Solving fully fuzzy mathematical programming model of EOQ problem with a direct approach based on fuzzy ranking and PSO

Usually purchasing cost is to be paid instantly after the delivery time in classical EOQ model. But practically, retailer demands the customers for pre-payment of whole or a specific percentage of purchasing cost prior to delivery time. The purpose of this article is to develop the customer's inventory control models with time-price dependent demand by maximising average total profit of system for deteriorating items under the constraint of full pre-payment based on circumstances like: No shortages; full backordering shortages; partial lost sale; all with and without preservation. The article estimates optimum replenishment cycle, selling price, backordered quantity and preservation constant by classical optimisation technique. So, to validate derived models, numerical examples along with sensitivity analysis is undertaken, practically advising retailer to opt for pre-payment by offering discount to customer without shortages but with preservation technology scheme and then opting full prepayment with fully backordering with utilisation of preservation technology.

The profitability of small businesses in the French construction industry depends partly on their social capital. However, social capital yields advantages as well as constraints. How and under what conditions do social networks improve a company's profit margins? From a socio‐technical perspective and strategic analysis, we defend the idea that return on social capital is conditioned by the nature of the tasks performed and by the interdependencies among firms. Comparing about 160 businesses from four various crafts, we show that loose networks profit relatively specialized businesses working independently on construction sites, while cohesive networks benefit those businesses that are most affected by socio‐technical uncertainties.

Purpose: This study aims to determine the compliance and understanding of PT KMU in implementing PSAK No. 24 of 2018, transparency, and disclosure of information provided by PT KMU to employees regarding the provision of employee benefits, and the impact of the application of PSAK No. 24 of 2018 on PT KMU's financial statements. Research methodology: Qualitative descriptive research was conducted through interviews, observations, and documentation. Results: As a consequence of this study, PT KMU put into effect PSAK 24 of 2018 in compliance with both Indonesian laws and financial accounting standards. PT KMU offers employees full openness and access to information on perks. Applying PSAK No. 24 in 2018 creates deferred tax assets and affects the company's profit margin. Limitations: The limitations of this research are that the interviews with PT KMU informants were conducted simultaneously, and the list of interview questions between informants was the same. Contribution: This research advances our knowledge and comprehension of how to use PSAK 24 of 2018 in compliance with relevant laws and regulations as well as Indonesian Financial Accounting Standards.

The basic assumption of the classical inventory (EOQ/EPQ) models is that %100 of items ordered/produced are perfect. However, in most of the production processes, it is unavoidable that the items ordered or produced are defective. This study developes a fuzzy economic order quantity model with defective items and shortages. In this model, the demand, defective rate, ordering cost, unit cost, disposal cost, holding cost, backordering cost and screening cost are expressed as trapezoidal and triangular fuzzy numbers. Moreover, the Graded Mean Integration Representation method is applied to defuzzify the total profit function in fuzzy sense, and then the optimal policy for the model is determined. The results between crisp case and fuzzy case are compared with the help of numerical examples. Finally, sensitivity analysis is carried out to find the effect of changes in the values of selling prices of good-and imperfect quality items, screening rate and percentage of scrap items on optimal solutions.

This paper extends a fruitful fuzzy EOQ (Economic Order Quantity) track of research with a multi-item model that takes storage limitation into consideration as well as a finite production rate (i.e. the products are produced to stock and not purchased). The order cycle time and the demand are allowed to be triangular fuzzy numbers. In the process industry, this is a situation that often occurs, since the production equipment typically manufactures a large amount of only one product at a time. The model is developed and solved with Lagrange multipliers. Two illustrative examples are also given.

The standard EOQ problem is studied from a cash flow point of view. The present value of the stream of cash disbursements is minimised, where the discount rate is the cost of capital, ICAP, rather than the total carrying charge, I. The value of I, which is used in the EOQ formula, contains two terms, ICAP + ΔI, where ΔI represents the additional carrying costs such as obsolescence, handling, etc. The purpose of this paper is to derive a formula for the errors which accrue when the simpler EOQ approach is used.

The present paper proposes a fuzzy economic order quantity (EOQ) model for deteriorating items with stock dependent demand rate where shortages are not allowed. The cycle time is divided into two parts. The first interval demand is considered as stock dependent and the second part is assumed to be constant. We first develop a crisp model. Since most of the parameters of the inventory model are uncertain, we consider the demand, holding cost, deterioration cost and deterioration rate as triangular fuzzy numbers. Graded mean representation, signed distance method and centroid method are used to defuzzify the total cost function. The results obtained by these methods are compared with the help of a numerical example. Sensitivity analysis is also carried out to explore the effect of changes in the values of the system parameters.

In this chapter we first look at finding solutions to $$ max/min \overline{Y} = f(\overline{X}), $$ where \(\overline{X}\) is a triangular (shaped) fuzzy number in some interval I, f is a fuzzy function mapping fuzzy numbers into fuzzy numbers and \(\overline{Y}\) is also a triangular shaped fuzzy number. As an example of this problem we consider a fuzzy EOQ (economic order quantity) problem to solve. To generate approximate solutions we plan to employ our fuzzy Monte Carlo method.

