Multiple Objective Decision Making — Methods and Applications

Hwang, Ching-Lai; Masud, Abu S. M.

doi:10.1007/978-3-642-45511-7

Cited by 1,340 publications

(878 citation statements)

References 49 publications

Supporting

Mentioning

806

Contrasting

Unclassified

Order By: Relevance

“…PIS maximises the benefit criteria and minimises the cost criteria, while NIS maximises the cost criteria and minimises the benefit criteria (). The fundamental principle is that the chosen alternative should have the shortest distance from the PIS and the farthest distance from the NIS ( The TOPSIS methodology presented by (Hwang & Yoon, 1981) consists of the following steps:…”

Section: Topsis Methods (Technique For Order Performance By Similaritymentioning

confidence: 99%

An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies

Knežević

Mandić

Mitrović

et al. 2017

mng

View full text Add to dashboard Cite

The aim of this paper is to apply an integrated model, which combines methods of classical and fuzzy Multi-criteria decision making (MCDM) in selected six large equity companies from the Serbian energy sector. The data considered are retrieved from the official financial statements. Four main criteria were analyzed, identified by the previous researchers and pointing to the employees’ productivity: Operating income/Number of employees, Equity/Number of employees, Net income/Number of employees and Total assets/Number of employees. The contribution of this paper lies in the application of a hybrid model that integrates two MCDM methods: Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to analyse the employee productivity in selected D-Electrical power supply companies operating in Serbia. The FAHP is an effective method for mathematical representation of uncertain and imprecise evaluations made by humans, while the TOPSIS method is an efficient way to rank the alternatives. Results show that operating income is of highest importance for estimating employee productivity and decision making, while equity is of the weakest. Furthermore, the most productive operations in large enterprises from selected companies of the sector D-Electrical power supply are found in the company PC EPS Beograd, and the lowest are in the ED Center llc Kragujevac.

show abstract

Section: Topsis Methods (Technique For Order Performance By Similaritymentioning

confidence: 99%

An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies

Knežević

Mandić

Mitrović

et al. 2017

mng

View full text Add to dashboard Cite

show abstract

“…TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) was first proposed by C.L. Hwang and K.Yoon in 1981.The basic idea is to establish an initial decision matrix first, and then find out the optimal solution and the worst solution in the limited solution based on the normalized initial matrix, that is, positive and negative ideal solutions, and then calculate each evaluation object and the optimal solution The distance from the worst case approach leads to a solution that is as close to positive as possible, while keeping as far as possible from negative ones [14].The method is reasonable and easy to understand, and the calculation is relatively simple. The method can be used to describe the performance of alternative solutions in a simple mathematical form and objective weights can be used in the comparison process [15].…”

Section: Basic Conceptmentioning

confidence: 99%

Fuzzy Soft Set Multi-Attribute Decision Making Method Based on TOPSIS with Improved Entropy Weight

Liu¹,

Liu²

2018

Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

View full text Add to dashboard Cite

Abstract. In the process of fuzzy soft set multi-attribute decision making, and It is difficult to determine the weight of the attribute parameters which results in low efficiency of decision making. Therefore, a new method of determining the entropy weight which is calculated by the notion of the importance degree and the deviation degree based on parameters, moreover entropy weight is used to determine the objective weight of attribute parameters. The dynamic weight determination method is proposed to determine the combined weight which combines the subjective weight and the objective weight, then combined with the traditional TOPSIS method, this paper proposes the method of fuzzy soft set multi-attribute decision making based on TOPSIS with improved entropy weight. Finally, a practical example has been analyzed to verify the feasibility and effectiveness of the approach, which can realize the dynamic decision making according to the demand of decision making and improve the efficiency of decision making.

show abstract

“…In the displacement problem, this means that a solution may solve some or all graphic conflicts in some parts of the map, but not in other parts. Hwang and Masud [27] illustrated the notion of a non-dominated solution or Pareto solution for optimality problems. A non-dominated solution is one in which no one objective function can be improved without simultaneously degrading to at least one of the other objectives.…”

Section: The Pareto Optimal Solutionmentioning

confidence: 99%

Reducing Building Conflicts in Map Generalization with an Improved PSO Algorithm

Huang

Qingsheng

Sun³

et al. 2017

IJGI

View full text Add to dashboard Cite

Abstract:In map generalization, road symbolization and map scale reduction may create spatial conflicts between roads and neighboring buildings. To resolve these conflicts, cartographers often displace the buildings. However, because such displacement sometimes produces secondary spatial conflicts, it is necessary to solve the spatial conflicts iteratively. In this paper, we apply the immune genetic algorithm (IGA) and improved particle swarm optimization (PSO) to building displacement to solve conflicts. The dual-inheritance framework from the cultural algorithm is adopted in the PSO algorithm to optimize the topologic structure of particles. We generate Pareto optimal displacement solutions using the niche Pareto competition mechanism. The results of experiments comparing IGA and the improved PSO show that the improved PSO outperforms IGA; the improved PSO results in fewer graphic conflicts and smaller movements that better satisfy the movement precision requirements.

show abstract

Multiple Objective Decision Making — Methods and Applications

Cited by 1,340 publications

References 49 publications

An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies

An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies

Fuzzy Soft Set Multi-Attribute Decision Making Method Based on TOPSIS with Improved Entropy Weight

Reducing Building Conflicts in Map Generalization with an Improved PSO Algorithm

Contact Info

Product

Resources

About