Optimization of knowledge transferring costs in designing product portfolio: a fuzzy binary linear programming model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nahid Dorostkar-Ahmadi ◽  
Mohsen Shafiei Nikabadi ◽  
Saman babaie-kafaki
Keyword(s):  
Linear Programming ◽  
Programming Model ◽  
Fuzzy Model ◽  
Linear Programming Model ◽  
Product Portfolio ◽  
Ranking Functions ◽  
Content Type ◽  
Binary Linear Programming ◽  
Knowledge Based ◽  
Knowledge Based Economy

Purpose The success of any organization in a knowledge-based economy depends on effective knowledge transferring and then proper use of the transferred knowledge. As is known, optimizing the knowledge transferring costs in a product portfolio plays an important role in improving productivity, competitive advantage and profitability of any organization. Therefore, this paper aims to determine an optimal product portfolio by minimizing the konlwedge transferring costs. Design/methodology/approach Here, a fuzzy binary linear programming model is used to select an optimal product portfolio. The model is capable of considering the knowledge transferring costs while taking into account the human-hours constraints for each product by a fuzzy approach. Using fuzzy ranking functions, a reasonable solution of the model can be achieved by classical or metaheuristic algorithms. Findings Numerical experiments indicate that the proposed fuzzy model is practically effective. Originality/value The contributions of this work essentially consist of considering knowledge transferring costs in selecting an optimal product portfolio and using the fuzzy data which make the model more realistic.

Optimization of profitability and liquidity for residential projects under debt and equity financing

2021 ◽  
Vol 11 (2) ◽  
pp. 369-391
Author(s):  
Emre Cevikcan ◽  
Yildiz Kose
Keyword(s):  
Linear Programming ◽  
Experimental Design ◽  
Cash Flow ◽  
Programming Model ◽  
Payback Period ◽  
Linear Programming Model ◽  
Project Financing ◽  
Equity Financing ◽  
Content Type ◽  
Space Allocation

PurposeAn appropriate space allocation among different residence types gives higher profitability and liquidity for cash flow management in real estate projects for developers. Thereby, a balance between debt and equity should be kept for capital formation in developers where high level of cost, profit and risk exists. The purpose of this paper is to provide cash flow optimization under debt and equity financing while providing an appropriate space allocation of residence types via synchronous consideration of profitability and liquidity.Design/methodology/approachA novel optimization methodology that includes project financing, optimization and experimental design modules is proposed. The first module, project financing, considers the flexibility of utilizing one or both of debt financing and equity financing when making capital. The optimization module addresses space allocation among different residence types for a construction while maximizing profitability and liquidity using two mixed-integer linear programming models in a pre-emptive manner. The experimental design module assesses the effects of decisive parameters within the methodology via multivariate analysis of variance (MANOVA).FindingsThe proposed methodology is applied to a real-life residential project in Istanbul. The optimization module yielded 42.5% profitability via the first linear programming model and 2.2% trade-off between liquidity and profitability while minimizing the payback period by the second linear programming model. Meanwhile, MANOVA results showed that profit per square meter and sale rate trends are the most prominent factors considering their significant effects on net present value and payback period.Originality/valueTo the best knowledge of the author, related papers focused only on profitability under equity financing. Liquidity (as an objective) and equity financing (as a financing method) have not been handled. Hence, this paper not only performs profitability and liquidity-oriented cash flow optimization under debt and equity financing but also optimizes space allocation of residences for the first time.

A web-based DSS for fuzzy distribution network optimization

2015 ◽  
Vol 28 (2) ◽  
pp. 260-274 ◽  
Author(s):  
Alp Ustundag ◽  
Aysenur Budak
Keyword(s):  
Linear Programming ◽  
Network Optimization ◽  
Programming Model ◽  
Distribution Network ◽  
Fuzzy Linear Programming ◽  
Strategic Decision ◽  
Linear Programming Model ◽  
Distribution Centers ◽  
Web Based ◽  
Content Type

Purpose – Distribution network design (DND) has become an important strategic decision for supply chain managers with increasing competitive nature of the industry nowadays. The purpose of this paper is to propose a web-based decision support system (DSS) for fuzzy distribution network optimization. For this purpose, a web-based DSS using fuzzy linear programming model is proposed to solve DND problem under uncertainty and a framework is created to optimize a distribution network. Design/methodology/approach – In this study, the fuzziness in distribution network optimization is addressed. Fuzzy linear programming is used in a DSS to consider the uncertain and imprecise data. A web-based DSS architecture is presented. Furthermore, as an application, distribution network optimization is conducted for a company in the ceramics industry. Findings – By using this DSS, the optimal transshipment amounts in the distribution network and the required facility and distribution centers can be determined for different fuzziness levels. In fact, for different uncertainty levels of input parameters, the planner can understand the range of optimum network planning costs. Based on the results of this study, planners will be able to decide how to develop the distribution network under uncertain demand. Originality/value – Reviewing previous research in the related literature revealed that there are no studies presenting a web-based DSS using fuzzy linear programming model to solve this type of problems under uncertainty.

