scholarly journals A COMPARATIVE STUDY OF THE USABILITY OF DIFFERENT PRODUCTION SCHEDULING ALGORITHMS AND RULES

2021 ◽  
Vol 2 ◽  
pp. 41-46
Author(s):  
Pavol Jurík
Keyword(s):  
Production Process ◽  
Production Scheduling ◽  
Job Shop ◽  
Flow Shop ◽  
Production Systems ◽  
Scheduling Problems ◽  
History Of ◽  
Service Object ◽  
The Right ◽  
Production Plans

Production scheduling optimization is a very important part of a production process. There are production systems with one service object and systems with multiple service objects. When using several service objects, there are systems with service objects arranged in a parallel or in a serial manner. We also distinguish between systems such as flow shop, job shop, open shop and mixed shop. Throughout the history of production planning, a number of algorithms and rules have been developed to calculate optimal production plans. These algorithms and rules differ from each other in the possibilities and conditions of their application. Since there are too many possible algorithms and rules it is not easy to select the proper algorithm or rule for solving a specific scheduling problem. In this article we analyzed the usability of 33 different algorithms and rules in total. Each algorithm or rule is suitable for a specific type of problem. The result of our analysis is a set of comparison tables that can serve as a basis for making the right decision in the production process decision-making process in order to select the proper algorithm or rule for solving a specific problem. We believe that these tables can be used for a quick and easy selection of the proper algorithm or rule for solving some of the typical production scheduling problems.

scholarly journals ANALISA PERBANDINGAN PENJADWALAN PRODUKSI DENGAN METODE CDS (CAMPBELL DUDEK SMITH), EDD (EARLIEST DUE DATE) DAN FCFS (FIRST COME FIRST SERVE) PADA PT. SARI WARNA ASLI UNIT V

2021 ◽  
Vol 1 (2) ◽  
pp. 46-51
Author(s):  
Dwi Ayu Lestari, Vikha Indira Asri
Keyword(s):  
Production Process ◽  
Production System ◽  
Production Scheduling ◽  
Job Shop ◽  
Allocation Of Resources ◽  
Due Date ◽  
Scheduling System ◽  
Make To Order ◽  
First Come First Serve ◽  
Scheduling Method

Scheduling is defined as the process of sequencing the manufacture of a product as a whole on several machines. All industries need proper scheduling to manage the allocation of resources so that the production system can run quickly and precisely as of it can produce optimal product. PT. Sari Warna Asli Unit V is one of the companies that implements a make to order production system with the FCFS system. Thus, scheduling the production process at this company is also known as job shop production scheduling. The methods used in this research are the CDS method, the EDD method and the FCFS method. The purpose of this research is to minimize the production time and determine the best method that can be applied to the company. The results of this research showed that the makespan obtained in the company's scheduling system with FCFS rules was 458 minutes, and the results of scheduling using the CDS method obtained a makespan value of 329 minutes, then the best production scheduling method that had the smallest makespan value was the CDS method.

scholarly journals PENJADWALAN MESIN DENGAN MENGGUNAKAN ALGORITMA JADWAL NON-DELAY DI PT. SNN SEKSI WORKSHOP

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Inna Kholidasari ◽  
Keyword(s):  
Production Process ◽  
Production Scheduling ◽  
Completion Time ◽  
Job Shop ◽  
Machine Scheduling ◽  
Spare Parts ◽  
First In First Out ◽  
A Company

Production scheduling is the most important part in carrying out the production process that will be carried out on a production floor. Scheduling activities are carried out before the production process begins to ensure the smooth running of the production process. If the production scheduling is not done properly, there will be obstacles in the production process and will cause losses to the company. This study aims to determine the production machine scheduling in a company engaged in the manufacture of spare parts for automotive products. This company implements a job shop production process and uses the First In First Out method in completing its work. Due to the large number of products that have to be produced, there are often two or more products that must be worked on at the same time and machine. This condition causes some products to have to wait for the associated machine to finish operating and causes long product turnaround times. This problem is solved by making a production machine scheduling using the Non-Delay method. By applying this method, the makespan of completion time can be minimized.

