scholarly journals Multiple Objective Fuzzy Sourcing Problem with Multiple Items in Discount Environments

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Feyzan Arikan
Keyword(s):  
Vital Role ◽  
Mixed Integer ◽  
Multiple Objective ◽  
Total Production ◽  
Integer Linear Programming Problem ◽  
Aspiration Levels ◽  
Multiple Item ◽  
Promising Solution ◽  
Nondominated Solution ◽  
Selection Of

The selection of proper supply sources plays a vital role to maintain companies’ competitiveness. In this study a multiple criteria fuzzy sourcing problem with multiple items in discount environment is considered as a multiple objective mixed integer linear programming problem. Fuzzy parameters are demand level and/or aspiration levels of objectives. Three objective functions are minimization of the total production and ordering costs, the total number of rejected units, and the total number of late delivered units, respectively. The model is developed for the all-units discount scheme. For the incremental discount and volume discount environment, modification requirements of the model are mentioned. The previously proposed interactive fuzzy approach combined with three fuzzy mathematical models is employed to obtain most satisfactory solution which is also a nondominated one. This study provides a realistic mathematical model and promising solution strategy to multiple item-single period sourcing problem in discount environment. Consideration of fuzziness makes the obtained nondominated solution implementable for the real cases.

A Method for Generating a Well-Distributed Pareto Set in Multiple Objective Mixed Integer Linear Programs Based on the Decision Maker’s Initial Aspiration Level

2016 ◽  
Vol 33 (04) ◽  
pp. 1650031
Author(s):  
S. Razavyan
Keyword(s):  
Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Mixed Integer ◽  
Multiple Objective ◽  
Pareto Optimal ◽  
Aspiration Level ◽  
Integer Linear Programming Problem ◽  
Pareto Optimal Set ◽  
Optimal Set ◽  
The Ideal

This paper attempt to generate a representative subset of the Pareto optimal set for multiple objective mixed integer linear programming problem using the weighted L1 norm distance. The procedure presented in this paper is somewhat similar to the one used in the ideal-point methods and its aim is to generate at each iteration the closest-points to the ideal vector corresponding to the decision maker’s initial aspiration level for a new tradeoff parameter. Unlike most of the known algorithms for generating a discrete representation of the Pareto optimal set, the procedure generates at each iteration a nondominated point by solving only one mixed integer linear programming problem. The obtained solution minimizes the weighted L1 norm distance to the ideal vector with respect to the distance between the ideal vector and previously found vectors. More generally, this approach is able to generate all Pareto optimal solutions, where all of the decision variables are restricted to be integer. In order to explain the presented details, several illustrative examples are provided.

Energy Efficiency Analysis in ERA using NFL-BA Algorithm

2020 ◽  
pp. 340-348
Author(s):  
Palky Mehta ◽  
H. L. Sharma
Keyword(s):  
Cluster Head ◽  
Vital Role ◽  
Wireless Sensor ◽  
Energy Usage ◽  
Cluster Heads ◽  
Comparison Results ◽  
Current Scenario ◽  
Energy Efficiency Analysis ◽  
Selection Of

In the current scenario of Wireless Sensor Network (WSN), power consumption is the major issue associated with nodes in WSN. LEACH technique plays a vital role of clustering in WSN and reduces the energy usage effectively. But LEACH has its own limitation in order to search cluster head nodes which are randomly distributed over the network. In this paper, ERA-NFL- BA algorithm is being proposed for selects the cluster heads in WSN. This algorithm help in selection of cluster heads can freely transform from global search to local search. At the end, a comparison has been done with earlier researcher using protocol ERA-NFL, which clearly shown that proposed Algorithm is best suited and from comparison results that ERA-NFL-BA has given better performance.

scholarly journals Optimising the selection of food items for FFQs using Mixed Integer Linear Programming

2014 ◽  
Vol 18 (1) ◽  
pp. 68-74 ◽  
Author(s):  
Johanna C Gerdessen ◽  
Olga W Souverein ◽  
Pieter van ‘t Veer ◽  
Jeanne HM de Vries
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Selection Process ◽  
Saturated Fat ◽  
Mixed Integer ◽  
Monounsaturated Fat ◽  
Food Items ◽  
Milp Model ◽  
Selection Of

AbstractObjectiveTo support the selection of food items for FFQs in such a way that the amount of information on all relevant nutrients is maximised while the food list is as short as possible.DesignSelection of the most informative food items to be included in FFQs was modelled as a Mixed Integer Linear Programming (MILP) model. The methodology was demonstrated for an FFQ with interest in energy, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, total carbohydrates, mono- and disaccharides, dietary fibre and potassium.ResultsThe food lists generated by the MILP model have good performance in terms of length, coverage and R2 (explained variance) of all nutrients. MILP-generated food lists were 32–40 % shorter than a benchmark food list, whereas their quality in terms of R2 was similar to that of the benchmark.ConclusionsThe results suggest that the MILP model makes the selection process faster, more standardised and transparent, and is especially helpful in coping with multiple nutrients. The complexity of the method does not increase with increasing number of nutrients. The generated food lists appear either shorter or provide more information than a food list generated without the MILP model.

