In this study, we consider the production environment of no-wait reentrant flow shop with the objective of minimizing makespan of the jobs. In a reentrant flow shop, at least one job should visit at least one of the machines more than once. In a no-wait flowshop scheduling problem, when the process of a specific job begins on the first machine, it should constantly be processed without waiting ...

Dynamic job shop scheduling (DJSS) problems are combinatorial optimisation problems that have been extensively studied in the literature due to their difficulty and their applicability to real-world manufacturing systems, e.g., car manufacturing systems. In a DJSS problem instance, jobs arrive on the shop floor to be processed on specific sequences of machines on the shop floor and unforeseen e...

In this article, we consider the minimization of the total tardiness in a flexible job-shop. In our knowledge, this criterion is not previously studied for this type of shop configuration. The total tardiness criterion was mainly considered in the single machine problem (Chu [Chu92] and Souissi et al. [SKC04]). Few references studied this criterion in a job-shop configuration. The priority rule...

A frequently occurring operational problem is one of processing a given number of jobs (commodities) on a specified number of machines (facilities) referred to by various investigators as scheduling, dispatching, sequencing, or combinations thereof (Gupta and Stafford, 2006). In most manufacturing environments, a set of processes is needed to be serially performed in several stages before a job...

Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Appropriate scheduling not only reduces manufacturing costs but also reduces possibilities for violating due dates. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple f...

In this paper, we analyze the characteristics of the dynamic job shop scheduling problem when machine breakdown and new job arrivals occur. A hybrid approach involving neural networks(NNs) and geneticalgorithm(GA) is presented to solve the dynamic job shop scheduling problem as a static scheduling problem. The objective of this kind of job shop scheduling problem is minimizing the completion ti...

In the classical job shop scheduling problem (JSSP), n jobs are processed to completion on m unrelated machines. Each job requires processing on each machine exactly once. For each job, technology constraints specify a complete, distinct routing which is fixed and known in advance. Processing times are sequence-independent, fixed, and known in advance. Each machine is continuously available fro...

This paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. In the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). However,, two significant criteria for each schedule in stochastic models are: expectable m...

This paper focuses on a hub reentrant shop scheduling problem which is motivated by actual packing production line in the iron and steel industry. There are five operations for processing a job where three operations must be processed on a hub machine, and between any two consecutive operations on the hub machine, two operations must be processed on other two secondary machines, respectively. W...

The just-in-time production philosophy has led to a growing interest in scheduling problems considering both earliness and tardiness penalties. Most publications considering these so-called non-regular objective functions are devoted to single machine problems. In the case of multi-machine problems, there are some papers dealing with parallel machine problems. However, for multi-operation sched...