The COVID-19 pandemic has significantly disrupted global business operations, causing challenges in supply chain management, particularly for perishable and deteriorating items. This study develops an Economic Order Quantity (EOQ) model for non-instantaneous deteriorating products, where demand is dependent on selling price. The model incorporates deterioration costs and salvage value, providing a realistic framework for inventory management during uncertain conditions. To handle uncertainty, triangular intuitionistic fuzzy numbers (TIFNs) is implemented and for defuzzification the centroid method is used. A numerical example validates the model, and sensitivity analysis demonstrates its robustness across various parameters. This model offers valuable insights for optimizing order quantity and minimizing total costs in the context of pandemic-induced disruptions. The primary objective is to optimize overall costs and determine an optimal cycle, order quantity under fuzzy environment.

Diseases such as diabete and cancer must be detected and treated precociouse. They are generally detected using recognition and classification systems. The latter must be choosen according their accuracies and other measures. In addition, some difficulties and ambiguities can exist related with features representing data sets such as their variant types (eg., integer, nominal, etc.) or overlapping between them. Also, data can be imprecise or incomplete and can influence negatively classification results. Fuzzy sets and their generalizations, resolve problems of data uncertainty by modeling them with linguistic variables. The latter are presented with membership functions having different shapes. Triangular fuzzy numbers which represent tringular functions are very rarely used in classification systems. The cause can be that triangular shape does not preserve in case of some calculations. This research proposes to generalize the classification system "‘Amended Fused TOPSIS-VIKOR for classification"’ (ATOVIC) with triangular fuzzy numbers and to apply it to some UCI date sets. The objective is to unveil the impact of triangular fuzzy numbers in classification. The results of generalized fuzzy ATOVIC are compared to those of its crisp version and those of some existing classification systems using fuzzy sets. Results of ATOVIC generalized with tringular fuzzy numbers are promising. Especially its results on breast cancer Wisconsin and IRIS data sets are higher than Mamdani and Segano fuzzy inference systems using triangular fuzzy numbers from literature.

Multi-criterion multi-attribute decision-making for an EOQ model in a hesitant fuzzy environment

CV Jaya Mandiri Motor is a company engaged in the sales and installation services of automotive and building window films, with branches in various cities. CV Jaya Mandiri Motor is an official dealer for various types of window films. Due to the increasing demand for window film installations, it is not uncommon for the CV Jaya Mandiri Motor branch in Kota Metro to experience shortages of window film stock, mainly due to the two-week lead time for ordering window films from the central distributor. Therefore, an optimization of the window film inventory system at the CV Jaya Mandiri Motor branch in Kota Metro is necessary to address the issue of stockouts and maximize the company's profits. In conducting research at the CV Jaya Mandiri Motor branch in Kota Metro, the Economic Order Quantity (EOQ) method is used to determine the most optimal and economical order quantities for each purchasing instance. The research results in the following EOQ values: Heat Protection window film, 98 meters in quantity with a frequency of 3 orders; 3M Black Beauty window film, 171 meters with a frequency of 2 orders; 3M Crystal Line window film, 83 meters with a frequency of 3 orders; Elite/5M window film, 633 meters with a frequency of 1 order; 3D Auto Film window film, 264 meters with a frequency of 2 orders; Black Sun Control window film, 264 meters with a frequency of 1 order; Black Platinum window film, 231 meters with a frequency of 1 order; and Crystal Ice window film, 456 meters with a frequency of 1 order

The inventory problem associated with trade credit is a popular topic in which interest income and interest payments are important issues. Most studies related to trade credit assume that the interest rate is both fixed and predetermined. However, in the real market, many factors such as financial policy, monetary policy and inflation, may affect the interest rate. Moreover, within the environment of merchandise storage, some distinctive factors arise which ultimately affect the quality of products such as temperature, humidity, and storage equipment. Thus, the rate of interest charges, the rate of interest earned, and the deterioration rate in a real inventory problem may be fuzzy. In this paper, we deal with these three imprecise parameters in inventory modeling by utilizing the fuzzy set theory. We develop the fuzzy inventory model based on Chang et al.'s [1] model by fuzzifying the rate of interest charges, the rate of interest earned, and the deterioration rate into the triangular fuzzy number. Subsequently, we discuss how to determine the optimal ordering policy so that the total relevant inventory cost, in the fuzzy sense, is minimal. Furthermore, we show that Chang et al.'s [1] model (the crisp model) is a special case of our model (the fuzzy model). Finally, numerical examples are provided to illustrate these results.

In this paper, we propose a method of solving the fully fuzzy linear fractional programming problems, Express all the parameters and variables are triangular fuzzy numbers. Convert all the triangular fuzzy numbers in their parametric form, we convert the fractional programming problem in to a single objective linear programming problem in parametric form. We put new fuzzy arithmetic and fuzzy ranking, we obtain the optimal solution the given fully fuzzy linear fractional programming problem without converting to its equivalent crisp linear programming problem. A numerical example is provided to illustrate the efficiency of the proposed method.

PurposeThe 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/approachHere, 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.FindingsNumerical experiments indicate that the proposed fuzzy model is practically effective.Originality/valueThe 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.