An Integrated Environment for Embedded Hard Real-Time Systems Scheduling with Timing and Energy Constraints

Tavares, Eduardo; Barreto, Raimundo; Maciel, Paulo; Oliveira, Marcelo Costa; Arcoverde, Adilson; Alves, Gabriel; Lima, Ricardo; Barros, L.O.; Bessa, Arthur

doi:10.1007/11556930_40

Cited by 1 publication

(1 citation statement)

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“…It needs too much work to build a complex system model. It needs too much repetitive work to build a complex system model with Petri net [2] . It has a high expectation of modeler to build a complex system model with Petri net.…”

Section: A Modeling Of Multi-resource Allocation Schedulingmentioning

confidence: 99%

Modeling and Simulation on Dynamic Allocation and Scheduling of Multi-resource problem

Hu²,

Cheng³

et al. 2011

JCP

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<p class="Abstract">Resource-constrained project scheduling and configuration determines the progress of the construction and quality. This paper proposes a simulation modeling method based on 0-1 variables according to multi-resource dynamic allocation and scheduling of discrete features, use digital circuit based simulation method to make a 0-1 variables model for multi-resource dynamic allocation and configuration problem. This paper constructs a model for dynamic resources allocation and scheduling based on priority and fuzzy theory. And use ant colony algorithm with trust mechanism to solve it. The algorithm simulates ant feeling of mutual trust and act and is subject to significant interaction between consciousness and unconsciousness in path selection, so that in the initial time to use their own experience, thereafter conditionally accept the trust mechanism for peers to influence the information volume, at the same time modify the amount of information on the path adaptively. In this way have good balance between accelerating the convergence and preventing early-maturing, stagnation. Each ant as an Agent, the autonomy of ant Agent shall be autonomous; each has some control of their own behavior. Through the port logistics scheduling system simulation applications, the results reflect the algorithm has good convergence and meet the actual production.</p>

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Section: A Modeling Of Multi-resource Allocation Schedulingmentioning

confidence: 99%