scholarly journals Optimal Decisions for Prepositioning Emergency Supplies Problem with Type-2 Fuzzy Variables

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Xuejie Bai
Keyword(s):  
Value At Risk ◽  
Fuzzy Variable ◽  
General Purpose ◽  
Mixed Integer ◽  
Fuzzy Variables ◽  
Logistics Network ◽  
Disaster Relief Operations ◽  
Proposed Model ◽  
Relief Operations

Prepositioning emergency supplies serves an important function in disaster relief operations. This paper presents a new class of fuzzy prepositioning emergency supplies model for three-echelon humanitarian logistics network, in which the postdisaster acquisition and transportation costs, the suppliers’ supply, and affected areas’ demand are uncertain and characterized by type-2 fuzzy variables with known possibility distributions. Since the inherent complexity of fuzzy prepositioning problem may be troublesome, the existing methods are no longer effective in dealing with the proposed model directly. We first derive the optimistic and pessimistic values formula for credibility value-at-risk (CVaR) reduced fuzzy variable of type-2 trapezoidal fuzzy variable. On the basis of formula obtained, we can convert original fuzzy prepositioning model into its equivalent parametric mixed integer programming form, which can be solved by conventional algorithms or general-purpose software. Finally, some numerical experiments have been performed to illustrate the effectiveness of the proposed model and solution strategy.

scholarly journals Minimum Risk Facility Location-Allocation Problem with Type-2 Fuzzy Variables

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Xuejie Bai ◽  
Ying Liu
Keyword(s):  
Facility Location ◽  
Value At Risk ◽  
Structural Characteristics ◽  
Fuzzy Variable ◽  
Mixed Integer ◽  
Minimum Risk ◽  
Fuzzy Variables ◽  
Location Allocation ◽  
The Impact

Facility location decision is basically viewed as a long-term strategy, so the inherited uncertainty of main parameters ought to be taken into account in order to make models applicable. In this paper, we examine the impact of uncertain transportation costs and customers’ demands on the choice of optimal location decisions and allocation plans. This leads to the formulation of the facility location-allocation (FLA) problem as a fuzzy minimum risk programming, in which the uncertain parameters are assumed to be characterized by type-2 fuzzy variables with known type-2 possibility distributions. Since the inherent complexity of type-2 fuzzy FLA may be troublesome, existing methods are no longer effective in handling the proposed problems directly. We first derive the critical value formula for possibility value-at-risk reduced fuzzy variable of type-2 triangular fuzzy variable. On the basis of formula obtained, we can convert original fuzzy FLA model into its equivalent parametric mixed integer programming form, which can be solved by conventional numerical algorithms or general-purpose software. Taking use of structural characteristics of the equivalent optimization, we design a parameter decomposition method. Finally, a numerical example is presented to highlight the significance of the fuzzy FLA model. The computational results show the credibility and superiority of the proposed parametric optimization method.

scholarly journals Type-2 Duality Triangular Fuzzy Fractional Transportation Problem using Goal Programming Technique

2020 ◽  
Vol 8 (6) ◽  
pp. 1295-1302
Keyword(s):  
Goal Programming ◽  
Transportation Problem ◽  
Fuzzy Numbers ◽  
Programming Technique ◽  
Intuitionistic Fuzzy Numbers ◽  
Fuzzy Variables ◽  
Proposed Model ◽  
Fuzzy Parameters ◽  
Interval Valued

The authors focused goal programming technique for solving type-2 duality fuzzy fractional transportation problem by using interval-valued triangular intuitionistic fuzzy numbers. The proposed method solves three types of models in which variables are taken as type-2 fuzzy variables which have spring up to the fuzzy fractional transportation problem. In these models, duality is applied and a particular type of non-linear membership functions are used to resolve duality fractional transportation problem including fuzzy parameters. A numerical example for examining the performance of the proposed model is envisaged here.

scholarly journals Modeling Portfolio Optimization Problem by Probability-Credibility Equilibrium Risk Criterion

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Ye Wang ◽  
Yanju Chen ◽  
YanKui Liu
Keyword(s):  
Convex Programming ◽  
Portfolio Selection ◽  
Optimization Problem ◽  
Fuzzy Variable ◽  
Optimization Method ◽  
General Purpose ◽  
Convex Programming Problem ◽  
Fuzzy Variables ◽  
Return Rates ◽  
Fuzzy Expected Value

