A MEMBERSHIP FUNCTION APPROACH FOR COST-RELIABILITY TRADE-OFF OF COTS SELECTION IN FUZZY ENVIRONMENT

2011 ◽  
Vol 18 (06) ◽  
pp. 573-595 ◽  
Author(s):  
PANKAJ GUPTA ◽  
SHILPI VERMA ◽  
MUKESH KUMAR MEHLAWAT
Keyword(s):  
Real World ◽  
Fuzzy Optimization ◽  
Delivery Time ◽  
Minimum Threshold ◽  
Trade Off ◽  
Total Cost ◽  
Fuzzy Environment ◽  
Proposed Model ◽  
The Cost ◽  
Cots Selection

The optimization techniques used in commercial-off-the-shelf (COTS) selection process faces challenges to deal with uncertainty in many important selection parameters, for example, cost, reliability and delivery time. In this paper, we propose a fuzzy optimization model for selecting the best COTS product among the available alternatives for each module in the development of modular software systems. The proposed model minimizes the total cost of the software system satisfying the constraints of minimum threshold on system reliability, maximum threshold on the delivery time of the software, and incompatibility among COTS products. In order to deal with uncertainty in real-world applications of COTS selection, the coefficients of the cost objective function, delivery time constraints and minimum threshold on reliability are considered fuzzy numbers. The fuzzy optimization model is converted into a pair of mathematical programming problems parameterized by possibility (feasibility) level α using Zadeh's extension principle. The solutions of the resultant problems at different α-cuts provide lower and upper bounds of the fuzzy minimum total cost which helps in constructing the membership function of the cost objective function. The solution approach provide fuzzy solutions instead of a single crisp solution thereby giving decision maker enough flexibility in maintaining cost-reliability trade-off of COTS selection besides meeting other important system requirements. A real-world case study is discussed to demonstrate the effectiveness of the proposed model in fuzzy environment.

scholarly journals Budgeted Optimization with Constrained Experiments

2016 ◽  
Vol 56 ◽  
pp. 119-152 ◽  
Author(s):  
Javad Azimi ◽  
Xiaoli Fern ◽  
Alan Fern
Keyword(s):  
Real World ◽  
Unknown Function ◽  
Optimization Problem ◽  
Experimental Results ◽  
Trade Off ◽  
Input Space ◽  
Real World Problem ◽  
Real Functions ◽  
The Cost

Motivated by a real-world problem, we study a novel budgeted optimization problem where the goal is to optimize an unknown function f(.) given a budget by requesting a sequence of samples from the function. In our setting, however, evaluating the function at precisely specified points is not practically possible due to prohibitive costs. Instead, we can only request constrained experiments. A constrained experiment, denoted by Q, specifies a subset of the input space for the experimenter to sample the function from. The outcome of Q includes a sampled experiment x, and its function output f(x). Importantly, as the constraints of Q become looser, the cost of fulfilling the request decreases, but the uncertainty about the location x increases. Our goal is to manage this trade-off by selecting a set of constrained experiments that best optimize f(.) within the budget. We study this problem in two different settings, the non-sequential (or batch) setting where a set of constrained experiments is selected at once, and the sequential setting where experiments are selected one at a time. We evaluate our proposed methods for both settings using synthetic and real functions. The experimental results demonstrate the efficacy of the proposed methods.

MODELING AND SIMULATION OF THE PRODUCTION OF HYDROGEN USING HYDROELECTRICITY IN VENEZUELA

2018 ◽  
pp. 88-95 ◽  
Author(s):  
A. Contrerasa ◽  
F. Possob ◽  
Т. N. Veziroglu
Keyword(s):  
Mathematical Model ◽  
Hydrogen Production ◽  
Modeling And Simulation ◽  
Regression Models ◽  
Low Cost ◽  
Total Cost ◽  
Time Horizons ◽  
Proposed Model ◽  
Production Of Hydrogen ◽  
The Cost

The purpose of this work is to develop and evaluate a mathematical model for the process of hydrogen production in Venezuela, via electrolysis and using hydroelectricity, with a view to using it as an energy vector in rural sectors of the country. Regression models were prepared to estimate the fluctuation of the main variables involved in the process: the production of hydrogen, the efficiency of energy conversion, the cost of hydroelectricity and the cost of the electrolyser. Finally, the proposed model was applied to various different time-horizons and populations, obtaining the cost of hydrogen production in each case. The results obtained are well below those mentioned in the references, owing largely to the low cost of the electricity used, which accounts for around 45% of the total cost of the system.

