This article deals with a quite complex machine scheduling problem comprising the following features: 1. unrelated parallel machines; 2. jobs have different due dates; 3. job splitting is allowed; 4. setup times are sequence dependent; 5. the objective function is to minimize the weighted sum of early, tardy and setup costs. The problem is formulated as a mixed-integer programming model which i...

In this work the authors addresses the problem of sequencing a set of jobs on a single machine using a genetic algorithm and simulation. The goal is to find the schedule that minimizes the total earliness and tardiness penalties of all jobs, under the assumptions that no pre-emption of jobs is allowed and all jobs are available at time zero. In order to accelerate the search process, the Author...

Scarce resources such as material, labor, and equipment are to be optimized to improve the performance and lower production costs in flexible assembly lines. These resources are usually allocated optimally through the generation of schedules. In this paper, variants of a differential evolution-based algorithm are employed to schedule flexible assembly lines (FAL). The performance of the assembl...

In this paper we address a multi-objective scheduling problem for unrelated parallel machines. In unrelated parallel systems, the processing cost/time of a given job on different machines may vary. The objective of scheduling is to simultaneously determine the job-machine assignment and job sequencing on each machine. In such a way the total cost of the schedule is minimized. The cost function ...

We study the Job-Shop Scheduling problem with Earliness and Tardiness penalties. We describe two Lagrangian relaxations of the problem. The first one is based on the relaxation of precedence constraints while the second one is based on the relaxation of machine constraints. We introduce dedicated algorithms to solve the corresponding dual problems. The second one is solved by a simple dynamic p...

We study the Job-Shop Scheduling problem with Earliness and Tardiness penalties. We describe two Lagrangean relaxations of the problem. The ̄rst one is based on the relaxation of precedence constraints while the second one is based on the relaxation of machine constraints. We introduce dedicated algorithms to solve the corresponding dual problems. The second one is solved by a simple dynamic pr...

This paper addresses a complex real life manufacturing problem that occurs in paper and wood industries: the online bin packing and cutting of small items using parallel machines in a just-in-time environment. The objective is to minimize both the unused areas of the bins and the sum of weighted earliness and tardiness penalties. This NP hard problem is herein solved using an agent-based approa...

This paper investigates the single-machine due-window assignment scheduling with truncated learning effects and past-sequence-dependent setup times simultaneously. The scheduler has option of job-rejection, i.e., some jobs are processed other rejected. Under three (i.e., common, slack different) methods, our goal is to minimize sum a general earliness-tardiness cost weighted earliness-tardiness...

her early schooling and unviersity preparatory studies in Qaemshahr. She then enrolled into Iran University of Science and Technology in Tehran after a highly selective admission procedure. In 2005, she finished her undergraduation studies in Mathematics with specialisation in topics of Applied Mathematics. After a brief 3-month training period spent working on updating flight managemeny system...

We consider the problem of scheduling a number of jobs on a single machine against a restrictive common due date. The paper consists of two parts: firstly a new and appropriate problem representation is developed. As the restrictive common due date problem is known to be intractable we decided, secondly, to apply meta-heuristics, namely evolutionary strategies, simulated annealing and threshold...