Component-based software system (CBSS) development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.

This study presents optimization of performance characteristics in unidirectional glass fiber reinforced plastic composites using Taguchi method and Grey relational analysis. Performance characteristics such as surface roughness and material removal rate are optimized during rough cutting operation. Process parameters including tool nose radius, tool rake angle, feed rate, cutting speed, cutting environment and depth of cut are investigated using mixed L18 orthogonal array. Grey relation analysis is used to optimize the parameters and Principal Component Analysis is used to find the relative significance of performance characteristics. Depth of cut is the factor, which has great influence on surface roughness and material removal rate, followed by feed rate. The percentage contribution of depth of cut is 54.399% and feed rate is 5.355%.

An important function of the project management is to optimize the project in various phases and at different levels. From sourcing and allocation to scheduling and even dealing with uncertainties, the science of operation research (OR) has played an important role in this area. So far, many papers have been published using the optimization science to make various decisions regarding the project management. This study aims to investigate all papers published on the application of optimization in the project management from 1940 to 2019 and shows: a) how the trend has changed over this 79 years period, b) to what direction the trend has changed, c) determines the interesting topics of the recent years, and d) which subjects are more attractive as future studies as the applications of the optimization techniques in the project management.

This paper deals with the development of an inventory model for time varying demand and constant demand; and time dependent holding cost and constant holding cost for case 1 and case 2 respectively. Previous models incorporating that the holding cost is constant for the entire inventory cycle. Mathematical model has been developed for determining the optimal order quantity, the optimal cycle time and optimal total inventory cost for both cases. Differential calculus is used for finding optimal solution. Numerical examples are given for both cases to validate the proposed model. Sensitivity analysis is carried out to analyze the effect of changes in the optimal solution with respect to change in various parameters.

Ultrasonic machining (USM) process has multiple performance measures, e.g. material removal rate (MRR), tool wear rate (TWR), surface roughness (SR) etc., which are affected by several process parameters. The researchers commonly attempted to optimize USM process with respect to individual responses, separately. In the recent past, several systematic procedures for dealing with the multi-response optimization problems have been proposed in the literature. Although most of these methods use complex mathematics or statistics, there are some simple methods, which can be comprehended and implemented by the engineers to optimize the multiple responses of USM processes. However, the relative optimization performance of these approaches is unknown because the effectiveness of different methods has been demonstrated using different sets of process data. In this paper, the computational requirements for four simple methods are presented, and two sets of past experimental data on USM processes are analysed using these methods. The relative performances of these methods are then compared. The results show that weighted signal-to-noise (WSN) ratio method and utility theory (UT) method usually give better overall optimisation performance for the USM process than the other approaches.

We study the question of how to ideally divide total profits among supply chain members, especially in a stochastic demand market. The Shapley value is used as the methodology solution to divide profits in a supply chain. To illustrate the Shapley value solution and procedures, a two-echelon supply chain consisting of one supplier and two heterogeneous retailers is examined. The goal is to figure out ideal transfer prices for products delivered among supply chain members. These transfer prices will achieve the suggested profit allocations among three companies.

Loading and unloading operations for Stock Keeping Units (SKUs) in warehouses are critical to logistics management systems. However, these operations also have a significant impact on the environment, particularly in terms of carbon dioxide (CO2) emissions. As such, warehouse management must consider not only operational efficiency but also environmental impact. The reduction of CO2 emissions in warehouses is becoming increasingly important, both for legal compliance and to meet sustainability targets. In this article, we will emphasize the environmental impact of warehouse operations, particularly on CO2 emissions, and explore ways to minimize them while still maximizing warehouse performance. We will review various optimization models proposed to address this issue and highlight the importance of considering environmental objectives when designing warehouse operations. We will also describe a simulation study conducted to determine the Pareto optimal frontier for a warehouse design, considering transportation, space utilization, and CO2 emissions. The outcomes of implementing this simulation's results include reduced CO2 emissions and increased space utilization, which demonstrate the potential benefits of considering environmental objectives in warehouse design and management.

The present study focused on the Taguchi experimental design technique of Friction Stir Welds of dissimilar aluminum alloys (AA2024-T6 and AA6351-T6) for tensile properties. Effect of process parameters, rotational speed, Traverse speed and axial force, on tensile strength was evaluated. Optimized welding conditions for maximize tensile strength were estimated in order to improve the productivity, weld quality. Non-linear regression mathematical model was developed to correlate the process parameters to tensile strength. The results were verified by conducting the confirmation tests at identified optimum conditions.

Effects of climate change can already be observed in many regions of the world. The basin of the Paraná River, in South America, has been suffering an important drought since 2019 in the whole region. The extension of the crisis has increased the risks in the flora and fauna, losses in logistics of navigation, besides the problems of urban water cleansing. In this regard, the novel proposal presents a new mathematical model to study the impact of this crisis. Besides the traditional constraints of the literature for hydraulic systems, this paper enhances inventory constraints, connections with electric systems, and other considerations as the head effects in electricity generation. Because several equations related to electricity generation are nonlinear (which the subsequent computational effort impacts), this proposal applies linearization techniques to reduce CPU times. The core is related to hydropower production, and the consequences of the water crisis in the regional markets. The mathematical model analyzes the interrelationships between reservoirs and water flows of the basin. To study the effectiveness of the novel proposal, the reported situation of the basin of the Paraná River is studied by considering two scenarios (normal conditions of the river flow and the conditions related to the drought). Results show that the crisis implies daily net economic losses of about 7 million USD for the operators of the power plants. Other problems (different from the ones related to the energy field) are also mentioned and analyzed.

Evaluating the capability of electrospinning method as an efficient versatile approach for fabrication of fibers, a central composite design (CCD) model was used to design an experimental program for investigation of effective in production of poly (vinyl alcohol) (PVA) fibers fabricated from aqueous solutions of PVA. The studied variables were polymer solution concentration, applied voltage, distance between nozzle and collector plate and flow rate of solution injection. The influence of these parameters on diameter and morphology of obtained PVA fibers was studied by SEM analysis. Among all factors, concentration would strongly affect the fiber diameter.