multi-agent based integration of scheduling algorithms EMBA论文

l are classified resource agents and job agents. ouelhadj et al.[4] defined an “actor” architecture where agents is associated with particular functions which are distributed over resource agents and use contact net protocol for dynamic scheduling. rabelo et al.[5] studied multi-agent based scheduling in virtual enterprise environments on the base of holos scheduling system, which is a framework devoted to derive “instance” of agile scheduling system.

2) process-type mass

predominant agents in such mass are called process agents. they map processes that realize a function [6], a computation [7], an activity [8], etc. each process agent can only solve part of a problem. different agents work together by collaboration to achieve system’s goal, as people coming from different fields to a team will do.

unlike entity-type mass that mainly composes of resource agents and job agents, process-type mass has no typical architecture. there is much difference among researches of such system by now. lau[6] defined a mass for fms scheduling, which is capable of individual learning and group learning. agents in the system are scheduling models that have ability of predictive scheduling and making reaction toward environment or other agents. morikawa et al.[7] use agent maps genetic algorithm in his research of scheduling in process of cim. the whole process of solving problem is divided into several stages. each agent responses one stage. they work one by one. one agent gets input from upriver agents and output result to downriver agents. gary knotts[8] present a multi-agent scheduling method to solve multimode, resource-constrained project scheduling problem. agents map activities of project.

baker[9] reviewed most scheduling algorithms and proved that they can be used into multi-agent heterarchy. so we consider to integrating more scheduling algorithms into one framework to adapt requirement of complicated production environment by defining a process-type mass. the agents in our architecture map scheduling algorithms.

the rest of the paper is organized as follow. in section 2, we introduce concept of integration of scheduling algorithms. in section 3, we detail the solution of multi-agent based integration of scheduling algorithms. in the last section, we conclude by descr

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