A MULTI-CHOICE GOAL PROGRAMMING APPROACH FOR COTS PRODUCTS SELECTION OF MODULAR SOFTWARE SYSTEMS

2013 ◽  
Vol 20 (06) ◽  
pp. 1350026 ◽  
Author(s):  
MUKESH KUMAR MEHLAWAT
Keyword(s):  
Goal Programming ◽  
Execution Time ◽  
Selection Problem ◽  
Software Systems ◽  
Programming Approach ◽  
Delivery Time ◽  
Modular Software ◽  
Proposed Model ◽  
Aspiration Levels ◽  
Cots Products

In this paper, we propose a multi-choice goal programming (MCGP) model of the multi-objective commercial-off-the-shelf (COTS) products selection problem. The proposed model simultaneously minimize the total cost, size, execution time and delivery time and maximize the system reliability of a modular software system subject to many realistic constraints including incompatibility among COTS products. We assume that the decision maker provides multiple aspiration levels regarding cost, size, execution time, delivery time and reliability objectives using discrete choices. To obtain efficient COTS selection plans, we use MCGP methodology to solve the COTS products selection problem. A real-world case study is discussed to demonstrate the effectiveness of the proposed model and methodology.

A FUZZY APPROACH TO MULTIOBJECTIVE COTS PRODUCTS SELECTION OF MODULAR SOFTWARE SYSTEMS USING EXPONENTIAL MEMBERSHIP FUNCTIONS

2014 ◽  
Vol 21 (01) ◽  
pp. 1450005 ◽  
Author(s):  
MUKESH KUMAR MEHLAWAT
Keyword(s):  
Optimization Model ◽  
Execution Time ◽  
Measurement Errors ◽  
Critical Parameters ◽  
Software System ◽  
Membership Functions ◽  
Delivery Time ◽  
Modular Software ◽  
Cots Products ◽  
Selection Of

In this paper, we study a decision-making problem related to software creation using commercial-off-the-shelf (COTS) products in a modular software system. The optimal selection of COTS products is difficult due to the variations in various critical parameters such as cost, reliability, execution time, and delivery time. Further, it is difficult to estimate precisely the values of these parameters since sufficient data may not be available and also there could be measurement errors. We present a fuzzy 0–1 optimization model of the multiobjective COTS products selection problem using exponential membership functions that simultaneously minimize the total cost, size, execution time and delivery time and maximize the reliability of a modular software system subject to many realistic constraints. The fuzzy goals are defined for each selection criterion as per the preferences of the decision maker and are aggregated using product operator to obtain an equivalent optimization model for optimal COTS selection. A real-world case study is discussed to demonstrate the effectiveness of the proposed model and the solution methodology.

A fuzzy goal programming approach for selecting sustainable suppliers

2017 ◽  
Vol 24 (5) ◽  
pp. 1138-1165 ◽  
Author(s):  
Peeyush Pandey ◽  
Bhavin J. Shah ◽  
Hasmukh Gajjar
Keyword(s):  
Goal Programming ◽  
Supplier Selection ◽  
Qualitative Data ◽  
Fuzzy Goal Programming ◽  
Programming Approach ◽  
Two Phase ◽  
Content Type ◽  
Lean Practices ◽  
Proposed Model ◽  
Fuzzy Goal

Purpose Due to the ever increasing concern toward sustainability, suppliers nowadays are evaluated on the basis of environmental performances. The data on supplier’s performance are not always available in quantitative form and evaluating supplier on the basis of qualitative data is a challenging task. The purpose of this paper is to develop a framework for the selection of suppliers by evaluating them on the basis of both quantitative and qualitative data. Design/methodology/approach Literature on sustainability, green supply chain and lean practices related to supplier selection is critically reviewed. Based on this, a two phase fuzzy goal programming approach integrating hyperbolic membership function is proposed to solve the complex supplier selection problem. Findings Results obtained through the proposed approach are compared to the traditional models (Jadidi et al., 2014; Ozkok and Tiryaki, 2011; Zimmermann, 1978) of supplier selection and were found to be optimal as it achieves higher aspiration level. Practical implications The proposed model is adaptive to solve real world problems of supplier selection as all criteria do not possess the same weights, so the managers can change the criteria and their weights according to their requirement. Originality/value This paper provides the decision makers a robust framework to evaluate and select sustainable supplier based on both quantitative and qualitative data. The results obtained through the proposed model achieve greater satisfaction level as compared to those achieved by traditional methods.

scholarly journals The LR-Type Fuzzy Multi-Objective Vendor Selection Problem in Supply Chain Management

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1621
Author(s):  
Irfan Ali ◽  
Armin Fügenschuh ◽  
Srikant Gupta ◽  
Umar Muhammad Modibbo
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Real Life ◽  
Selection Problem ◽  
Programming Approach ◽  
Vendor Selection ◽  
Chain Management ◽  
Multi Objective ◽  
Fuzzy Environment ◽  
Proposed Model

