scholarly journals Interval-Valued Fuzzy Cooperative Games Based on the Least Square Excess and Its Application to the Profit Allocation of the Road Freight Coalition

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 709 ◽  
Author(s):  
Wen-Jian Zhao ◽  
Jia-Cai Liu
Keyword(s):  
Analytical Solution ◽  
Cooperative Games ◽  
Programming Model ◽  
Solution Concept ◽  
Least Square ◽  
Real Situation ◽  
The Road ◽  
Profit Allocation ◽  
Road Freight ◽  
Interval Valued

This paper is mainly committed to constructing a new model for solving interval-valued fuzzy cooperative games based on the least square excess. We propose the interval-valued least square excess solution according to the solution concept of the least square prenucleolus and the least square nucleolus for solving crisp cooperative games. In order to obtain the corresponding optimal analytical solution, one mathematic programming model is constructed. The least square excess solution can be used to determine plays’ payoffs directly. Considering the fuzziness and uncertainty existing in the process of the road freight coalition, we establish the interval-valued fuzzy utility function of the road freight coalition that can properly reflect the real situation in view of the green logistics. The illustratively calculated results show that the least square excess solution proposed in this paper is effectual and ascendant, and satisfied many important and useful properties of cooperative games, such as symmetry and uniqueness. As for the problems of interval-valued cooperative games, the model proposed in this paper can be applied appropriately to obtain the players’ interval-valued payoffs.

scholarly journals Quadratic Programming Method for Cooperative Games with Coalition Values Expressed by Triangular Fuzzy Numbers and Its Application in the Profit Distribution of Logistics Coalition

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Jia-Cai Liu ◽  
Yuan-Fei Zhu ◽  
Wen-Jian Zhao
Keyword(s):  
Quadratic Programming ◽  
Fuzzy Set ◽  
Cooperative Games ◽  
Fuzzy Numbers ◽  
Programming Model ◽  
Least Square ◽  
Triangular Fuzzy Numbers ◽  
Profit Distribution ◽  
Cut Set ◽  
Quadratic Programming Method

A quadratic programming model is constructed for solving the fuzzy cooperative games with coalition values expressed by triangular fuzzy numbers, which will be abbreviated to TFN-typed cooperative games from now on. Based on the concept of α-cut set and the representation theorem for the fuzzy set, the least square distance solution for solving TFN-typed cooperative games is proposed. The least square distance solution successfully avoids the subtraction operation of TFNs, which may inevitably lead to the amplification of uncertainty and the distortion of decision information. A calculating example related to the profit distribution of logistics coalition is illustrated to show the advantages, validity, and applicability of the proposed method. Besides, the least square distance solution for solving TFN-typed cooperative games satisfies many important properties of cooperative games, such as uniqueness, additivity, symmetry, and uniqueness.

The least square pre-nucleolus for interval cooperative games based on anti-symmetric interval excess values

2020 ◽  
Vol 39 (3) ◽  
pp. 3561-3575
Author(s):  
Jian Lin ◽  
Meiling Li ◽  
Chunsheng Cui ◽  
Zhiyong Tian
Keyword(s):  
Quadratic Programming ◽  
Lagrange Multiplier ◽  
Pollution Control ◽  
Cooperative Games ◽  
Programming Model ◽  
Least Square ◽  
Cardinal Characteristics ◽  
Excess Value ◽  
Analytic Expression ◽  
Single Objective

Considering both cardinal characteristics and double powers, the anti-symmetric interval excess value is defined. The least square pre-nucleolus for interval cooperative games is presented by making a single-objective programming model. We obtain the analytic expression of least square pre-nucleolus using Lagrange multiplier method, and construct an effective quadratic programming model to derive the least square pre-nucleolus of incomplete interval cooperative games. In addition, the application of least square pre-nucleolus in land pollution control is provided to show the validity of the proposed solution concepts.

scholarly journals How Will Digitalization Change Road Freight Transport? Scenarios Tested in Sweden

2020 ◽  
Vol 13 (1) ◽  
pp. 304
Author(s):  
Anna Pernestål ◽  
Albin Engholm ◽  
Marie Bemler ◽  
Gyözö Gidofalvi
Keyword(s):  
Freight Transport ◽  
Sustainable Transportation ◽  
Transport Sector ◽  
Strategic Uncertainty ◽  
Scenario Development ◽  
Service Levels ◽  
Urban Freight ◽  
The Road ◽  
Road Freight ◽  
On The Road