Capitated pricing model for stroke thrombectomies: a single center experience across three companies

2020 ◽  
pp. neurintsurg-2020-016160 ◽  
Author(s):  
Kavit Shah ◽  
Merritt Brown ◽  
Shashvat M Desai ◽  
Tudor G Jovin ◽  
Ashutosh P Jadhav ◽  
...  
Keyword(s):  
Real World ◽  
Mechanical Thrombectomy ◽  
Cost Savings ◽  
Pricing Model ◽  
Single Center ◽  
Pricing Models ◽  
Healthcare Expenditures ◽  
Total Cost ◽  
Single Center Experience ◽  
The Cost

BackgroundWith a continued rise in healthcare expenditures, there is a demonstrable focus on curbing expenses. Mechanical thrombectomy (MT) is the standard of treatment for large vessel occlusions (LVOs); however, considerable costs are associated with devices utilized in each procedure. We report our institution’s experience with capitation pricing models negotiated with three different companies.MethodsWe retrospectively reviewed a prospectively maintained database from February 2018 to August 2019 identifying cases performed under capitation models. We calculated the cost of equipment for each thrombectomy using the cost for individual devices utilized (virtual) and compared this sum to the total derived from cost-negotiated bundled equipment packages. This was compared with real-world cases that did not meet capitation criteria during this study period.Results107 cases met the criteria for capitation; 39 cases used company A’s models (28 with stentrievers), 44 cases used company B’s models (3 with stentrievers), and 24 cases used company C’s models (14 with stentrievers). Overall, there was a net savings of $202 370.50 utilizing the capitated model ($689 435 vs $891 805.50), amounting to $1891.31 savings per case. Mean capitation was lower ($6972±2774) compared with virtual ($8794±4614) and real-world non-capitation costs ($7176±3672).ConclusionThe negotiated capitated pricing model yielded total cost savings associated with equipment from each company. Overall mean capitation costs were lower than virtual and real-world cases. This may serve as a model for other centers in controlling costs for patients undergoing MT for LVO.

scholarly journals Finding Your Way: Shortest Paths on Networks

2021 ◽  
Vol 9 ◽  
Author(s):  
Teresa Rexin ◽  
Mason A. Porter
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Real World ◽  
Major Part ◽  
Shortest Paths ◽  
Travel Distance ◽  
Daily Lives ◽  
Total Cost ◽  
The Real ◽  
The Cost

Traveling to different destinations is a major part of our lives. We visit a variety of locations both during our daily lives and when we are on vacation. How can we find the best way to navigate from one place to another? Perhaps we can test all of the different ways of traveling between two places, but another method is to use mathematics and computation to find a shortest path between them. In this article, we discuss how to construct shortest paths and introduce Dijkstra’s algorithm to minimize the total cost of a path, where the cost may be the travel distance, the travel time, or some other quantity. We also discuss how to use shortest paths in the real world to save time and increase traveling efficiency.

scholarly journals An Improved Fuzzy Classification System for Financial Credit Decision using Multi-Objective Evolutionary Optimization

2019 ◽  
Vol 8 (6) ◽  
pp. 4982-4990
Keyword(s):  
Classification System ◽  
Optimal Solution ◽  
Fuzzy Classification ◽  
Credit Allocation ◽  
Trade Off ◽  
Multi Objective ◽  
Proposed Model ◽  
Financial Credit ◽  
Fuzzy Classification System ◽  
The Cost

In fuzzy classification system, accuracy has been gained at the cost of interpretability and vice versa. This situation is known as Interpretability-Accuracy Trade-off. To handle this trade-off between accuracy and interpretability the evolutionary algorithms (EAs) are often used to optimize the performance of the fuzzy classification system. From the last two decades, several multi-objective evolutionary systems have been designed and successfully implemented in several fields for finding multiple solutions at a single run. In Financial Decision making concerning Credit Allocation, Classification is a significant component to obtain credit scores and predict bankruptcy. A fuzzy classification system for the financial credit decision has been designed and find out the Accuracy and Interpretability parameters for applying various MOEAs to get the pareto optimal solution resulting in to improvement in the performance of the proposed system. The proposed model implemented on standard benchmark financial credit allocation datasets i.e., German Credit Approval system available from the UCI repository of machine learning databases (http://archive.ics.uci.edu/ml) and using the open source tool MOEA framework (http://www.moeaframework.org). The experimental analysis highlights that the NSGA-III works efficiently for financial credit approval system and improves the performance by making a balanced trade-off between accuracy and interpretability.

scholarly journals Finding Your Way: Shortest Paths on Networks

2020 ◽  
Author(s):  
Teresa Rexin ◽  
Mason A. Porter
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Real World ◽  
Shortest Paths ◽  
Travel Distance ◽  
Dijkstra’S Algorithm ◽  
Total Cost ◽  
The Real ◽  
Dijkstra's Algorithm ◽  
The Cost

Traveling to different destinations is a big part of our lives. How do we know the best way to navigate from one place to another? Perhaps we could test all of the different ways of traveling between two places, but another method is using mathematics and computation to find a shortest path. We discuss how to find a shortest path and introduce Dijkstra’s algorithm to minimize the total cost of a path, where the cost may be the travel distance or travel time. We also discuss how shortest paths can be used in the real world to save time and increase traveling efficiency.

