This paper addresses the application of AI techniques in a practical OR problem , i.e. scheduling. Scheduling is a scientific domain concerning the allocation of tasks to a limited set of resources over time. The goal of scheduling is to maximize (or minimize) different optimization criteria such as the makespan (i.e. the completion time of the last operation in the schedule), the occupation ra...

The objective of this paper is to study a selected set of scheduling criteria commonly used in scheduling research and develop a set of simple rules that can be easily implemented in relatively small dynamic job-shops. Simulation models were developed for two dynamic production shop environments, namely, a job-shop with jumbled flow and a job-shop with limited jumbled flow. Five scheduling crit...

This article overviews a recent PhD dissertation representing the first effort at many-objective optimization in job shop scheduling (JSS). The thesis develops genetic programming hyperheuristic (GP-HH) approaches to evolve effective dispatching rules for many conflicting objectives JSS problems. aim is develop GP-HH methods that alleviate issues related problems and new capable of enhancing sh...

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...

This paper deals with multi-operation models, which are different from the flow shop and job shop models. In the flow shop or job shop models, the routes of all jobs are known in advance. In practice, the route of the job is often immaterial and up to the scheduler to decide. When the routes of the jobs are open, the model is referred to as an open shop. This paper describes the development of ...

this paper presents a new mathematical model for a bi-objective job shop scheduling problem with sequence-dependent setup times that minimizes the weighted mean completion time and the weighted mean tardiness time. for solving this multi-objective model, we develop a fuzzy multi-objective linear programming (fmolp) model. in this problem, a proposed fmolp method is applied with respect to the o...

We consider a general class of multiprocessor shop scheduling problems, preemptive or nonpreemptive, with precedence constraints between operations, with job or operation release dates, and with a class of objective functions including weighted sums of job, operations and stage completion times. We present a general approximation method combining a linear programming relaxation in the operation...

A model combining Discrete Event System (DES) and Multi-Agent System (MAS) is proposed to simulate a real-time job shop so that it can work as a test bed to systematically study the performance of control rules and algorithms in dynamic job shop scheduling. A definition of a generic job shop is given considering dynamic events, shop floor layout and the Material Handling System (MHS). It is fir...

We use the Akers-Friedman geometric approach to solve the two jobs job-shop problem when there is an earliness cost on the first operation and a tardiness cost on the last operation of each job. We then generalize the problem by imposing earliness and tardiness costs on each operation and finally, we solve it using a dynamic programming algorithm. KeywordsEarliness-tardiness scheduling, Polyn...