This paper studies the portfolio selection problem in hybrid uncertain decision systems. Firstly the return rates are characterized by random fuzzy variables. The objective is to maximize the total expected return rate. For a random fuzzy variable, this paper defines a new equilibrium risk value (ERV) with credibility level beta and probability level alpha. As a result, our portfolio problem is built as a new random fuzzy expected value (EV) model subject to ERV constraint, which is referred to as EV-ERV model. Under mild assumptions, the proposed EV-ERV model is a convex programming problem. Furthermore, when the possibility distributions are triangular, trapezoidal, and normal, the EV-ERV model can be transformed into its equivalent deterministic convex programming models, which can be solved by general purpose optimization software. To demonstrate the effectiveness of the proposed equilibrium optimization method, some numerical experiments are conducted. The computational results and comparison study demonstrate that the developed equilibrium optimization method is effective to model portfolio selection optimization problem with twofold uncertain return rates.

scholarly journals Arithmetic Operations and Expected Values of Regular Interval Type-2 Fuzzy Variables

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2196
Author(s):  
Hui Li ◽  
Junyang Cai
Keyword(s):  
Fuzzy Variable ◽  
Fuzzy Arithmetic ◽  
Computation Complexity ◽  
Arithmetic Operations ◽  
Fuzzy Variables ◽  
Expected Value Operator ◽  
Interval Type ◽  
High Degree ◽  
Mutually Independent

High computation complexity restricts the application prospects of the interval type-2 fuzzy variable (IT2-FV), despite its high degree of freedom in representing uncertainty. Thus, this paper studies the fuzzy operations for the regular symmetric triangular IT2-FVs (RSTIT2-FVs)—the simplest IT2-FVs having the greatest membership degrees of 1. Firstly, by defining the medium of an RSTIT2-FV, its membership function, credibility distribution, and inverse distribution are analytically and explicitly expressed. Secondly, an operational law for fuzzy arithmetic operations regarding mutually independent RSTIT2-FVs is proposed, which can simplify the calculations and directly output the inverse credibility of the functions. Afterwards, the operational law is applied to define the expected value operator of the IT2-FV and prove the linearity of the operator. Finally, some comparative examples are provided to verify the efficiency of the proposed operational law.

Optimization of Biomass-to-Bioenergy Logistics Network Design Problem: A Case Study

2018 ◽  
Vol 16 (11) ◽  
Author(s):  
Meisam Shamsi ◽  
Reza Babazadeh ◽  
Maghsud Solimanpur
Keyword(s):  
Network Design ◽  
Design Problem ◽  
Fossil Fuels ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Efficient Design ◽  
Logistics Network ◽  
Sustainable Solutions ◽  
Proposed Model ◽  
And Performance

Abstract Increasing the emissions of greenhouse gases (GHG) due to fossil fuel consumption has led to problems such as global warming, climate change, loss of biodiversity, and urban pollutions. Bioethanol production especially from different biomass such as wheat straw has been specified as one of the sustainable solutions to deal with energy crisis. Bioethanol logistics network optimization will reduce total costs of supply chain management and improves its competency with fossil fuels. In this paper, a mixed-integer linear programming (MILP) model is proposed to integrate and optimize bioethanol logistics network design problem. The proposed model is a multi-period and multi-echelon including feedstock supply centers, collection centers, bio-refineries, and customer centers. The proposed model is applied in a real case in Iran. The results justify the applicability and performance of the model in efficient design of bioethanol logistics network problems.

scholarly journals An Incremental-Hybrid-Yager’s Entropy Model for Dynamic Portfolio Selection with Fuzzy Variable

2018 ◽  
Vol 2018 ◽  
pp. 1-15
Author(s):  
Yin Li ◽  
Jian Tao ◽  
Yazhi Song
Keyword(s):  
Markov Chain ◽  
Asset Price ◽  
Fuzzy Variable ◽  
Time Interval ◽  
Entropy Model ◽  
Fuzzy Variables ◽  
Proposed Model ◽  
Dynamic Portfolio ◽  
The Relationship ◽  
Mean Variance

To settle down the resolutional uncertainty in optimum portfolio strategy, this paper addresses an incremental-hybrid-Yager’s entropy model to newly describe the relationship between return and risk. Different from the traditional multiperiod portfolio, we design the ratio threshold to divide asset price into different time interval and use state instead of time point to model the dynamic portfolio process. In addition, fuzzy variables are utilized to represent prices of assets, while historical data based on Markov chain is exploited to estimate membership functions of fuzzy prices. At last, a compromised genetic algorithm is designed, and the numerical example shows that the proposed model achieves solid returns compared against the mean-variance model and Markov chain Monte Carlo method.