Campaign Optimization through Mobility Network Analysis

2015 ◽  
pp. 33-75 ◽  
Author(s):  
Yaniv Altshuler ◽  
Erez Shmueli ◽  
Guy Zyskind ◽  
Oren Lederman ◽  
Nuria Oliver ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Network Analysis ◽  
Real World ◽  
Service Provision ◽  
Political Campaigns ◽  
Mobility Data ◽  
Proposed Model ◽  
Geographical Regions ◽  
Marketing Service ◽  
The Cost

Optimizing the use of available resources is one of the key challenges in activities that consist of interactions with a large number of “target individuals”, with the ultimate goal of affecting as many of them as possible, such as in marketing, service provision and political campaigns. Typically, the cost of interactions is monotonically increasing such that a method for maximizing the performance of these campaigns is required. This chapter proposes a mathematical model to compute an optimized campaign by automatically determining the number of interacting units and their type, and how they should be allocated to different geographical regions in order to maximize the campaign's performance. The proposed model is validated using real world mobility data.

scholarly journals Routing cross-docking depots, considering the time windows and pricing routes (case study: container transportation of Chabahar port)

2020 ◽  
Vol 33 (02) ◽  
pp. 409-422
Author(s):  
Farhad Bavar ◽  
Majid Sabzehparvar ◽  
Mona Ahmadi Rad
Keyword(s):  
High Efficiency ◽  
Programming Model ◽  
Time Windows ◽  
Container Transportation ◽  
Total Cost ◽  
Cross Docking ◽  
Proposed Model ◽  
Nonlinear Programming Model ◽  
Implementation Time ◽  
The Cost

In this study, we develop a model for routing cross-docking centers considering time windows and pricing routs. In this model picking and delivery in several times is permitted and each knot can be serviced by more than one vehicle. Every truck can transport one or more product, in other words, we consider compatibility between product and vehicle. This model includes two goals: reducing the total cost and reducing the cost of carrying goods (freight fare). The total cost includes the cost required to traverse between the points, the cost of traversing the routes between the central cross-docking center and the first points after moving, and the cost to traverse the routes between the last points in each route and the depots that must be minimized. In general, the purpose of the model is to obtain the number of cross-docking center, the number of vehicles and the best route in the distribution network. We present a nonlinear programming model for this problem. We have solved the proposed model by GAMS. As the dimensions of the problem increase, the implementation time of the program increases progressively. So, in order to solve the model in medium and large scales, we proposed a genetic meta-heuristic algorithm. The results of examining different issues by the meta-heuristic approach show the very high efficiency of the developed algorithms in terms of the solution time and the answer of the problem.

scholarly journals Neutrosophic Triangular Fuzzy Travelling Salesman Problem Based on Dhouib-Matrix-TSP1 Heuristic

2021 ◽  
Vol 10 (5) ◽  
Author(s):  
Souhail Dhouib
Keyword(s):  
Real World ◽  
Fuzzy Number ◽  
Travelling Salesman Problem ◽  
Numerical Test ◽  
Optimal Solution ◽  
Triangular Fuzzy Number ◽  
Travelling Salesman ◽  
Total Cost ◽  
Fuzzy Environment ◽  
Neutrosophic Number

In this paper, the Travelling Salesman Problem is considered in neutrosophic environment which is more realistic in real-world industries. In fact, the distances between cities in the Travelling Salesman Problem are presented as neutrosophic triangular fuzzy number. This problem is solved in two steps: At first, the Yager’s ranking function is applied to convert the neutrosophic triangular fuzzy number to neutrosophic number then to generate the crisp number. At second, the heuristic Dhouib-Matrix-TSP1 is used to solve this problem. A numerical test example on neutrosophic triangular fuzzy environment shows that, by the use of Dhouib-Matrix-TSP1 heuristic, the optimal or a near optimal solution as well as the crisp and fuzzy total cost can be reached.

Achieving an optimal global versus domestic sourcing balance under demand uncertainty

2004 ◽  
Vol 24 (12) ◽  
pp. 1292-1305 ◽  
Author(s):  
Byoungho Jin
Keyword(s):  
Demand Uncertainty ◽  
Ideal Point ◽  
Production Costs ◽  
Global Sourcing ◽  
Delivery Time ◽  
Mixed Strategies ◽  
Total Cost ◽  
The Cost ◽  
The Ideal

As manufacturers face demand uncertainty and new retailing practices, such as filling frequent, small replenishment orders, agility has become an important competitive tool. By sourcing globally, manufacturing firms can reduce production costs, but may not be agile enough to meet retailers' needs on a timely basis. To minimize the cost/agility trade‐off, many firms are combining global and domestic sourcing. However, factors to be considered for mixed strategies have not been suggested. Based on Bucklin's concepts of postponement and speculation, this study tried to find the ideal point, “I”, at which the optimal amount of global and domestic sourcing can be formulated considering the total cost and delivery time simultaneously. In mixing domestic and global sourcing to reach the optimum profit, this study provided four conditions under which the larger portion of domestic sourcing can be formulated: greater level of demand uncertainly, information and manufacturing technology, local subcontractor clusters, and long‐term relationship with a subcontractor.

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