This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i.e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduli...

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...

Scheduling for job shop is very important in both fields of production management and combinatorial op-timization. However, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. The combination of several optimization criteria induces additional complexity and new problems. In this paper, we pro...

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 algorithm for the job s...

This study aims to investigate characteristics of job-shop scheduling methods for micro-enterprise. Many scheduling methods have been proposed and evaluated. However, most of evaluations are not focused on application for micro-enterprise. In order to figure out an appropriate scheduling method for micro-enterprise, job-shop scheduling methods are evaluated from the view of applicability for mi...

The indeterministic multi-layer job-shop scheduling problem, which is the extension of the traditional job-shop scheduling, is introduced in this paper. The framework and some key issues of the problem are discussed. A multi-agent reinforcement learning approach, named memory-evolution-based MAS reinforcement learning algorithm, is breifly introduced too. Experiment results show that our approa...

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...

The purpose of this study is to develop an effective scheduling methodology for a realistic flow shop sequencing problem. The flow shop consists of two machines where only the first machine has separable, external, and sequence dependent setup times. The length of setup times required for a job depends not on the immediately preceding job but on the job which is two steps prior to it. The probl...

The subject of this paper is a flow-shop based on a case study aimed at the optimisation of ordering production jobs in mechanical engineering, in order to minimize the overall processing time, the makespan. The production jobs are processed by machines, and each job is assigned to a certain machine for technological reasons. Before processing a job, the machine has to be adjusted; there is onl...