The production planning problem is common to many production systems, and typically implies assigning the required tasks to the available resources. Given its combinatorial nature, the planning problem which consists in determining the number of products to be produced in a set of parallel machines is often very difficult to solve optimally; this is especially true when additional factors such as setup times must be considered.Determination of a production planning for theallocation oflimited resources induring the time forgroup of activities, aso ne ofthe key success factorsinany manufacturing organizationofgoodsandserviceshas importantandeffective role. Due to done researchextensive, modelusedinthe any production planningproblembased onthe objectivesandcharacteristicsof eachmanufacturing system is different.One of basic assumption in more studies on the problems of lot sizing and production scheduling is adherence to thefactoryobligationstosatisfy all demands of customers, while due tocapacity constraintsit maynot bepossible. One of approach to achieve this important topic is, considering overtimeand sub contracts that both methods typically are done at a cost higher than production cost. In this thesis, withconsideringsetup costs, product variety, batchproductionon the setofnon-identical parallelmachinesandthere are alsomanufacturingperiods for implement manufacturingprocessto satisfydemandineachperiod withconsidering warehousingcosts, effort has been done toclosermodelto the realsituation.The problem at hand basically consists in determining the number of units of each product to be manufactured in a set of parallel machines, and incorporates both intra- and inter-family setup times.As such, it is a problem of production planning and scheduling for a system of machines in parallel.Alsodue toreduce production costs,grouptechnologyassumptions and consideringpossibility of preparation transferencebetweenperiodsaddedto the modelforbatchesof manufacturing and the other hand with consideringovertimeandsubcontractsissatisfied possibility ofachieve the goal to supplythe demandineachperioddespite productioncapacity constraints.Otherimportantconstraints areinclude thecapacity of themachinery, accessibletoworkersduringovertime, boundaries of theproduction rate andsubcontractsineach period. In addition tothe construction ofa mixedintegermathematicalprogramming modelbased onassumptionexisting andprovideexactmethod forsolving it, twodifferentand efficientmetaheuristic methodsis presentedforsolvinglargescale, whichin comparisonwiththe exactsolution have solutionsthe appropriate In terms ofqualityand solvingtime. The first method is based ongenetic algorithmandsecond based onsimulatedannealingmethod. In the endboth methodscompared withthe exactsolutionobtained fromtheGAMSsoftwareandthe resultsshow thatboth methods are appropriatein terms ofqualityandsolvingtime.