A multi-objective emergency network design problem to carry out disaster relief operations in developing countries

2019 ◽  
Vol 9 (2) ◽  
pp. 250-269 ◽  
Author(s):  
Mohsen Babaei ◽  
Afshin Shariat-Mohaymany ◽  
Nariman Nikoo ◽  
Ahmad-Reza Ghaffari
Keyword(s):  
Developing Countries ◽  
Disaster Relief ◽  
Transportation Network ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Content Type ◽  
Multi Objective ◽  
Total Length ◽  
Disaster Relief Operations ◽  
Relief Operations

Purpose One of the problems in post-earthquake disaster management in developing countries, such as Iran, is the prediction of the residual network available for disaster relief operations. Therefore, it is important to use methods that are executable in such countries given the limited amount of accurate data. The purpose of this paper is to present a multi-objective model that seeks to determine the set of roads of a transportation network that should preserve its role in carrying out disaster relief operations (i.e. known as “emergency road network” (ERN)) in the aftermath of earthquakes. Design/methodology/approach In this paper, the total travel time of emergency trips, the total length of network and the provision of coverage to the emergency demand/supply points have been incorporated as three important metrics of ERN into a multi-objective mixed integer linear programming model. The proposed model has been solved by adopting the e-constraint method. Findings The results of applying the model to Tehran’s highway network indicated that the least possible length for the emergency transportation network is about half the total length of its major roads (freeways and major arterials). Practical implications Gathering detailed data about origin-destination pair of emergency trips and network characteristics have a direct effect on designing a suitable emergency network in pre-disaster phase. Originality/value To become solvable in a reasonable time, especially in large-scale cases, the problem has been modeled based on a decomposing technique. The model has been solved successfully for the emergency roads of Tehran within about 10 min of CPU time.

Modeling pricing decision problem based on interval type-2 fuzzy theory

2021 ◽  
pp. 1-16
Author(s):  
Huili Pei ◽  
Hongliang Li ◽  
Yankui Liu
Keyword(s):  
Decision Making ◽  
Level Sets ◽  
Fuzzy Variable ◽  
Possibility Distribution ◽  
Fuzzy Variables ◽  
Pricing Decision ◽  
Selection Variable ◽  
Interval Type ◽  
Analytical Expressions

In practical decision-making problems, decision makers are often affected by uncertain parameters because the exact distributions of uncertain parameters are usually difficult to determine. In order to deal with this issue, the major contribution in this paper is to propose a new type of type-2 fuzzy variable called level interval type-2 fuzzy variable from the perspective of level-sets, which is a useful tool in modeling distribution uncertainty. With our level interval type-2 fuzzy variable, we give a method for constructing a parametric level interval (PLI) type-2 fuzzy variable from a nominal possibility distribution by introducing the horizontal perturbation parameters. The proposed horizontal perturbation around the nominal distribution is different from the vertical perturbation discussed in the literature. In order to facilitate the modeling in practical decision-making problems, for a level interval type-2 fuzzy variable, we define its selection variable whose distribution can be determined via its level-sets. The numerical characteristics like expected value and second order moments are important indices in practical optimization and decision-making problems. With this consideration, we establish the analytical expressions about the expected values and second order moments of the selection variables of PLI type-2 trapezoidal, normal and log-normal fuzzy variables. Furthermore, in order to derive the analytical expressions about the numerical characteristics of the selection variable for the sums of the common PLI type-2 fuzzy variables, we discuss the arithmetic about the sums of common PLI type-2 fuzzy variables. Finally, we apply the proposed optimization method to a pricing decision problem to demonstrate the efficiency of our new method. The computational results show that even a small perturbation of the nominal possibility distribution can affect the quality of solutions.

China’s response to the 2014–2016 Ebola crisis: Enhancing Africa’s soft security under Sino-US competition

2020 ◽  
pp. 0920203X2097854
Author(s):  
Jean-Pierre Cabestan
Keyword(s):  
Humanitarian Assistance ◽  
Medical Sciences ◽  
Health Security ◽  
Public Health Emergencies ◽  
Strategic Competition ◽  
International Response ◽  
Disaster Relief Operations ◽  
Relief Operations ◽  
Set Up ◽  
Military Teams

The 2014–16 Ebola crisis in West Africa was China’s very first opportunity to demonstrate its willingness and ability to play a meaningful role in addressing public health emergencies of international concern. China’s decision to participate in the international response to the outbreak was part of an ambition to enhance its contribution to Africa’s security in general and health security in particular and to exert more influence on global norms. The specific role played by the People’s Liberation Army (PLA), especially its Academy of Military Medical Sciences, in Sierra Leone and Liberia is part of an ongoing effort to increase China’s involvement in international humanitarian assistance and disaster relief operations. It was the first time that it sent medical military teams to set up and operate infectious disease hospitals overseas. This participation also underscores the PLA’s crucial role in fighting epidemics overseas as well as at home, as the current COVID-19 pandemic illustrates. The Ebola crisis enables us to explore aspects of the PLA’s overseas missions, some of which are humanitarian and others which generally enhance China’s influence as a great power in Africa and in the world in the context of a growing Sino-US strategic competition.

Sign in / Sign up

Export Citation Format

Share Document