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.

scholarly journals Research of the College Enrollment Plan Based on Fuzzy Linear Programming Model

2021 ◽  
Vol 251 ◽  
pp. 01092
Author(s):  
Yuhong Sun ◽  
Guoxing Zhang ◽  
Yueyang Gao ◽  
Mingzhu Chen
Keyword(s):  
Linear Programming ◽  
Mathematical Models ◽  
Hierarchical Structure ◽  
College Enrollment ◽  
Programming Model ◽  
College Admission ◽  
Fuzzy Linear Programming ◽  
Linear Programming Model ◽  
Use Of Resources ◽  
Linear Programming Methods

This paper aims at the problems of professional structure and hierarchical structure in college admission plans, uses linear programming methods to establish mathematical models, maximizes the use of resources on the basis of completing the national enrollment plan, determines the reasonable enrollment structure and enrollment scale, and makes the enrollment plan more scientific and reasonable. In actual situations, the number of students enrolled in the school, the consumption of students, and the number of teachers are constantly changing. Therefore, the concept of fuzzy linear programming is introduced, and the constraints of the linear programming model are fuzzy optimized to obtain more reasonable results, which inspires some reasonable suggestions for colleges in formulating enrollment plans.

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.

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.

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