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...

We consider the unrelated parallel machines scheduling problem where jobs have earliness and tardiness penalties and a common due date. We formulate this problem and some of its variants as 0-1 programs with quadratic objective function subject to linear constraints. The main contribution of this paper is to use and develop different convex reformulations to solve exactly the quadratic programs...

Maintenance is important to manufacturing process with a view to sustaining production efficiency. In this study scheduling of unrelated parallel machines with effects of learning and aging and multi maintenance activities is considered. The objective is to find the optimal maintenance periods, optimal maintenance frequencies and optimal job sequences such that the makespan of all jobs are mini...

In this paper, we provide a new class of randomized approximation algorithms for scheduling problems by directly interpreting solutions to so-called time-indexed LPs as probabilities. The most general model we consider is scheduling unrelated parallel machines with release dates (or even network scheduling) so as to minimize the average weighted completion time. The crucial idea for these multi...

Here, we consider approximation algorithms for the Graph Balancing problem which is a special case of the job scheduling on unrelated parallel machines to minimize the makespan. We present an interpretation of the 2approximation LP-rounding algorithm given by Lenstra et al. to the special case of graph balancing. We then show how the approximation guarantee can be improved by the technique of a...

The paper suggests a stochastic approximate solution to scheduling problems with unrelated parallel machines. The presented method is based on neurodynamic programming (reinforcement learning and feed-forward artificial neural networks). For various scheduling environments (static-dynamic, deterministicstochastic) different variants of episodic Q-learning rules are proposed. A way to improve th...

This study deals with an unrelated parallel machine scheduling problem additional resources (UPMR). That is one of the important sub-problems in scheduling. UPMR consists a set jobs on machines. In addition to that, number or more are needed. very and its importance comes from wealth applications; they applicable engineering scientific situations manufacturing systems such as industrial robots,...

appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. one type of scheduling problems is just-in-time (jit) scheduling and in this area, motivated by jit manufacturing, this study investigates a mathematical model for...