Material Handling and Product Optimality of an Educational Institution Bakery Using Integer Programming

Material Handling and Product Optimality of an Educational Institution Bakery Using Integer Programming

Adedugba Adebayo, Ogunnaike Olaleke, Kingsley Adeyemo, Busola Kehinde
Copyright: © 2021 |Pages: 9
DOI: 10.4018/IJBSA.20210701.oa4
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Abstract

This study presents a numerical analysis for enhancing material handling allotment and deciding whether to produce or not in a bread production section of an educational institution. The study utilized 0/1 and real variables by the means of integer linear programming. In line with this, integer linear programming was applied in a bread production plant that produces three brands of bread, such as, medium size (x1), huge size (x2), and small size (x3). The discoveries using 0/1 variable shows that x1 = x2 = x3 = 1 while Z = 80 Naira. Hence, the item mix of bread is optimal, and production can continue. The result obtained utilizing real variable demonstrated that x1 (medium-size bread) = 649, x2 (huge-size bread) = 0, x3 (small-size bread) = 145, Z=18,388 Naira. In this manner the material handling allotment was optimized to obtain a profit of 18,388 Naira. Consequently, the organization should produce more medium-size bread (x1), more small-size bread (x3), and less huge-size bread (x2).
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1. Introduction

In a production framework, there are a lot of cycles and events that are sequentially arranged. One of the production frameworks is material handling. It is an integral aspect of production that decides the amount and place, which in turn will determine the product output. In line with this, there is need to optimize the interconnected production frameworks by applying optimization strategies to achieve product optimality (Ogunnaike, Bishop, Akinsulire, Kehinde, & Oreagba 2018). This model is employed to decide if an item will be produced or not due to limited resources. The high demand for raw materials require equivalent effectiveness in material handling proficiency and allocation in the manufacturing sector. Mathematical techniques are often proposed due to the need from organizations to respond to shortage or economic situations (Kallrath, 2005). These techniques investigate and measure the productivity and propose alternative solutions.

An optimal material handling framework is set to accomplish the profitability of an item. On the grounds that about 80% of the overall cost of an item is fundamentally based on the allocation and movement of materials (Kamble & Patil, 2019). While, 20% is associated with the procedure of production. According to (Noor, Omair, Maqsood & Zubairm, 2019) the cycle of material handling includes various capacities, such as, the conveyance and capacity in an assembling plant, the control and, security of crude materials and items. It also involves the allocation of materials and completed products, sorting, arrangement, fabricating and utilization. The most significant aspect of material handling process is the allotment of materials to a suitable location of utilization within any production facility (Mohite & Dongre, 2015). This will make the manufacturing procedure seamless and less time will be expended during production and product optimality will be achieved. Purnomo and Wiwoho (2019) asserted that an optimal material handling distribution framework and the determination of what to produce precipitate profitability.

The conveyance of materials within any production structure, for instance, the rate, quantity, and satisfying similar number of necessities are the objectives to optimize material allocation and item production (Adebayo, Kehinde, Ogunnaike, Olaoye, & Adesanya, 2019). In line with this, the technique of mixed-integer linear programming model was utilized to tackle a scheduling issue in a school which was an issue of allocation (Kristiansen, Sorensen & Stidsen, 2015). The utilization of integer mathematical models can be applied to portray decision issues based on the optimal utilization of resources in designing innovation, businesses and other various fields (Al-Shihabi & Aldurgam, 2020). A linear model with an integer limitation and decision factors is termed linear integer model. This class of mathematical model has a specific significance in organizations where the dynamic state of variables is engaged with numerous decision making circumstances i.e. production fields.

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