The n×m minimum-makespan general job-shop scheduling problem, hereafter referred to as the JSSP, can be described by a set of n jobs {Ji}1≤j≤n which is to be processed on a set of m machines {Mr}1≤r≤m. Each job has a technological sequence of machines to be processed. The processing of job Jj on machine Mr is called the operation Ojr. Operation Ojr requires the exclusive use of Mr for an uninte...

The job shop problem is an important part of scheduling in the manufacturing industry. A new intelligent algorithm named Shuffled Complex Evolution (SCE) algorithm is proposed in this paper with the aim of getting the minimized makespan. The sequence mapping mechanism is used to change the variables in the continuous domain to discrete variables in the combinational optimization problem; the se...

Smaller production companies, such as job shops, are often incapable of committing significant human or capital resources for the improvement of manufacturing flow times. However, there is considerable demand in these organizations for solutions that offer improvements without the risk involved in expending these resources. This paper investigates the impact of scheduling rules and reorganizati...

We study an inverse counterpart of the two machine flow-shop scheduling problem that arises in the context of inverse optimization. While in the forward scheduling problem all parameters are given and the objective is to find job sequence(s) for which the value of the makespan is minimum, in the inverse scheduling the exact values of processing times are unknown and they should be selected with...

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...

We present a comprehensive complexity analysis of classical shop scheduling problems subject to various combinations of constraints imposed on the processing times of operations, the maximum number of operations per job, the upper bound on schedule length, and the problem type (taking values “open shop”, “job shop”, “mixed shop”). It is shown that in the infinite class of such problems there ex...

We survey solution methods for the job shop scheduling problem with an emphasis on local search. Both deterministic and randomized local search methods as well as the proposed neighborhoods are discussed. We compare the computational performance of the various methods in terms of their eeectiveness and eeciency on a standard set of problem instances. In the job shop scheduling problem we are gi...

A train scheduling problem in a single-track railway can be modeled as a job-shop scheduling problem. We use a mixed graph model for such a job-shop problem with appropriate criteria. There are several performance evaluations for a train schedule. Optimizing a train schedule subtends minimizing total tardiness of the trains, minimizing the sum of train transit times, minimizing the makespan for...

In most real production environment, schedules are usually inevitable with the presence of a variety of unexpected disruptions. Thus it is necessary to develop predictive/reactive schedules which can absorb disruptions while maintaining high shop performance. In this paper, a robust predictive/reactive scheduling method is developed for solving job shop scheduling in dynamic environment. It con...