scholarly journals The Optimization Problem of Product Mix and Linear Programming Applications: Case Study in the Apparel Industry

2017 ◽  
Vol 2 (2) ◽  
Author(s):  
Gera Workie Woubante
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Inventory Management ◽  
Industrial Development ◽  
Optimization Problem ◽  
Management Decision ◽  
Product Mix ◽  
Use Of Resources ◽  
Customer Orders

Industrial development strategy is characterized by the efficient use of resources at every production stage. The analysis and efficient utilization of resources are made sustainable by effective management decision making techniques employed in the industry. A quantitative decision making tool called linear programming can be used for the optimization problem of product mix. Understanding the concept behind the optimization problem of product mix is essential to the success of the industry for meeting customer needs, determining its image, focusing on its core business, and inventory management. Apparel manufacturing firms profit mainly depends on the proper allocation and usage of available production time, material, and labor resources. This paper considers an apparel industrial unit in Ethiopia as a case study. The monthly held resources, product volume, and amount of resources used to produce each unit of product and profit per unit for each product have been collected from the company. The data gathered was used to estimate the parameters of the linear programming model. The model was solved using LINGO 16.0 software. The findings of the study show that the profit of the company can be improved by 59.84%, that is, the total profit of Birr 465,456 per month can be increased to Birr 777,877.3 per month by applying linear programming models if customer orders have to be satisfied. The profit of the company can be improved by 7.22% if the linear programming formulation does not need to consider customer orders.

scholarly journals “Case Study: Application for optimizing the product mix problem of linear programming in the Apparel Industry”

2021 ◽  
Vol 23 (07) ◽  
pp. 1091-1098
Author(s):  
Varsha Rathi ◽  
◽  
Sangeeta Gupta ◽  
Sweta Srivastav ◽  
◽  
...  
Keyword(s):  
Linear Programming ◽  
Optimization Problem ◽  
Apparel Industry ◽  
Management Decision ◽  
Effective Management ◽  
Product Mix ◽  
Management Decision Making ◽  
Labor Resources ◽  
Study Application

The industry has made effective management decision-making techniques possible through surveys and the efficient use of sources and assets. Linear programming can be used for the optimization problem of product mix. We have to understand the concept behind the optimization problem of product mix is important to get success in the industry for meeting customer needs. The manufacturing profit depends on the proper distribution of product material and usage of available production time material and labor resources. The findings of the study show that the profit of the company and the demand for the product.

scholarly journals Constructing a Sustainable and Dynamic Promotion Model for Fresh Foods Based on a Digital Transformation Framework

2021 ◽  
Vol 13 (19) ◽  
pp. 10687
Author(s):  
Tsung-Yin Ou ◽  
Guan-Yu Lin ◽  
Chin-Ying Liu ◽  
Wen-Lung Tsai
Keyword(s):  
Decision Making ◽  
Business Models ◽  
Simulation Analysis ◽  
Real Data ◽  
Digital Transformation ◽  
Retail Industry ◽  
Management Decision ◽  
Sustainable Business ◽  
Use Of Resources ◽  
Convenience Stores

The emergence of digital technology has compelled the retail industry to develop innovative and sustainable business models to predict and respond to consumer behavior. However, most enterprises are crippled with doubt, lacking frameworks and methods for moving forward. This study establishes a five-step decision-making framework for digital transformation in the retail industry and verifies it using real data from convenience stores in Taiwan. Data from residential type and cultural and educational type convenience stores, which together account for 75% of all stores, underwent a one-year simulation analysis according to the following three decision models for promotions: the shelf-life extended scrap model (SES), the fixed remaining duration model (FRD), and the dynamic promotion decision model (DPD). The results indicated that the DPD model reduced scrap in residential type stores by 12.88% and increased profit by 15.43%. In cultural and educational stores, the DPD model reduced scrap by 10.78% and increased profit by 7.63%. The implementation of the DPD model in convenience stores can bring additional revenue to operators, and at the same time address the problem of food waste. With the full use of resources, sustainable operation can be turned into a concrete and feasible management decision-making plan.