Vendor selection is an established problem in supply chain management. It is regarded as a strategic resource by manufacturers, which must be managed efficiently. Any inappropriate selection of the vendors may lead to severe issues in the supply chain network. Hence, the desire to develop a model that minimizes the combination of transportation, deliveries, and ordering costs under uncertainty situation. In this paper, a multi-objective vendor selection problem under fuzzy environment is solved using a fuzzy goal programming approach. The vendor selection problem was modeled as a multi-objective problem, including three primary objectives of minimizing the transportation cost; the late deliveries; and the net ordering cost subject to constraints related to aggregate demand; vendor capacity; budget allocation; purchasing value; vendors’ quota; and quantity rejected. The proposed model input parameters are considered to be LR fuzzy numbers. The effectiveness of the model is illustrated with simulated data using R statistical package based on a real-life case study which was analyzed using LINGO 16.0 optimization software. The decision on the vendor’s quota allocation and selection under different degree of vagueness in the information was provided. The proposed model can address realistic vendor selection problem in the fuzzy environment and can serve as a useful tool for multi-criteria decision-making in supply chain management.

scholarly journals A Fuzzy Goal Programming Approach for Solving Multi-Objective Supply Chain Network Problems with Pareto-Distributed Random Variables

2019 ◽  
Vol 27 (04) ◽  
pp. 559-593 ◽  
Author(s):  
Vincent Charles ◽  
Srikant Gupta ◽  
Irfan Ali
Keyword(s):  
Supply Chain ◽  
Goal Programming ◽  
Fuzzy Goal Programming ◽  
Programming Approach ◽  
Supply Chain Network ◽  
Delivery Time ◽  
Demand And Supply ◽  
Multi Objective ◽  
Weighted Goal Programming ◽  
Fuzzy Goal

Uncertainty is unavoidable and addressing the same is inevitable. That everything is available at our doorstep is due to a well-managed modern global supply chain, which takes place despite its efficiency and effectiveness being threatened by various sources of uncertainty originating from the demand side, supply side, manufacturing process, and planning and control systems. This paper addresses the demand- and supply-rooted uncertainty. In order to cope with uncertainty within the constrained multi-objective supply chain network, this paper develops a fuzzy goal programming methodology, with solution procedures. The probabilistic fuzzy goal multi-objective supply chain network (PFG-MOSCN) problem is thus formulated and then solved by three different approaches, namely, simple additive goal programming approach, weighted goal programming approach, and pre-emptive goal programming approach, to obtain the optimal solution. The proposed work links fuzziness in transportation cost and delivery time with randomness in demand and supply parameters. The results may prove to be important for operational managers in manufacturing units, interested in optimizing transportation costs and delivery time, and implicitly, in optimizing profits. A numerical example is provided to illustrate the proposed model.

A GOAL PROGRAMMING APPROACH TO FUZZY LINEAR REGRESSION WITH NON-FUZZY INPUT AND FUZZY OUTPUT DATA

2009 ◽  
Vol 26 (05) ◽  
pp. 587-604 ◽  
Author(s):  
H. HASSANPOUR ◽  
H. R. MALEKI ◽  
M. A. YAGHOOBI
Keyword(s):  
Linear Regression ◽  
Goal Programming ◽  
Programming Approach ◽  
Simulation Studies ◽  
Fuzzy Linear Regression ◽  
Output Data ◽  
The Past ◽  
Proposed Model ◽  
Fuzzy Input ◽  
Fuzzy Linear Regression Model

Many researches have been carried out in fuzzy linear regression since the past three decades. In this paper, a fuzzy linear regression model based on goal programming is proposed. The proposed model takes into account the centers of fuzzy data as an important feature as well as their spreads. Furthermore, the model can deal with both symmetric and non-symmetric data. To show the efficiency of proposed model, it is compared with some earlier methods based on simulation studies and numerical examples. Moreover, the sensitivity of the model to outliers is discussed.

scholarly journals Goal Programming Approach for Selection of COTS Components in Designing a Fault Tolerant Modular Software System under Consensus Recovery Block Scheme

2014 ◽  
pp. 65-72
Author(s):  
P. C. Jha ◽  
Vikram Bali
Keyword(s):  
Goal Programming ◽  
Software Reliability ◽  
Fault Tolerant ◽  
Random Variable ◽  
Chance Constraint ◽  
Programming Approach ◽  
Software System ◽  
Modular Software ◽  
Goal Programming Model ◽  
Commercial Off The Shelf

The application of computer systems has now crossed many different fields. Systems are becoming more software intensive. The requirements of the customer for a more reliable software led to the fact that software reliability is now an important research area. One method to improve software reliability is by the application of redundancy. A careful use of redundancy may allow the system to tolerate faults generated during software design and coding thus improving software reliability. The fault tolerant software systems are usually developed by integrating COTS (commercial off-the-shelf) software components. This paper is designed to select optimal components for a fault tolerant modular software system so as to maximize the overall reliability of the system with simultaneously minimizing the overall cost. A chance constrained goal programming model has been designed after considering the parameters corresponding to reliability and cost of the components as random variable. The random variable in this case has been considered as value which has known mean and standard deviation. A chance constraint goal programming technique is used to solve the model. The issue of compatibility among different commercial off-the shelf alternatives is also considered in the paper. Numerical illustrations are provided to demonstrate the model.

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