess formalisiert werden. Der von den Anforderungen getrieben Auswahlprozess ist ein Kernstück der hier vorgestellten Arbeit. Durch die Formulierung der Anforderungen und der Annotation eines Koordinationsmechanismus bezüglich der erfüllten und nicht erfüllten Anforderungen werden die Motive für Designentscheidungen dieses Verfahren expliziert. Wenn Koordinationsverfahren anhand dieser Anforderungen klassifiziert werden können, ist es weiterhin möglich den Auswahlprozess (unabhängig vom ECo-Ansatz) zu vereinfachen und zu beschleunigen. Im Rahmen dieser Arbeit wird eine Klassifikation von Koordinationsansätzen anhand von allgemeinen Kriterien vorgestellt, die die Identifikation von geeigneten Kandidaten erleichtern. Diese Kandidaten können dann detaillierter untersucht werden. Dies wurde in den vorgestellten Fallstudien erfolgreich demonstriert. Für die Unterstützung der Implementierung eines Koordinationsansatzes wird in dieser Arbeit zusätzlich der CoPS Prozess vorgeschlagen. Der CoPS Prozess erlaubt einen ganzheitlichen systematischen Ansatz für den Entwurf und die Implementierung eines Koordinationsverfahrens. Unterstürzt wird der CoPS Prozess durch das CoPS Framework, das die Implementierung erleichtert, indem es als eine Plattform mit Basisfunktionalität eines Agenten bereitstellt, der für die Koordination von Planungssystemen verantwortlich ist. Im Rahmen des CoPS Verfahrens werden Techniken für den Entwurf und die Implementierung von Konversation im Kontext des agenten-orientiertem Software Engineerings ausführlich behandelt. Der Entwurf von Konversationen geht dabei weit über Fragestellung der Formatierung von Nachrichten hinaus, wie dies etwa in den FIPA Standards geregelt ist, und ist für die Implementierung von agentenbasierten Systemen im Allgemeinen von Bedeutung. Die Funktionsweise des ECo-CoPS Ansatzes wird anhand von zweierfolgreich durchgeführten Fallstudien aus dem betriebswirtschaftlichen Kontext vorgestellt

    Variable Weighted Multi-Objective Multi-Dimensional Genetic Algorithm for Demand Response Scheduling in a Smart Grid

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    This research presents the optimized scheduling of demand response loads of a residential community of 30 houses using a multi-objective multi-dimensional genetic algorithm (MOMD-GA) with a variable weighted objective function. Incorporating day ahead hourly real time pricing (RTP), the MOMD-GA attempts to present possible optimized dispatch patterns with their associated penalties and constraints (environmental, consumers and suppliers) thus providing system operators (SOs) and distribution network operators (DNOs) sufficient data for real time decision making. The variable weights for each considered component of the cost function is chosen to force the MOMD-GA towards exploring optimum solutions with lower environmental cost. Further shown are the trade-offs in selecting particular dispatch bias (consumer, supplier, environmental and optimized) and the impact of the various dispatch scenarios on the cost of overall electricity bill of the community
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