Tardiness heuristic for scheduling Flexible Manufacturing Systems (original) (raw)
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MASDScheGATS - Scheduling System for Dynamic Manufacturing Environmemts
Multiagent Systems, 2009
This chapter addresses the resolution of scheduling in manufacturing systems subject to perturbations. The planning of Manufacturing Systems involves frequently the resolution of a huge amount and variety of combinatorial optimisation problems with an important impact on the performance of manufacturing organisations. Examples of those problems are the sequencing and scheduling problems in manufacturing management, routing and transportation, layout design and timetabling problems. The classical optimisation methods are not enough for the efficient resolution of those problems or are developed for specific situations (Brucker, 2004) (Blazewicz et al., 2005) (Pinedo, 2005) (Madureira, 2003). New organizational and technological paradigms are needed to reply to the modern manufacturing systems challenges. The traditional structure of manufacturing industries is constructed upon the three pillars of land, labour and capital. The challenge is to move towards a new structure, which can be described as innovating manufacturing, founded on knowledge and capital. Future manufacturing solutions must identify multiple perspectives and linkages between novel approaches to customization, customer response, logistics and maintenance. The current typically linear approach to research, development, design, construction and assembly will be replaced by simultaneous activity in all areas to satisfying global demand and shorten time-to-market (MANUFUTURE, 2004). Multi-agent paradigm is emerging for the development of solutions to very hard distributed computational problems. This paradigm is based either on the activity of "intelligent" agents which perform complex functionalities or on the exploitation of a large number of simple agents that can produce an overall intelligent behaviour leading to the solution of alleged almost intractable problems. The multi-agent paradigm is often inspired by biological systems. Meta-Heuristics (MH) form a class of powerful and practical solution techniques for tackling complex, large-scale combinatorial problems producing efficiently high-quality solutions. From the literature we can conclude that they are adequate for static problems. However, real scheduling problems are quite dynamic, considering the arrival of new orders, orders being cancelled, machine delays or faults, etc. Scheduling problem in dynamic environments have been investigated by a number of authors, see for example (
Minimizing tardiness for job shop scheduling under uncertainties
2016 International Conference on Control, Decision and Information Technologies (CoDIT), 2016
Many disturbances can occur during the execution of a manufacturing scheduling process. To cope with this drawback, flexible solutions are proposed based on the offline and the online phase of the schedule. Groups of permutable operations is one of the most studied flexible scheduling methods bringing flexibility as well as quality to a schedule. The online phase of this method is based on a human-machine system allowing to choose in real-time one schedule from a set of schedules that fits best the real state of the system. In this paper, we propose and evaluate a new criterion called the best-case in order to be used in real-time during the online phase of the groups of permutable operations. This criterion offers an optimal or near-optimal solution from a set of solutions. The usefulness of this criterion is showed using a comparative review with two other criteria on a benchmark instances using the maximum tardiness objective.
A review for Dynamic Scheduling in Manufacturing
— This paper discusses review of literature of dynamic scheduling in manufacturing. First, the problem is defined. The scheduling problems are classified based on the nature of the shop configuration into five classes, i.e., single machine, parallel machines, flow shop, job shop, and open shop. A variety of approaches have been developed to solve the problem of dynamic scheduling. Dynamic scheduling could be classified into four categories, completely reactive scheduling, predictive-reactive scheduling, robust predictive-reactive scheduling, and robust pro-active scheduling. It is better to combine together different techniques such as operational research and artificial intelligence to overcome dynamic scheduling problems so as to endow the scheduling system with the required flexibility and robustness, and to suggest various orientations for further work is this area of research.
An analysis of heuristics in a dynamic job shop with weighted tardiness objectives
International Journal of Production Research, 1999
An analysis of heuristics in a dynamic job shop with weighted tardiness objectives E. KUTANOGLU ² and I. SABUNCUOGLU * Meeting due dates as a re¯ection of customer satisfaction is one of the scheduling criteria that is frequently encountered in today's manufacturing environments. The natural quanti® cation of this qualitative goal involves tardiness related measures. In this study, we consider the dynamic job shop scheduling problem with the weighted tardiness criterion. After we present a comprehensive literature survey on the topic, we measure the long-run performances of more than 20 single-pass dispatching rules under various experimental conditions. In this study, we pay special attention to recently proposed dispatching heuristics such as CEXSPT, CR+ SPT, S/RPT+ SPT, and Bottleneck Dynamics (BD). We also investigate the e ects of six resource pricing schemes proposed recently for BD. Moreover, we extend the earlier versions of inserted idleness and identif y the conditions in which these techniques can be applied without incurring too much computational cost. Future research directions are also outlined in light of the computational results.