An (s, S) Inventory Optimization Problem

2019 ◽  
pp. 187-206
Author(s):  
Gizem Sağol ◽  
Görkem Sariyer ◽  
Banu Yetkin Ekren ◽  
Mustafa Gökalp Ataman
Keyword(s):  
Inventory Management ◽  
Optimization Problem ◽  
Service Level ◽  
Inventory Model ◽  
Considerable Effort ◽  
Medical Products ◽  
High Service ◽  
Inventory Optimization ◽  
Medical Supplies

Inventory management is one essential lever to use the resources efficiently. However, managing inventories in hospitals is a challenging task because of the several issues: a high service level of medical supplies is required under the unpredictable demand, medical products constitute a significant portion of the overall costs, and the management of these supplies requires considerable effort to check the levels to track usage and to distribute them. Therefore, it is pertinence to apply operations research tools to cope with the managerial issues of the hospital inventory system. In this chapter, the authors implement an (s, S) inventory model by using simulation in a case study of a hospital in Izmir, Turkey. They aim to analyze the unpredictable nature of demand of medical supplies in this hospital and its implications on the developed inventory policy.

Production Planning Optimization in F Company: A Scheduling Theory Case Study

2013 ◽  
Vol 655-657 ◽  
pp. 1646-1649 ◽  
Author(s):  
Chi Zhang ◽  
Zhen He ◽  
Yuan Peng Ruan
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Optimization Problem ◽  
Assembly Line ◽  
Scheduling Theory ◽  
Scheduling Model ◽  
Planning Optimization ◽  
Optimization Methodology ◽  
Optimum Production

Scheduling is an effective optimization methodology which has been widely used for production planning. This paper presents a scheduling model to optimize the output of an assembly line in F Semiconductor Company in Tianjin, China. The authors formulate the optimization problem as linear programming. The model and its implementation are described in detail in this article. The optimum production allocations have been founded by the scheduling model and the output has been increased.

scholarly journals Using game theory to assess multi-company strategies in watershed management

2016 ◽  
Vol 11 (3) ◽  
pp. 535
Author(s):  
Luke Ogilvie Thompson ◽  
Alexandre Bevilacqua Leoneti ◽  
René Bañares-Alcántara ◽  
Eduardo Cleto Pires
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Watershed Management ◽  
Nash Equilibria ◽  
Engineering Problem ◽  
Management Decision ◽  
Problem Case ◽  
Management Decision Making

The main objective of this work was to evaluate the use of game theory as a strategic tool for watershed management decision-making. An engineering problem case study was used in which three organizations compare various scenarios when deciding where to locate a polluting plant on a watershed. Six games were modeled to provide a variety of conditions that could feasibly be implemented and were simulated using software for finding Nash Equilibria solutions. The results show that game theory can provide key insights, such as the consideration of other players’ strategies, and identify possible pitfalls that may occur when the companies seek only to maximize their individual profitability.

Adoption of renewable energy technologies (RETs) using a mixed-method approach

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nicholas Morgan Geddes
Keyword(s):  
Decision Making ◽  
Diffusion Of Innovations ◽  
Mixed Methodology ◽  
Management Decision ◽  
Content Type ◽  
Study Approach ◽  
Energy Technologies ◽  
Water Pumping ◽  
Management Decision Making

Purpose This paper aims to propose that the socio-technical perspective is under-represented when appraising the adoption potential of renewable energy technologies (RETs) in late-industrialising countries and that this results in under-adoption. It also aims to identify a methodological approach that allows the socio-technical perspective to be integrated into management decision-making, alongside the more typical economic appraisal methodology. Design/methodology/approach A case study and novel mixed-methodology approach is used, which applies the diffusion of innovations framework, innovation system (IS) framework and system dynamics modelling (SDM) alongside traditional economic modelling and appraisal techniques. This approach is used to assess the adoption potential of solar photovoltaic (PV) and diesel water pumping systems in the wildlife conservation sector and surrounding rural communities in Kenya. The case study approach tests the merits of the mixed-methodology approach. Findings The life-cycle costs of solar PV water pumping systems are lower in nearly all financing and utilisation scenarios; offer additional social, technical and environmental benefits; and the conditions exist for greater adoption. The use of an integrated diffusion of innovations and IS framework generates significant qualitative data that can support management decision-making. The use of SDM techniques aid conceptualisation of the community economic, water and institutional systems into which water pumps may be diffused and provide a starting point for formal SDM simulation. The results suggest that these techniques capture the socio-technical perspective well and, when used alongside traditional project appraisal approaches, produce more complete information with which to support management decision-making. Originality/value This mixed-methodology approach could be used by practitioners to increase the diffusion and adoption of RETs in more complex contexts in late-industrialising countries. The emergent theory built through the case-study approach should be tested further to assess the merits of applying these techniques to support RET management decision-making in other contexts and more broadly.