Road freight transport is a key function of modern societies. At the same time, road freight transport accounts for significant emissions. Digitalization, including automation, digitized information, and artificial intelligence, provide opportunities to improve efficiency, reduce costs, and increase service levels in road freight transport. Digitalization may also radically change the business ecosystem in the sector. In this paper, the question, “How will digitalization change the road freight transport landscape?” is addressed by developing four exploratory future scenarios, using Sweden as a case study. The results are based on input from 52 experts. For each of the four scenarios, the impacts on the road freight transport sector are investigated, and opportunities and barriers to achieving a sustainable transportation system in each of the scenarios are discussed. In all scenarios, an increase in vehicle kilometers traveled is predicted, and in three of the four scenarios, significant increases in recycling and urban freight flows are predicted. The scenario development process highlighted how there are important uncertainties in the development of the society that will be highly important for the development of the digitized freight transport landscape. One example is the sustainability paradigm, which was identified as a strategic uncertainty.

scholarly journals An Effective Joint Soft-Sensing Strategy for Multi-Information under Diverse Vehicle Driving Scenarios

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 505
Author(s):  
Jianfeng Chen ◽  
Jiantian Sun ◽  
Shulin Hu ◽  
Yicai Ye ◽  
Haoqian Huang ◽  
...  
Keyword(s):  
Time Delay ◽  
Fast Response ◽  
Least Square ◽  
Accurate Information ◽  
Recursive Least Square ◽  
Soft Sensing ◽  
The Road ◽  
Vehicle Mass ◽  
Cubature Kalman Filter ◽  
Road Slope

A variety of accurate information inputs are of great importance for automotive control. In this paper, a novel joint soft-sensing strategy is proposed to obtain multi-information under diverse vehicle driving scenarios. This strategy is realized by an information interaction including three modules: vehicle state estimation, road slope observer and vehicle mass determination. In the first module, a variational Bayesian-based adaptive cubature Kalman filter is employed to estimate the vehicle states with the time-variant noise interference. Under the assumption of road continuity, a slope prediction model is proposed to reduce the time delay of the road slope observation. Meanwhile, a fast response nonlinear cubic observer is introduced to design the road slope module. On the basis of the vehicle states and road slope information, the vehicle mass is determined by a forgetting-factor recursive least square algorithm. In the experiments, a contrasted strategy is introduced to analyse and evaluate performance. Results declare that the proposed strategy is effective and has the advantages of low time delay, high accuracy and good stability.

scholarly journals Interval-Valued Probabilistic Hesitant Fuzzy Set Based Muirhead Mean for Multi-Attribute Group Decision-Making

Mathematics ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 342 ◽  
Author(s):  
Krishankumar ◽  
Ravichandran ◽  
Ahmed ◽  
Kar ◽  
Peng
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Set ◽  
Group Decision ◽  
Partial Information ◽  
Programming Model ◽  
Hesitant Fuzzy Set ◽  
Occurrence Probability ◽  
Source Selection ◽  
Interval Valued

As a powerful generalization to fuzzy set, hesitant fuzzy set (HFS) was introduced, which provided multiple possible membership values to be associated with a specific instance. But HFS did not consider occurrence probability values, and to circumvent the issue, probabilistic HFS (PHFS) was introduced, which associates an occurrence probability value with each hesitant fuzzy element (HFE). Providing such a precise probability value is an open challenge and as a generalization to PHFS, interval-valued PHFS (IVPHFS) was proposed. IVPHFS provided flexibility to decision makers (DMs) by associating a range of values as an occurrence probability for each HFE. To enrich the usefulness of IVPHFS in multi-attribute group decision-making (MAGDM), in this paper, we extend the Muirhead mean (MM) operator to IVPHFS for aggregating preferences. The MM operator is a generalized operator that can effectively capture the interrelationship between multiple attributes. Some properties of the proposed operator are also discussed. Then, a new programming model is proposed for calculating the weights of attributes using DMs’ partial information. Later, a systematic procedure is presented for MAGDM with the proposed operator and the practical use of the operator is demonstrated by using a renewable energy source selection problem. Finally, the strengths and weaknesses of the proposal are discussed in comparison with other methods.

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