In classical scheduling problems, the processing time of a job assumed to be constant. This consumption is true in some cases but because machines and tools depreciate and their efficiency reduce during time, this consumption cannot be true in all cases. This assumption in many manufacturing environment is not correct and in practice, we encounter the environments in which the various factors impress on the processing time and cause an increase or decrease in times. So, in many situation a job processed later consumes more time that the same job processed earlier. This phenomenon is called deterioration. For example,Williams and Gupta and Gupta pointed outthat the ingot batches must be preheated to the requiredtemperature in soaking pits before they can be hot-rolledby a blooming mill in steel production. Kunnathur andGupta gave a fire fighting example where the timeand effort to cease a fire increase if there is a delay instarting the fire fighting. In deteriorating job scheduling problems, most of the researchers assume that the actual job processing time is a function of its starting time. Machine scheduling problems with deteriorating jobs have been paid more attention in recent years. In the current manufacturing environment, gaining production efficiency is important while ensuring that customer orders are delivered as close to their due date as possible. Often, grouping of jobs that tend to be similar in some way, such as the required tooling in a family is desirable. As a result of such a similarity, a job does not need a setup when following another job from the same family, but a known family setup time is required when a job follows a member of some other family. Also, the concept of group technology with different grouping parts and products and with the same manufacturing and design, cause increasing in efficiency and productivity. However, job deterioration is relative unexplored in the context of group technology. In many various criterion scheduling problems, the objective function of sum of tardiness is very useful in application and industrial environment. This is due to the corresponding objective function with cost of offseting the tardiness in production and assembly lines and in most cases is equvalent to the cost of losing costomers.actually In a just-in-time environment, each job should be completed as close as possible to its due date. Missing a job’s duedate may result in the loss of the customer or the need tocompensate for the delay along the production or assembly line. A single machine scheduling problem is studied. There is a partiton of the set of n jobs into m groups on the basis of group technology with piece wise deterioration consideration.A common technique for solving large NP-hard combinatorial optimization problems is Branch and Bound (B am) algorithm.This study contain single machine scheduling problem with deteriorated jobs and group technology suppostion to minimize sum of tardiness in which job’s processing times is a non-decreasing function based on the job starting time.this problem is Np-hard.A branch and bound algorithm incorporating with three properties, a lower bound and an upper bound is developed to derive the optimal solution. Computational results for 1920 problems show that problems with 25 jobs can be solved in all series .Therefor, the large size problems with using combination of genetic algorithm and electromagnetic method are solved and the answers given is compared with genetic algorithm in terms of solution quality and time of solution.
