Job shop scheduling (JSS) is a problem which involves an assignment of a set of tasks to the machines in a predefined sequence in order to optimize one or more objectives considering job performance measures of the system. It’s a multi-objective, multi-criteria optimization problem. A job shop environment consists of ‘n’ jobs. Each job has a given machine routine in which some machines could be...

The problem of finding good solutions to scheduling problems is very important to real manufacturing systems, since the production rate and production costs are very dependent on the schedules used for controlling the work in the system. Most research in scheduling focuses on optimisation of static problems, where all problem data are known before scheduling starts. However many real world opti...

Job-shop manufacturing environment requires planning of schedules for the systems of low-volume having numerous variations. For a job-shop scheduling, ‘k’ number of operations and ‘n’ number of jobs on ‘m’ number of machines processed through an assured objective function to be minimized (makespan). This paper presents a capable genetic algorithm for the job-shop scheduling problems among opera...

The flexibility present in a job shop is an important determinant of the future success of the shop, since it increases the ability to deal with the changes a job shop is faced with in a dynamic environment. The presence of idle-time in a job shop schedule contributes considerably to this flexibility. By introducing an anticipation factor that preserves idletime in the scheduling process more f...

The various industries such as automobile industry, aerospace industry, printing industry, and chemical industry operate on job shop system. Job shop scheduling problems are complex and real world. The present work assesses the effect of change in shop utilizations levels on total setups and mean setup time measures. The simulation model of the job shop is developed for investigation purpose. T...

Job shop scheduling problem is one of the most important problems in the combinatorial optimization problems, and it is applied to various fields about engineering. Many works have been reported for this problem using Genetic Algorithm (GA). The GA is one of the most powerful optimization methods based on the mechanics of natural evolution. In this paper, we propose a new genetic coding for the...

Two scheduling methods based on Extreme Value Theory (SEVAT) and Genetic Algorithms (GA) are developed. The SEVAT approach is a schedule building approach that creates a statistical profile of schedules through random sampling and predicts the potential' of a schedule alternative. The GA approach, on the other hand, is a schedule permutation approach, in which a population of schedules are init...

This paper presents a state of the art overview on Ants Systems. Initially the work proposes the fundamental concepts of Ants Theory and offers a description of the main algorithms (based on Ants Theory) and the respective fields of application. Among different fields of application, the paper focuses on industrial plants scheduling problems in open shop, flow shop and job shop systems. The las...

We consider the problem of scheduling jobs in a hybrid job shop We use the term hybrid to indicate that we consider a lot of extensions of the classic job shop such as transportation times multiple resources and setup times The Shifting Bottleneck procedure can be generalized to deal with those extensions We test this approach for an assembly shop In this shop we study the in uence of static an...

 Inventory plays a major role in deciding the overall manufacturing costs, and a good scheduling system should balance the on-time delivery of products versus low work-in-process (WIP) inventory. In this paper, the “CONstant Work-In-Process” (CONWIP) concept is applied to job shop scheduling to effectively control WIP inventory. A new mathematical formulation of CONWIP-based job shop schedulin...