A Least Cost Transmission Planning Model Considering Operation Cost

2014 ◽  
Vol 15 (2) ◽  
pp. 121-128
Author(s):  
Jorge Hans Alayo
Keyword(s):  
Test System ◽  
Mixed Integer ◽  
Transmission Planning ◽  
Integer Linear Programming Problem ◽  
Transmission Expansion ◽  
Planning Models ◽  
Proposed Model ◽  
Expansion Model ◽  
Operation Cost ◽  
Linearization Techniques

Abstract Existing transmission planning models consider basic aspects of the problem. In practice, a transmission utility needs to model other important details such as operation cost of the power system. In this article, a least cost transmission expansion model is proposed considering the operation cost in order to model the trade-off between building new transmission capacity and increasing the power system’s operation cost. The proposed model is transformed into a mixed integer linear programming problem using linearization techniques and solved with CPLEX. Finally, results of the model for the Garver test system and IEEE 24-bus test system are shown.

scholarly journals Students’ Perception and Attitudes toward Faculty Image on Social Networks

2021 ◽  
pp. 63-74
Author(s):  
Milena Vukić ◽  
Snežana Milićević ◽  
Ksenija Vukić
Keyword(s):  
Social Networks ◽  
Social Media ◽  
New Technology ◽  
Common Source ◽  
Positive Perception ◽  
Promotion Strategy ◽  
Promising Solution ◽  
And Gender ◽  
Source Of Information ◽  
Selection Of

Purpose of this paper is to determine how students perceive the image of their faculty on social networks, but also to analyse their experience and attitudes towards faculty social media strategy. The research was implemented using descriptive statistic techniques, as well as non-parametric tests such as Mann-Whitney U Test, Kruskal-Wallis H Test and Spearman’s Rho. The most common source of information when it comes to enrolment to faculty is word of mouth, while social media have a signifi-cantly lower credibility. During their schooling the respondents have most confidence in the official website, and far less in social networks. Such findings signalize the necessity of creating an adequate digital marketing strategy that can significantly improve the perceived faculty image. Positive perception of the image is fundamental for understanding the process of searching for and selection of the faculty, especially since the results have shown that the students do not value highly the image their faculties have on social networks. Positive perception of faculty image mostly depends on promotion strategy on Facebook and Insta-gram, and far less on LinkedIn and Twitter. In addition, students value more the image of the faculty whose social network pro-file they follow and, in a case, when they are followed back. No correlation was found between faculty image and gender, age or average grade. Therefore, we can conclude that social networks are very important in creating positive image and thanks to new technology, they are a promising solution for differentiation from competition in digital space.

Optimal Sizing of a Gas Turbine Cogeneration Plant in Consideration of Its Operational Strategy

1994 ◽  
Vol 116 (1) ◽  
pp. 32-38 ◽  
Author(s):  
R. Yokoyama ◽  
K. Ito ◽  
Y. Matsumoto
Keyword(s):  
Programming Problem ◽  
Gas Turbine ◽  
Mixed Integer ◽  
Turbine Plant ◽  
Operational Strategies ◽  
Integer Linear Programming Problem ◽  
Energy Demands ◽  
Annual Total ◽  
Planning Problems ◽  
Annual Total Cost

An optimal planning method is proposed for the fundamental design of cogeneration plants. Equipment capacities and utility maximum demands are determined so as to minimize the annual total cost in consideration of the plants’ annual operational strategies for the variations of both electricity and thermal energy demands. These sizing and operational planning problems are formulated as a nonlinear programming problem and a mixed-integer linear programming problem, respectively. They are solved efficiently in consideration of their hierarchical relationship by a penalty method. A numerical example about a gas turbine plant is given to ascertain the validity and effectiveness of the proposed method.

Scale elasticity in the presence of integer data: An application to electricity distribution companies

2021 ◽  
Vol 39 (2) ◽  
Author(s):  
Homeira Amirmohammadi ◽  
Alireza Amir Amirteimoori ◽  
Sohrab Kordrostami ◽  
Mohsen Vaez-Ghasemi
Keyword(s):  
Operations Research ◽  
Returns To Scale ◽  
Mixed Integer ◽  
Data Envelopment ◽  
Electricity Distribution ◽  
Scale Elasticity ◽  
Frontier Point ◽  
Integer Linear Programming Problem ◽  
Lagrangian Dual ◽  
Scale Properties

Returns to scale and scale elasticity are two important issues in the field of economics and operations research. Recently, estimating returns to scale and scale elasticity using tools such as data envelopment analysis (DEA) has attracted considerable attention among researchers. The existing approaches to calculate scale elasticity in DEA context, assume all inputs and outputs are real-valued and in this sense, the underlying technology is a continuous set. In many real cases, however, we face input/output measures that are restricted to be integer-valued. Scale properties of frontier points in such cases are interesting and important. In this paper, this problem in integer-valued DEA is studied. The Lagrangian dual formulation of a mixed integer linear programming problem is used to calculate the scale elasticity of a frontier point. To illustrate the real applicability of the theoretical framework, a real case on electricity distribution companies is given.

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