An integrated model for solving production planning and production capacity problems using an improved fuzzy model for multiple  linear programming according to Angelov's method

Khalaf, Batool Atiyah; Khalaf, Wakas S.; Mansor, Hassan Kadum

doi:10.21533/pen.v9i3.2254

Cited by 2 publications

(1 citation statement)

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“…It is possible to take advantage of this method through the assistance it provides in designing the manufacturing process and reducing unnecessary diversity that causes duplication in product design, as aggregate technology can identify product families and parts that can be manufactured in manufacturing cells in one batch, which leads to a reduction in time Preparing for the process, reducing waiting time, reducing stock under operation, and simplifying the process of planning and controlling production [17].…”

Section: Theoretical Motivationsmentioning

confidence: 99%

Solving multi-objective supply chain management using non-dominated sorting genetic algorithm

Khalaf¹

2023

PEN

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Focusing on production processes is the decisive factor in managing an efficient supply chain that leads to the company's success. The objective constraints in the model include all the goals the company seeks to achieve and the level to achieve for each. In addition to clarifying the contribution of each decision variable in achieving the specified levels of the different goals, the conclusions reached are the results that prove the possibility of solving a problem. Applying the mathematical model according to the demand for parts (derived from the demand for the final product) contributed significantly to saving the stock of raw materials, as (100) refers to the quantity that is kept as a regular stock for the first week and varies from one week to another according to the change in demand. As a result of reducing the stock of materials, the costs associated with it will decrease, and the difference can be seen in the total costs of storing raw materials and semimanufactured parts, which is estimated at (47929.1) Iraqi dinars) for the storage of materials and parts for all weeks, according to the planning periods established by the company. By applying the genetic algorithm, the total storage costs were calculated, and it was (13024.8) Iraqi dinars, which is the most critical indicator of success in improving the supply chain performance.

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Section: Theoretical Motivationsmentioning

confidence: 99%

Solving multi-objective supply chain management using non-dominated sorting genetic algorithm

Khalaf¹

2023

PEN

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Designing Data-Intensive Application System for Production Plans Data Processing and Near Real-Time Analytics

Suleykin

Panfilov

2022

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)

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An integrated model for solving production planning and production capacity problems using an improved fuzzy model for multiple linear programming according to Angelov's method

Cited by 2 publications

References 0 publications

Solving multi-objective supply chain management using non-dominated sorting genetic algorithm

Solving multi-objective supply chain management using non-dominated sorting genetic algorithm

Designing Data-Intensive Application System for Production Plans Data Processing and Near Real-Time Analytics

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