Implementation of Quantitative Risk Assessment: Case Study

2014 ◽  
Author(s):  
David Mangold ◽  
W. Kent Muhlbauer ◽  
Jim Ponder ◽  
Tony Alfano
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Management ◽  
The United States ◽  
Management Program ◽  
Quantitative Risk Assessment ◽  
Management Decision ◽  
Classical Statistics ◽  
Wide Range

Risk management of pipelines is a complex challenge due to the dynamic environment of the real world coupled with a wide range of system types installed over many decades. Various methods of risk assessment are currently being used in industry, many of which utilize relative scoring. These assessments are often not designed for the new integrity management program (IMP) requirements and are under direct challenge by regulators. SemGroup had historically used relative risk assessment methodologies to help support risk management decision-making. While the formality offered by these early methods provided benefits, it was recognized that, in order to more effectively manage risk and better meet the United States IMP objectives, a more effective risk assessment would be needed. A rapid and inexpensive migration into a better risk assessment platform was sought. The platform needed to be applicable not only to pipeline miles, but also to station facilities and all related components. The risk results had to be readily understandable and scalable, capturing risks from ‘trap to trap’ in addition to risks accompanying each segment. The solution appeared in the form a quantitative risk assessment that was ‘physics based’ rather than the classical statistics based QRA. This paper will outline the steps involved in this transition process and show how quantitative risk assessment may be efficiently implemented to better guide integrity decision-making, illustrated with a case study from SemGroup.

scholarly journals The prioritization and categorization method (PCM) process evaluation at Ericsson: a case study

2017 ◽  
Vol 23 (2) ◽  
pp. 377-398 ◽  
Author(s):  
Jens Ohlsson ◽  
Shengnan Han ◽  
Harry Bouwman
Keyword(s):  
Decision Making ◽  
Process Improvement ◽  
Process Management ◽  
Single Case ◽  
Management Decision ◽  
Organizational Setting ◽  
Content Type ◽  
Business Context ◽  
Management Decision Making

Purpose The purpose of this paper is to demonstrate and evaluate the prioritization and categorization method (PCM), which facilitates the active participation of process stakeholders (managers, owners, customers) in process assessments. Stakeholders evaluate processes in terms of effectiveness, efficiency and relevance against certain contextual business and industry factors. This collective evaluation serves as a foundation for the management decision-making process regarding process improvement and redesign. Design/methodology/approach The PCM is examined based on a case study at Ericsson. In total, 55 stakeholders, representing different organizational levels and functions, assessed eight core processes. Follow-up interviews and feedback after the evaluation sessions were collected for triangulation purpose. Findings The PCM helps Ericsson evaluate its processes within business context and industry environments. The results show that, to realize seamless end-to-end processes in the eight assessed processes, Ericsson has to make a greater effort to improve its process structures, governance and culture for fulfilling the needs of future business. Ericsson Steering Group is satisfied with the insights provided and has decided to train more stakeholders to use PCM. Research limitations/implications This research is based on a single case within a specific organizational setting. The results may not be necessary generalizable to other business and industry settings. Organizations need to configure PCM in consideration of their own processes and business contingencies to explore and fulfil their process improvement purposes. Originality/value This paper presents a new context-aware, easy-to-use and holistic method for business process management (BPM), the PCM. The method requires the active engagement of stakeholders, it focusses on developing dynamic BPM capabilities and fully embeds organizational contingencies and contextual factors in the decision-making regarding BPM. This paper contributes a novel method to explorative BPM.

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