Genetic algorithms using multi-objectives(10)

We are interested in a job-shop scheduling problem corresponding to an industrial problem. Gantt diagram’s optimization can be considered as an NP-difficult problem. Determining an optimal solution is almost impossible, but trying to improve the current s

A.Cardonetal./RoboticsandAutonomousSystems33(2000)179–190185

Ontheotherhand,thestaticmodeldoesnotin-cludethepossibleinteractionbetweentheworkshopandtheenvironmentsuchasastrike,amachinefailure,etc.

Inthestaticmodel,theplacingobtainedgivesasolutioncorrespondingtothescheduleofalljobs.But,bynegotiations,theschedulecanbebuiltstepbystep.Forexample,ifajobarrivestoosoon,thedelaycorrespondingtothetardinessincreases.Therefore,ifwecanchangethescheduleduringthecalculationprocess,wecanimprovethetardiness.Itisoneofoureconomicfunctions.

7.ActionsontheGanttdiagram

TheJSSPdoesnotadmitacomputablesolution,sotheuseofmulti-agentsystemsforthesolvingofsuchaproblemseemsreasonable[23].Multi-agentsystemresearchisconcernedwiththebehaviorofasetofagentsthatcooperateinordertosolveaproblem[31].Inamulti-agentsystem(MAS)[11],theagentsareseenaslittleproblemsolversthatcooperativelyworkinordertosolveaproblem[58]farbeyondtheirin-dividualabilities[13].Here,weconsideranagentasanentitywithgoals,actionstoaccomplishandareasofknowledge,whichissituatedinitsenvironment[56].Therefore,becauseoftheknowledgeofagents,rulesofactions,etc.,theMASwillhave,forprinci-palobjective,togroupagentshavingsimilarbehavior[49]toelaboratestrategiestothejobslevel,jobsofjobs,machines,machinesofmachines,etc.Indeed,theproblemofcon ictsbetweenagentsisamajorconcerninMASresearch[4,30–32].TheobjectiveoftheMASistoimprovetheGanttdiagram[35,36],thereforeitleadsustoestablishthenotionofgroupcorrespondingtoelementaryentitieshavingcom-mongrindsandphysicalsameness(samecapacityofmachine,etc.)orinterdependence.