We consider the problem of scheduling of n jobs to minimize the total earliness and tardiness penalty. The scheduling objective is to minimize the sum of job dependent earliness and tardiness penalties.. After determining the scheduling for single machine common due date, using neural network, the result shows that the neural network solution performs very well.

This paper considers the problem of minimizing the mean tardiness of N jobs when the jobs are scheduled on a single machine. A simple algorithmic procedure is develop to obtain an optimal or a near optimal sequence for the N jobs while considering an equal penalty cost incurred to each job delivered later than its due date. The developed algorithm is applied to the several test problems. The re...

This paper investigates common (slack) due-date assignment single-machine scheduling with controllable processing times within a group technology environment. Under linear and convex resource allocation functions, the cost function minimizes (including weighted sum of earliness, tardiness, assignment, where weights are position-dependent) resource-allocation costs. Given some optimal properties...

This research studies the problem of batching orders in a dynamic, finite-horizon environment to minimize order tardiness and overtime costs of the pickers. The problem introduces the following trade-off: at every period, the picker has to decide whether to go on a tour and pick the accumulated orders, or to wait for more orders to arrive. By waiting, the picker risks higher tardiness of existi...

For the purpose of solving the flexible job-shop scheduling problem (FJSP), an improved quantum genetic algorithm based on earliness/tardiness penalty coefficient is proposed in this paper. For minimizing the completion time and the job-shop cost, a simulation model was established firstly. Next, according to the characteristics of the due in production, a double penalty coefficient was designe...

The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for multi-objective optimization of a dynamic multi pickup and delivery problem with time windows (Dynamic m-PDPTW). We propose a brief literature review of the PDPTW, pre...

This paper addresses a one-machine scheduling problem in which the efficiency of the machine is not constant, that is the duration of a task is longer in badly efficient time periods. Each task has an irregular completion cost. Under the assumption that the efficiency constraints are time-periodic, we show that the special case where the sequence is fixed can be solved in polynomial time. The g...

We consider a common due-window assignment scheduling problem jobs with variable job processing times on a single machine, where the processing time of a job is a function of its position in a sequence (i.e., learning effect) or its starting time (i.e., deteriorating effect). The problem is to determine the optimal due-windows, and the processing sequence simultaneously to minimize a cost funct...

In the previous chapter, we have made an analytical study regarding the completion time and the due time of each job, in order to find out the satisfaction level of demand maker in a flow shop scheduling. But this chapter differs in the study that here each job has to process on equi potential parallel machines at first stage and then on other succeeding machines in a specified order. Some addi...