In this paper we compare simulated annealing and tabu search approaches to a single machine common due date assignment and scheduling problem with jobs available at different times. The objective is to minimize the total weighted sum of earliness, tardiness and due date costs.

The paper presents the methodology of parallel algorithm designing based on the memetic approach (Lamarck and Baldwin evolution theory) making use of specific properties of the problem and distributed island model. This approach is presented on the example of the single machine scheduling problem with earliness/tardiness

Due-dates are often determined during sales negotiations between customers and the sales team of the firm. In the preliminary (pre-sale) stage, the customer provides a time interval (due-window) of his preferred due-dates. This interval reflects acceptable leadtimes, which are functions of the customer resource constraints (e.g. storage or personnel limitations). If the due-dates are assigned e...

This paper describes a genetic algorithm approach to the dynamic job shop scheduling problem with jobs arriving continually. Both deterministic and stochastic models of the dynamic problem were investigated. The objective functions examined were weighted flow time, maximum tardiness, weighted tardiness, weighted lateness, weighted number of tardy jobs, and weighted earliness plus weighted tardi...

extensive research has been devoted to resource constrained project scheduling problem. however, little attention has been paid to problems where a certain time penalty must be incurred if activity preemption is allowed. in this paper, we consider the project scheduling problem of minimizing the total cost subject to resource constraints, earliness-tardiness penalties and preemption penalties, ...

Single machine, distinct due dates, early/lately machine problem and fuzzy environment closely models the situation faced by ‘Just In Time’ manufacturing. The objective of this paper is to sequence the jobs on the machine, so that the total penalty cost be minimum. This cost is composed of the total earliness and the total tardiness cost. An algorithm is developed here to minimize the total pen...

A fully polynomial time approximation scheme (FPTAS) with run time O( n m εm−1 ) is developed for a problem which combines common due window assignment and scheduling n jobs on m identical parallel machines. The problem criterion is bottleneck (min-max) such that the maximum cost, which includes job earliness, job tardiness and due window size costs, is minimized.

This paper addresses the one-machine scheduling problem with earliness-tardiness penalties. We propose a new branch-and-bound algorithm that can solve instances with up to 50 jobs and that can solve problems with even more general non-convex cost functions. The algorithm is based on the combination of a Lagrangean relaxation of resource constraints and new dominance rules.

We consider a single machine earliness/tardiness scheduling problem with general weights, ready times and due dates. Using completion time information obtained from the optimal solution to a preemptive relaxation, we generate feasible solutions to the original non-preemptive problem. We report extensive computational results demonstrating the speed and effectiveness of this approach.