We consider a variety of preemptive scheduling problems with controllable processing times on a single machine and on identical/uniform parallel machines, where the objective is to minimize the total compression cost. In this paper, we propose fast divide-and-conquer algorithms for these scheduling problems. Our approach is based on the observation that each scheduling problem we discuss can be...

This paper addresses a practical scheduling problem arising in the packaging department of a pharmaceutical industrial plant. The problem is modeled as a parallel machine scheduling problem with setups, release and due dates and additional constraints related to the scarce availability of tools and human operators. The objective functions are minimization of makespan and maximum tardiness in le...

In this paper, we provide a new class of randomized approximation algorithms for parallel machine scheduling problems. The most general model we consider is scheduling unrelated machines with release dates (or even network scheduling) so as to minimize the average weighted completion time. We introduce an LP relaxation in time-indexed variables for this problem. The crucial idea to derive appro...

Scheduling of multiple parallel machines in the face of sequence dependent setups and downstream considerations is a hard problem. No single efficient algorithm is guaranteed to produce optimal results. We describe a solution for an instance of this problem, in the domain of paper manufacturing. The problem has additional job machine restrictions and fixed costs of assigning jobs to machines. W...

Job scheduling is concerned with the optimal allocation of scare resources with objective of optimising one or several criteria. Job scheduling has been a fruitful area of research for many decades in which scheduling resolve both allocation of machines and order of processing. If the jobs are scheduled properly, not only the time is saved but also efficiency of system is increased. The paralle...

Abstract. This paper is devoted to Resource Constrained Scheduling. An instance for this problem is given by a set of n jobs with lengths and weights and a set of m machines with capacities. At every time each machine can run arbitrary many jobs in parallel but the total weight of these jobs must not exceed the capacity of the machine. Furthermore the m machines work in parallel and we wish to ...

In this paper we propose a tabu search implementation to solve the unrelated parallel machines scheduling problem with sequenceand machinedependent setup times to minimize the schedule’s makespan. The problem is NP-hard and finding an optimal solution efficiently is unlikely. Therefore, heuristic techniques are more appropriate to find near-optimal solutions. The proposed tabu search algorithm...

Evolutionary programming is a kind of evolutionary computing method based on stochastic search suitable for solving system optimization. In this paper, evolutionary programming method is applied to the identical parallel machine production line scheduling problem of minimizing the number of tardy jobs, which is a very important optimization problem in the field of research on CIMS and industria...