Machines and AGVs Scheduling in Flexible Manufacturing System With Mean Tardiness Criterion
International Journal of Advanced Materials Manufacturing & Characterization, 2014
Optimum Automated Guided Vehicles (AGVs) operation plays a crucial role in improving the performance of Flexible Manufacturing System (FMS). One of the main elements in the implementation of AGV is task scheduling. This will enhance the productivity, Minimize delivery cost and optimally utilize the entire fleet. This enhance article Deals with Hybrid Genetic Vehicle Heuristic Algorithm (HGVHA) for simultaneous Scheduling of machines and AGVs adopting minimization of makespan and minimization of mean tardiness. The method is found to provide better solution.
Journal of Engineering, Management and Information Technology, 2024
In most of the manufacturing units job shop scheduling is a difficult task due to the complexity of the system. If the company maintains good job shop scheduling, can save time and money. And can improve the utilization of the machine. The case study was conducted in Hibert Manufacturing and Machine Building Industry (HMMBI), for five jobs and five machines Reactive job shop schedule. most of the time the company scheduling methods is depending on the first come first serve principles the existing make-span of the jobs is high around 803 minutes, due to this there is low machine utilization and dissatisfaction of customer in the company to minimizing this problem we have to look different scheduling techniques by using LEKIN scheduling software and arena simulation software to show the existing scheduling system. The results indicate heuristic methods like Shifting Bottleneck /Tmax and others can reduce the make-span from 803 minutes to 707 minutes around 96 minutes reduce and the machine utilization sum can be increased from 1.9029 to 2.1736 around 0.2707=27.1%..
A Review for Dynamic Scheduling in Manufacturing By Khalid Muhamadin
2018
This paper discusses review of literature of dynamic scheduling in manufacturing. First, the problem is defined. The scheduling problems are classified based on the nature of the shop configuration into five classes, i.e., single machine, parallel machines, flow shop, job shop, and open shop. A variety of approaches have been developed to solve the problem of dynamic scheduling. Dynamic scheduling could be classified into four categories, completely reactive scheduling, predictive-reactive scheduling, robust predictive reactive scheduling, and robust proactive scheduling. It is better to combine together different techniques such as operational research and artificial intelligence to overcome dynamic scheduling problems so as to endow the scheduling system with the required flexibility and robustness, and to suggest various orientations for further work is this area of research.
A Review on Scheduling in Flexible Manufacturin System Using Heuristics Approach
ELK ASIA PACIFIC JOURNAL OF MECHANICAL ENGINEERING RESEARCH, 2018
In recent years, Heuristics approaches involving natural computing techniques are recommended to resolve routing and sequencing combinatorial issues in versatile producing or FMS system. These techniques are applied one by one and in hybrid forms with relative success to planning issues. This work tries to review the achievement of heuristic approach applied in planning issues.
Applied Computer Systems
A problem of minimizing the total weighted tardiness in the preemptive single machine scheduling for discrete manufacturing is considered. A hyper-heuristic is presented, which is composed of 24 various heuristics, to find an approximately optimal schedule whenever finding the exact solution is practically intractable. The three heuristics are based on the well-known rules, whereas the 21 heuristics are introduced first. Therefore, the hyper-heuristic selects the best heuristic schedule among 24 schedule versions, whose total weighted tardiness is minimal. Each of the 24 heuristics can solely produce a schedule which is the best one for a given scheduling problem. Despite the percentage of zero gap instances decreases as the greater number of jobs is scheduled, the average and maximal gaps decrease as well. In particular, the percentage is not less than 80 % when up to 10 jobs are scheduled. The average gap calculated over nonzero gaps does not exceed 4 % in the case of scheduling 7...
Minimizing Total Tardiness: A Case Study in an Autoparts Factory
International Transactions in Operational Research, 2002
The application of heuristic procedures for solving a real scheduling problem that arises in an autoparts factory is reported in this paper. Due to the characteristics of the environment, the measure of performance considered is the minimization of the total tardiness of the jobs. The original problem is reduced to the single machine scheduling problem, and the dispatching rules EDD (earliest due date), SPT (shortest processing time), and the PSK algorithm are used to obtain approximate solutions. Computational tests and a comparison with the usual schedule are presented.