3,036 research outputs found
Comparison of agent-based scheduling to look-ahead heuristics for real-time transportation problems
We consider the real-time scheduling of full truckload transportation orders with time windows that arrive during schedule execution. Because a fast scheduling method is required, look-ahead heuristics are traditionally used to solve these kinds of problems. As an alternative, we introduce an agent-based approach where intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. This approach offers several advantages: it is fast, requires relatively little information and facilitates easy schedule adjustments in reaction to information updates. We compare the agent-based approach to more traditional hierarchical heuristics in an extensive simulation experiment. We find that a properly designed multiagent approach performs as good as or even better than traditional methods. Particularly, the multi-agent approach yields less empty miles and a more stable service level
Human-Agent Decision-making: Combining Theory and Practice
Extensive work has been conducted both in game theory and logic to model
strategic interaction. An important question is whether we can use these
theories to design agents for interacting with people? On the one hand, they
provide a formal design specification for agent strategies. On the other hand,
people do not necessarily adhere to playing in accordance with these
strategies, and their behavior is affected by a multitude of social and
psychological factors. In this paper we will consider the question of whether
strategies implied by theories of strategic behavior can be used by automated
agents that interact proficiently with people. We will focus on automated
agents that we built that need to interact with people in two negotiation
settings: bargaining and deliberation. For bargaining we will study game-theory
based equilibrium agents and for argumentation we will discuss logic-based
argumentation theory. We will also consider security games and persuasion games
and will discuss the benefits of using equilibrium based agents.Comment: In Proceedings TARK 2015, arXiv:1606.0729
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Centralized versus market-based approaches to mobile task allocation problem: State-of-the-art
Centralized approach has been adopted for finding solutions to resource allocation problems (RAPs) in many real-life applications. On the other hand, market-based approach has been proposed as an alternative to solve the problem due to recent advancement in ICT technologies. In spite of the existence of some efforts to review the pros and cons of each approach in RAPs, the studies cannot be directly applied to specific problem domains like mobile task allocation problem which is characterised with high level of uncertainty on the availability of resources (workers). This paper aims to review existing studies on task allocation problems(TAPs) focusing on those two approaches and their comparison and identify major issues that need to be resolved for comparing the two approaches in mobile task allocation problems. Mobile Task Allocation Problem (MTAP) is defined and its problematic structures are explained in relation with task allocation to mobile workers. Solutions produced by each approach to some applications and variations of MTAP are also discussed and compared. Finally, some future research directions are identified in order to compare both approaches in function of uncertainty emerging from the mobile nature of the MTAP
Agent-based transportation planning compared with scheduling heuristics
Here we consider the problem of dynamically assigning vehicles to transportation orders that have di€erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule their own routes. They interact with job agents, who strive for minimum transportation costs, using a Vickrey auction for each incoming order. We use simulation to compare the on-time delivery percentage and the vehicle utilization of an agent-based planning system to a traditional system based on OR heuristics (look-ahead rules, serial scheduling). Numerical experiments show that a properly designed multi-agent system may perform as good as or even better than traditional methods
Cooperative intelligent system for manufacturing scheduling
Hybridization of intelligent systems is a
promising research field of computational intelligence
focusing on combinations of multiple approaches to
develop the next generation of intelligent systems.
In this paper we will model a Manufacturing System by
means of Multi-Agent Systems and Meta-Heuristics
technologies, where each agent may represent a processing
entity (machine). The objective of the system is to deal with
the complex problem of Dynamic Scheduling in
Manufacturing Systems
MASDScheGATS: a prototype system for dynamic scheduling
A manufacturing system has a natural dynamic nature observed through several kinds of random occurrences and
perturbations on working conditions and requirements over time. For this kind of environment it is important the
ability to efficient and effectively adapt, on a continuous basis, existing schedules according to the referred
disturbances, keeping performance levels. The application of Meta-Heuristics and Multi-Agent Systems to the
resolution of this class of real world scheduling problems seems really promising.
This paper presents a prototype for MASDScheGATS (Multi-Agent System for Distributed Manufacturing
Scheduling with Genetic Algorithms and Tabu Search)
AN AGENT-BASED COOPERATIVE MECHANISM FOR INTEGRATED PRODUCTION AND TRANSPORTATION PLANNING
This paper presents a decentralized cooperative economic scheduling mechanism for a supply chain environment. For this purpose, we design autonomous agents that minimize the production or transportation costs and outsourcing costs incurred by the external execution of a task. The decentralized cooperative scheduling approach comprises two parts: the individual optimization an agent\u27s local schedule and the cooperative contract optimization, either by outsourcing the task or by (re-)contracting the release time and due time with the contract partners aiming to maximize their total profits. A negotiation mechanism based on trust accounts is employed to protect the agents against systematic exploitation by their partners
Autonomic computing for scheduling in manufacturing systems
We describe a novel approach to scheduling resolution by combining
Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired
Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm
aiming at embedding applications with a management structure similar to a central
nervous system. A natural Autonomic Computing evolution in relation to Current
Computing is to provide systems with Self-Managing ability with a minimum human
interference. In this paper we envisage the use of Multi-Agent Systems paradigm
for supporting dynamic and distributed scheduling in Manufacturing Systems
with Autonomic properties, in order to reduce the complexity of managing
systems and human interference. Additionally, we consider the resolution of realistic
problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet
Line will be evaluated. Results show that proposed approach has advantages when
compared with other scheduling systems
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