Usulan Penjadwalan Produksi dengan Algoritma Ant Colony (Studi Kasus PT. KLM Medan)

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Dila Syafrina Bangko ◽  
Rosnani Ginting
Keyword(s):  
Production Process ◽  
Production Scheduling ◽  
Completion Time ◽  
Processing Time ◽  
Ant Colony Algorithm ◽  
Optimal Combination ◽  
Ant Colony ◽  
A Value ◽  
Scheduling Method

Algoritma Ant Colony adalah suatu metauristik yang menggunakan teknik semut dengan kombinasi permasalahan secara optimal atau secara komunikasi semunt yang menggunakan alat penciuman untuk memecahkan masalah. Metode penjadwalan produksi yang selama ini digunakan berdasarkan kesamaan proses produksi. Hal inilah yang terkadang menyebabkan waktu penyelesaian produksi menjadi lebih panjang. Maka dilakukan metode lain untuk menggurangi makespan yaitu dengan menggunakan metode penjadwalan algoritma ant colony. Pada metode Shortest Processing Time (SPT) menghasilkan makespan sebesar 236079.89, sedangkan pada algoritma ant colony menghasilkan nilai α=10, β = 1, ρ = 0.5, Ncmax = 50, jumlah semut 7 dan makespan=215243.22. berdasarkan hasil yang diperoleh maka algoritma ant colony memiliki makespan terkecil yaitu 215243.22 detik.   The Ant Colony algorithm is a metauristic that uses ant techniques with optimal combination of problems or semuntic communication using olfactory tools to solve problems. The production scheduling method that has been used is based on the similarity of the production process. This is what sometimes causes the production completion time to be longer. Then another method is used to reduce makespan by using the ant colony algorithm scheduling method. In the Shortest Processing Time (SPT) method produces makespan of 236079.89, while the ant colony algorithm produces a value of α = 10, β = 1, ρ = 0.5, Ncmax = 50, the number of ants 7 and makespan = 215243.22. Based on the results obtained, the ant colony algorithm has the smallest makespan, 215243.22 seconds.

Weaving scheduling based on an improved ant colony algorithm

2020 ◽  
pp. 004051752094889
Author(s):  
Wentao He ◽  
Shuo Meng ◽  
Jing’an Wang ◽  
Lei Wang ◽  
Ruru Pan ◽  
...  
Keyword(s):  
Production Scheduling ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Superior Performance ◽  
Ant Colony System ◽  
Local Optimum ◽  
Scheduling Method ◽  
Automatic Methods ◽  
Automatic Scheduling ◽  
Improved Ant Colony Algorithm

Weaving enterprises are faced with problems of small batches and many varieties, which leads to difficulties in manual scheduling during the production process, resulting in more delays in delivery. Therefore, an automatic scheduling method for the weaving process is proposed in this paper. Firstly, a weaving production scheduling model is established based on the conditions and requirements during actual production. By introducing flexible model constraints, the applicability of the model has been greatly expanded. Then, an improved ant colony algorithm is proposed to solve the model. To address the problem of the traditional ant colony algorithm that the optimizing process usually traps into local optimum, the proposed algorithm adopts an iterative threshold and the maximum and minimum ant colony system. In addition, the initial path pheromone distribution is formed according to the urgency of the order to balance each objective. Finally, the simulation experiments confirm that the proposed method achieves superior performance compared with manual scheduling and other automatic methods. The proposed method shows a certain guiding significance for weaving scheduling in practice.

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.

USING ANT COLONY OPTIMIZATION TO MINIMIZE THE FUZZY MAKESPAN AND TOTAL WEIGHTED FUZZY COMPLETION TIME IN FLOW SHOP SCHEDULING PROBLEMS

2009 ◽  
Vol 17 (04) ◽  
pp. 559-584 ◽  
Author(s):  
PENG-JEN LAI ◽  
HSIEN-CHUNG WU
Keyword(s):  
Completion Time ◽  
Ant Colony Algorithm ◽  
Fuzzy Numbers ◽  
Flow Shop ◽  
Computational Procedure ◽  
Ant Colony ◽  
Flow Shop Scheduling ◽  
Scheduling Problems ◽  
Shop Scheduling ◽  
Processing Times

The flow shop scheduling problems with fuzzy processing times are investigated in this paper. For some special kinds of fuzzy numbers, the analytic formulas of the fuzzy compltion time can be obtained. For the general bell-shaped fuzzy numbers, we present a computational procedure to obtain the approximated membership function of the fuzzy completion time. We define a defuzzification function to rank the fuzzy numbers. Under this ranking concept among fuzzy numbers, we plan to minimize the fuzzy makespan and total weighted fuzzy completion time. Because the ant colony algorithm has been successfully used to solve the scheduling problems with real-valued processing times, we shall also apply the ant colony algorithm to search for the best schedules when the processing times are assumed as fuzzy numbers. Numerical examples are also provided and solved by using the commercial software MATLAB.

scholarly journals Mutation Ant Colony Algorithm of Milk-Run Vehicle Routing Problem with Fastest Completion Time Based on Dynamic Optimization

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Jianhua Ma ◽  
Guohua Sun
Keyword(s):  
Vehicle Routing ◽  
Dynamic Optimization ◽  
Vehicle Routing Problem ◽  
Completion Time ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Routing Problem ◽  
Numerical Examples ◽  
Customer Order ◽  
Milk Run

The objective of vehicle routing problem is usually to minimize the total traveling distance or cost. But in practice, there are a lot of problems needed to minimize the fastest completion time. The milk-run vehicle routing problem (MRVRP) is widely used in milk-run distribution. The mutation ACO is given to solve MRVRP with fastest completion time in this paper. The milk-run VRP with fastest completion time is introduced first, and then the customer division method based on dynamic optimization and split algorithm is given to transform this problem into finding the optimal customer order. At last the mutation ACO is given and the numerical examples verify the effectiveness of the algorithm.

Cascade Reservoirs Optimal Scheduling Method Based on Chaotic Ant Colony Algorithm

2014 ◽  
Vol 919-921 ◽  
pp. 1230-1233
Author(s):  
Zhong Hao Zhu ◽  
Hong Min Gao
Keyword(s):  
Ant Colony Algorithm ◽  
Optimal Scheduling ◽  
Ant Colony ◽  
Effective Solution ◽  
Cascade Reservoirs ◽  
Cascade Hydropower Stations ◽  
Scheduling Method ◽  
Generation Capacity ◽  
Hydropower Stations

On the basis of the analysis of the basic information of the river basin reservoirs and application of chaotic ant colony algorithm, the medium-and long-term optimization operation model is established, which regards the maximum annual generation capacity of the cascade hydropower stations as the main purpose. The simulation result shows the algorithm improves the total annual power generation of the cascade reservoirs, and finally provides an effective solution to solve the cascade reservoirs optimization operation problem.

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