Modified Migrating Birds Optimization for Solving the Low-carbon Scheduling Problem

2020 ◽  
Vol 12 (4) ◽  
pp. 63-75
Author(s):  
Zhifeng Zhang ◽  
Yusheng Sun ◽  
Yadong Cui ◽  
Haodong Zhu
Keyword(s):  
Production Scheduling ◽  
Job Shop ◽  
Optimal Solution ◽  
Scheduling Problem ◽  
Low Carbon ◽  
Scheduling Problems ◽  
Solution Quality ◽  
Migrating Birds Optimization ◽  
Initialization Scheme ◽  
Migrating Birds

Production scheduling problems have historically emphasized cycle time without involving the environmental factors. In the study, a low-carbon scheduling problem in a flexible job shop is considered to minimize the energy consumption, which mainly consists of two parts: the useful part and the wasted part. First, a mathematical model is built based on the features of the workshop. Second, a modified migrating bird's optimization (MMBO) is developed to obtain the optimal solution. In the MMBO, a population initialization scheme is designed to enhance the solution quality and convergence speed. Five types of neighborhood structures are introduced to create neighborhood solutions. Furthermore, a local search method and a reset mechanism are developed to improve the computational results. Finally, experimental results validate that the MMBO is effective and feasible.

scholarly journals Pengembangan Algoritma Non Delay Pada Kasus Penjadwalan Non-Permutation Hybrid Flowshop Untuk Minimasi Mean Flowtime

2018 ◽  
Vol 19 (2) ◽  
pp. 148
Author(s):  
Siti Muhimatul Khoiroh
Keyword(s):  
Production Scheduling ◽  
Manufacturing Industry ◽  
Success Factors ◽  
Flow Shop ◽  
Flow Time ◽  
Hybrid Flow Shop ◽  
Scheduling Problems ◽  
Mean Flow ◽  
Mean Flow Time ◽  
Permutation Flow Shop

Production scheduling is one of the key success factors in the production process. Scheduling approach with Non-Permutation flow shop is a generalization of the traditional scheduling problems Permutation flow shop for the manufacturing industry to allow changing the job on different machines with the flexibility of combinations. This research tries to develop a heuristic approach that is non-delay algorithm by comparing Shortest Processing Time (SPT) and Largest Remaining Time (LRT) in the case of non-permutation flow shop to produce minimum mean flow time ratio. The result of simulation shows that the SPT algorithm gives less mean flow time value compared to LRT algorithm which means that SPT algorithm is better than LRT in case of non-permutation hybrid flow shop.

scholarly journals An Analysis of Research Trends in the Sustainability of Production Palnning

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 483
Author(s):  
Mohamed Saeed khaled ◽  
Ibrahim Abdelfadeel Shaban ◽  
Ahmed Karam ◽  
Mohamed Hussain ◽  
Ismail Zahran ◽  
...  
Keyword(s):  
Production Planning ◽  
Production Scheduling ◽  
Production Systems ◽  
Lot Sizing ◽  
Raw Materials ◽  
Social Indicators ◽  
Sustainable Production ◽  
Future Research ◽  
Scheduling Problems ◽  
Planning Problems

Sustainability has become of great interest in many fields, especially in production systems due to the continual increase in the scarcity of raw materials and environmental awareness. Recent literature has given significant attention to considering the three sustainability pillars (i.e., environmental, economic, and social sustainability) in solving production planning problems. Therefore, the present study conducts a review of the literature on sustainable production planning to analyze the relationships among different production planning problems (e.g., scheduling, lot sizing, aggregate planning, etc.) and the three sustainability pillars. In addition, we analyze the identified studies based on the indicators that define each pillar. The results show that the literature most frequently addresses production scheduling problems while it lacks studies on aggregate production planning problems that consider the sustainability pillars. In addition, there is a growing trend towards obtaining integrated solutions of different planning problems, e.g., combining production planning problems with maintenance planning or energy planning. Additionally, around 45% of the identified studies considered the integration of the economic and the environmental pillars in different production planning problems. In addition, energy consumption and greenhouse gas emissions are the most frequent sustainability indicators considered in the literature, while less attention has been given to social indicators. Another issue is the low number of studies that have considered all three sustainability pillars simultaneously. The finidings highlight the need for more future research towards holistic sustainable production planning approaches.

scholarly journals Application of genetic algorithm to industrial scheduling and problems of parameters evaluation