Simultaneous scheduling of maintenance crew and maintenance tasks in bus operating companies: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rodrigo Martins ◽  
Francisco Fernandes ◽  
Virginia Infante ◽  
Antonio R. Andrade
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Programming Model ◽  
Maintenance Scheduling ◽  
Linear Programming Model ◽  
Integer Linear Programming Model ◽  
Content Type ◽  
Maintenance Schedules ◽  
Operating Company

PurposeThe purpose of this paper is to describe an integer linear programming model to schedule the maintenance crew and the maintenance tasks in a bus operating company.Design/methodology/approachThe proposed methodology relies on an integer linear programming model that finds feasible maintenance schedules. It minimizes the costs associated with maintenance crew and the costs associated with unavailability. The model is applied in a real-world case study of a Portuguese bus operating company. A constructive heuristic approach is put forward, based on solving the maintenance scheduling problem for each bus separately.FindingsThe heuristic finds better solutions than the exact methods (based on branch-and-bound techniques) in a much lower computational time.Practical implicationsThe results suggest the relevance of such heuristic approaches for maintenance scheduling in practice.Originality/valueThis proposed model is an effective decision-making support method that provides feasible maintenance schedules for the maintenance technicians and for the maintenance tasks in a fleet of buses. It also complies with several operational, technical and labour constraints.

Resource-based model for small innovative enterprises

2020 ◽  
Vol 58 (8) ◽  
pp. 1525-1541 ◽  
Author(s):  
Moinak Maiti ◽  
Victor Krakovich ◽  
S.M. Riad Shams ◽  
Darko B. Vukovic
Keyword(s):  
Linear Programming ◽  
Life Cycle ◽  
Dynamic Capabilities ◽  
Programming Model ◽  
Rate Of Change ◽  
Linear Programming Model ◽  
Mixed Integer ◽  
Significant Feature ◽  
Programming Technique ◽  
Content Type

PurposeThe paper introduces a resource-based linear programming model for resource optimization in small innovative enterprises (SIE).Design/methodology/approachThe model is grounded on resource-based view on the firm and dynamic capabilities approach. Linear programming technique is used to provide the actual framework to the resource-based model.FindingsThe paper introduces a new resource-based linear programming model for resource optimization in small innovative enterprises. The conceptual model is grounded on resource-based view (RBV) and dynamic capabilities strategy. The RVB of firm and firm strategy is based on the concept of economic rent. Linear programming technique is used to provide the actual framework to the resource-based model. In developing the versatility concept, study suggests a distinct sight regarding resource fungibility. Study classifies resources into multipliable, rentable and expendable resources to increases adequacy of the model. The developed model includes both tangible and intangible assets such as human capital. The survival rate of SIE in the early stages of life cycle is very low due to the competition among SIEs. In this regard, the greatest advancement of the developed resource-based linear programming model is its simplicity and versatility which is much desirable for the SIE especially in their initial stages of the life cycle. Kelliher and Reinl (2009) argued that micro firms have unique advantage over bigger firms in following term: rate of learning or redeployment of strategy in micro firms is faster than the rate of change in their environment. One very significant feature of the developed resource-based linear programming model is that mathematically the proposed model could easily be transformed into mixed integer or stochastic linear programming models to meet the time variant requirement of small firms especially when it expands its operation.Research limitations/implicationsThe survival rate of SIE in the early stages of life cycle is very low due to the competition among SIEs. In this regard, the greatest advancement of the developed resource-based linear programming model is its simplicity and versatility which is much desirable for the SIE especially in their initial stages of the life cycle. Kelliher and Reinl (2009) argued that micro firms have unique advantage over bigger firms in following term: rate of learning or redeployment of strategy in micro firms is faster than the rate of change in their environment. One very significant feature of the developed resource-based linear programming model is that mathematically the proposed model could easily be transformed into mixed integer or stochastic linear programming models to meet the time variant requirement of small firms especially when it expands its operation.Originality/valueOne very significant contribution of the present study is that the study develops a new resource-based model for SIE especially for the SIE in the initial stages of the life cycle, to gain competitive advantages. Furthermore, the present study contributes to the existing literature in strategy at least in three senses as mentioned below: 1. further addition of SIE research based on the RBV and dynamic capabilities in the strategy literature 2. in developing the versatility concept, the study suggests a distinct sight regarding resource fungibility and it classifies resources into three categories as follows: multipliable, rentable and expendable resources to increases adequacy of the model. 3. Finally, the study introduces a new resource-based linear programming model for SIE resources allocation. To the best of author’s knowledge, no such similar model is introduced by any previous studies for small firm. The greatest advancement of the developed resource-based linear programming model is its simplicity and versatility.

