A Mixed-Integer Programming Model for the Job Scheduling Problem in a Production Company (original) (raw)
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Production scheduling for a job shop using a mathematical model
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Today, all organizations are continually seeking to produce high quality, reliable, and timely goods and services that meet the needs of their customers. Therefore, production scheduling is one of the most complex activities in production management in organizations. In the present work, the production projection is developed in a Job Shop system using a mathematical model of linear integer programming whose objective is to minimize the total lateness. The developed model is validated by means of an application case with three jobs and four machines, obtaining the optimum programming according to the requirements. The results obtained have been compared with a scheduling software to evaluate the performance of the proposed model.
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Hierarchical Minimization of Total Completion Time and Number of Tardy Jobs Criteria
2 Abstract: In this study, the single machine bicriteria scheduling problem of hierarchically minimizing the total completion time of jobs (C ) and number of tardy jobs (NT) with release time was explored. Two types of tot hierarchical minimization models (the case of the total completion time criterion being more important than the number of tardy jobs criterion and the case of the number of tardy jobs criterion being more important than the total completion time criterion) were discussed. Three heuristics (HR4, HR5 and HR6) selected from the literature were used to test the models.
European Journal of Operational Research, 2014
This study investigates scheduling problems that occur when the weighted number of late jobs that are subject to deterministic machine availability constraints have to be minimized. These problems can be modeled as a more general job selection problem. Cases with resumable, non-resumable, and semiresumable jobs as well as cases without availability constraints are investigated. The proposed efficient mixed integer linear programming approach includes possible improvements to the model, notably specialized lifted knapsack cover cuts. The method proves to be competitive compared with existing dedicated methods: numerical experiments on randomly generated instances show that all 350-job instances of the test bed are closed for the well-known problem 1jr i j P w i U i. For all investigated problem types, 98.4% of 500-job instances can be solved to optimality within 1 hour.
This paper presents a simulation and comparison analysis conducted to investigate the due-date assignment methods through various scheduling rules. The due date assignment methods investigated are flow time due date (FTDD) and total work content (TWK) method. Three scheduling rules are integrated in the simulation for scheduling of jobs on machines. The performance of the study is evaluated based on the configuration system of Hibret manufacturing and machine building Industry, subsidiary company of Metals and Engineering Corporation were thoroughly considered. The performance of the system is evaluated based on maximum tardiness, number of tardy jobs and total weighted tardiness. Simulation experiments are carried in different scenarios through combining due-date assignment methods and scheduling rules. A two factor Analysis of variance of the experiment result is performed to identify the effect of due-date assignment methods and scheduling rules on the performance of the job shop system. The least significant difference (LSD) method was used for performing comparisons in order to determine which means differ from the other. The finding of the study reveals that FTDD methods gives less mean value compared to TWK when evaluated by the three scheduling rules.
Solving the problem of scheduling the production process based on heuristic algorithms
JUCS - Journal of Universal Computer Science, 2022
The paper deals with a production scheduling process, which is a problematic and it requires considering a lot of various factors while making the decision. Due to the specificity of the production system analysed in the practical example, the production scheduling problem was classified as a Job-shop Scheduling Problem (JSP). The production scheduling process, especially in the case of JSP, involves the analysis of a variety of data simultaneously and is well known as NP-hard problem. The research was performed in partnership with a company from the automotive industry. The production scheduling process is a task that is usually performed by process engineers. Thus, it can often be affected by mistakes of human nature e.g. habits, differences in experience and knowledge of engineers (their know-how), etc. The usage of heuristic algorithms was proposed as the solution. The chosen methods are genetic and greedy algorithms, as both of them are suitable to resolve a problem that requir...
An optimization approach and a model for Job Shop Scheduling Problem with Linear Programming
2019
Optimization approaches and models are developed for job shop scheduling problems over the last decades, particularly the most attempts have been done in industry and considerable progress has been made on an academic line. The Job-shop scheduling considered the most significant industrial activities, mostly in manufacturing. The JSSP (Job Shop Scheduling Problems) is typical NP-hard problem. To solve this problem, we have used the linear programming approach. Real data have been taken from the company of the metalworking industry. The model has been created, then it was analyzed using Spreadsheet-Excel Solver. The appropriate sequence has been obtained and the results shown that it is possible to achieve the minimum completion time compared to other sequence combination