2021 ◽  
Vol 47 ◽  
Author(s):  
Edgaras Šakurovas ◽  
Narimantas Listopadskis
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Flow Shop ◽  
Np Hard ◽  
Scheduling Problems ◽  
Optimal Parameters ◽  
Algorithm Performance ◽  
Hard Problems ◽  
Np Hard Problems ◽  
Real World Problems

Genetic algorithms are widely used in various mathematical and real world problems. They are approximate metaheuristic algorithms, commonly used for solving NP-hard problems in combinatorial optimisation. Industrial scheduling is one of the classical NP-hard problems. We analyze three classical industrial scheduling problems: job-shop, flow-shop and open-shop. Canonical genetic algorithm is applied for those problems varying its parameters. We analyze some aspects of parameters such as selecting optimal parameters of algorithm, influence on algorithm performance. Finally, three strategies of algorithm – combination of parameters and new conceptualmodel of genetic algorithm are proposed.

A DYNAMIC APPROACH OF USING DISPATCHING RULES IN SCHEDULING

2016 ◽  
Vol 78 (6) ◽  
Author(s):  
Khaled Ali Abuhasel
Keyword(s):  
Processing Time ◽  
Job Shop ◽  
Flow Shop ◽  
Job Shop Scheduling ◽  
Working Environment ◽  
Dispatching Rules ◽  
Scheduling Problems ◽  
Changing Environment ◽  
Environment Simulation ◽  
Made In

Manufacturing system in reality has dynamic nature due to certain unexpected events occur in changing environment, which requires rescheduling. This does not mean that every decision is made in real time. Based on the state of the working environment, determining best rule at right time is one of the alternatives.  This study focuses on selecting the dispatching rule that show best performance dynamically both in static and changing environment.  Simulation is carried out by employing genetic algorithm on flow-shop and job-shop scheduling problems to compare the performance of the dispatching rules dynamically. Out of many rules proposed in the past, it has been observed that under certain conditions, the SPT (shortest processing time) performs best in both the environment, when the total processing time of a job is not high relatively.  

Hybrid Flow-Shop Scheduling Method and Simulation Based on Adaptive Genetic Algorithm

2014 ◽  
Vol 670-671 ◽  
pp. 1434-1438
Author(s):  
Jian Feng Zhao ◽  
Xiao Chun Zhu ◽  
Bao Sheng Wang
Keyword(s):  
Genetic Algorithm ◽  
Production Scheduling ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Adaptive Genetic Algorithm ◽  
Scheduling Problems ◽  
Mutation Operators ◽  
Hybrid Flow Shop Scheduling ◽  
Encoding Method

The n-job, k-stage hybrid flow shop problem is one of the general production scheduling problems. Hybrid flow shop (HFS) problems are NP-Hard when the objective is to minimize the makespan .The research deals with the criterion of makespan minimization for the HFS scheduling problems. In this paper we present a new encoding method so as to guarantee the validity of chromosomes and convenience of calculation and corresponding crossover and mutation operators are designed for optimum sequencing. The simulation results show that the Sequence Adaptive Cross Genetic Algorithm (SACGA) is an effective and efficient method for solving HFS Problems.

A New GT Heuristic for Solving Multi Objective Job Shop Scheduling Problems

2014 ◽  
Vol 591 ◽  
pp. 184-188
Author(s):  
D. Lakshmipathy ◽  
M. Chandrasekaran ◽  
T. Balamurugan ◽  
P. Sriramya
Keyword(s):  
Production Scheduling ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Heuristic Method ◽  
Flow Time ◽  
Scheduling Problems ◽  
Mean Flow ◽  
Practical Applications ◽  
Shop Scheduling ◽  
Mean Flow Time

The n-job, m-machine Job shop scheduling (JSP) problem is one of the general production scheduling problems in manufacturing system. Scheduling problems vary widely according to specific production tasks but most are NP-hard problems. Scheduling problems are usually solved using heuristics to get optimal or near optimal solutions because problems found in practical applications cannot be solved to optimality using reasonable resources in many cases. In this paper, optimization of three practical performance measures mean job flow time, mean job tardiness and makespan are considered. New Game theory based heuristic method (GT) is used for finding optimal makespan, mean flow time, mean tardiness values of different size problems. The results show that the GT Heuristic is an efficient and effective method that gives better results than Genetic Algorithm (GA). The proposed GT Heuristic is a good problem-solving technique for job shop scheduling problem with multi criteria.

Sign in / Sign up

Export Citation Format

Share Document