A grey mathematical model for crashing of projects by considering time, cost, quality, risk and law of diminishing returns

2018 ◽  
Vol 8 (3) ◽  
pp. 272-294 ◽  
Author(s):  
Amin Mahmoudi ◽  
Mohammad Reza Feylizadeh
Keyword(s):  
Linear Programming ◽  
Programming Model ◽  
Linear Programming Model ◽  
Time Cost ◽  
Saturation Point ◽  
Content Type ◽  
Diminishing Returns ◽  
Project Risks ◽  
Quality Risk ◽  
The Law

Purpose The purpose of this paper is to examine projects crashing based on the factors including cost, time, quality, risk and the law of diminishing returns. Design/methodology/approach The paper first investigated effective factors on project crashing then proposed a grey linear programming model. In the proposed grey linear programming model, the costs of quality of works that include the cost of conformance and non-conformance of deliverables in the project were studied. The results are presented for considering the existing uncertainties using positioned programming under the sensitivity analysis table and graphs. Findings The lack of consideration of project risks will reduce the project success probability in future. The proposed model reduces the existing uncertainties to a significant extent by covering the project risks completely. Based on the law of diminishing returns, after a certain point technically known as saturation point, the increase of resources does not lead to the reduction of time and may even have negative impacts. Finding the saturation point for each activity prevents the excessive allocation of resources that can lead to reduction of productivity. Practical implications The main duty of each project manager is finishing the project in the framework of the determined objectives. In most of the cases, after the preparation of the initial project schedule by the project team, it is seen that there is a need for the time reduction. This study has used a grey linear programming model for optimum crashing of project activities. In order to make the model more realistic and applicable, the authors endeavoured to consider most of the factors that are involved in doing a project. Originality/value In the present study, to the best of the authors’ knowledge the factors of time, cost, quality, risk and the law of diminishing returns are simultaneously considered in project crashing for the first time and the grey theory was used for considering the uncertainties of project parameters. Also, “the law of diminishing returns” has not been considered during crashing in the studies conducted so far.

A Linear Programming Model for Product Mix Profit Maximization in A Small Medium Enterprise Company

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
S Mohd Baki ◽  
Jack Kie Cheng
Keyword(s):  
Linear Programming ◽  
Production Planning ◽  
Business Performance ◽  
Programming Model ◽  
Profit Maximization ◽  
Optimal Level ◽  
Linear Programming Model ◽  
Product Mix ◽  
Small Medium Enterprises ◽  
Medium Enterprises

Production planning is often challenging for small medium enterprises (SMEs) company. Most of the SMEs are having difficulty in determining the optimal level of the production output which can affect their business performance. Product mix optimization is one of the main key for production planning. Many company have used linear programming model in determining the optimal combination of various products that need to be produced in order to maximize profit. Thus, this study aims for profit maximization of a SME company in Malaysia by using linear programming model. The purposes of this study are to identify the current process in the production line and to formulate a linear programming model that would suggest a viable product mix to ensure optimum profitability for the company. ABC Sdn Bhd is selected as a case study company for product mix profit maximization study. Some conclusive observations have been drawn and recommendations have been suggested. This study will provide the company and other companies, particularly in Malaysia, an exposure of linear programming method in making decisions to determine the maximum profit for different product mix.

A Linear Programming Model to Evaluate Gas Availability for Vital Industries in Saudi Arabia

1992 ◽  
Vol 43 (11) ◽  
pp. 1035-1045
Author(s):  
S O Duffuaa ◽  
J A Al-Zayer ◽  
M A Al-Marhoun ◽  
M A Al-Saleh
Keyword(s):  
Saudi Arabia ◽  
Linear Programming ◽  
Programming Model ◽  
Linear Programming Model
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