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.

In this paper we study the resource-constrained project scheduling problem with weighted earliness-tardiness penalty costs. Project activities are assumed to have a known deterministic due date, a unit earliness as well as a unit tardiness penalty cost and constant renewable resource requirements. The objective is to schedule the activities in order to minimize the total weighted earliness-tard...

This paper considers the problem of scheduling a given number of jobs on a single machine to minimize total earliness and tardiness when family setup times exist. The paper proposes optimal branch-and-bound algorithms for both the group technology assumption and if the group technology assumption is removed. A heuristic algorithm is proposed to solve larger problems with the group technology as...

We study the earliness-tardiness scheduling problem on a single machine with due date assignment and controllable processing times. We analyze the problem with three different due date assignment methods and two different processing time functions. For each combination of these, we provide a polynomialtime algorithm to find the optimal job sequence, due date values and resource allocation minim...

In many manufacturing systems, jobs that are completed early are held as finished-goods inventory until their due-dates, and hence we incur earliness costs. Similarly, jobs that are completed after their due-dates incur penalty. The objective in such situations would, therefore, be to meet the due-dates of the respective jobs as closely as possible, and consequently minimize the sum of earlines...

We use the Akers-Friedman geometric approach to solve the two jobs job-shop problem when there is an earliness cost on the first operation and a tardiness cost on the last operation of each job. We then generalize the problem by imposing earliness and tardiness costs on each operation and finally, we solve it using a dynamic programming algorithm. KeywordsEarliness-tardiness scheduling, Polyn...

This paper focuses on a stochastic scheduling problem in which n immediately available jobs are to be scheduled jointly with the preventive maintenance in a single machine subject to breakdowns. The objective is to minimize expected total earliness and tardiness costs with a common due-date. The problem of scheduling only n jobs to minimize total earliness and tardiness costs in a single machin...

A novel algorithm for one machine scheduling to minimize total weighted earliness and tardiness using particle swarm optimization is proposed. Existing techniques face challenges such as job size limitations increase in computational time and inaccurate solutions. To overcome these challenges the proposed work implements Meta-Heuristic based particle swarm optimization to optimize the total wei...

Scheduling problems involving both earliness and tardiness costs became more important in recent years. This kind of problems include both earliness and tardiness penalties and tries to reduce them. In this study a case study from real world is investigated. Since the machine is bottle neck in the production line and all jobs have a common restrictive due date and different earliness and tardin...

The objective of this paper is to propose a scheduling problem for multiple automated guided vehicles (AGVs) in a manufacturing system. Considering the due date of AGVs requiring for material handling among shops in a job shop layout, their earliness and tardiness are significant in satisfying the expected cycle time and from an economic view point. Earliness results in AGVs waiting and tardine...