A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment

The purpose of this paper is to design a new extension of the ELECTRE, known as the elimination and choice translating reality method, for multi-criteria group decision-making problems based on intuitionistic fuzzy sets. This method is widely utilized when a set of alternatives should be identified and evaluated with respect to a set of conflicting criteria by reflecting decision makers’ (DMs’) preferences. However, handling the exact data and numerical measure is difficult to be precisely focused because the DMs’ judgments are often vague in real-life decision problems and applications. A more realistic and practical approach can be to use linguistic variables expressed in intuitionistic fuzzy numbers instead of numerical data to model DMs’ judgments and to describe the inputs in the ELECTRE method. The proposed intuitionsitic fuzzy ELECTRE utilizes the truth-membership function and non-truth-membership function to indicate the degrees of satisfiability and non-satisfiability of each alternative with respect to each criterion and the relative importance of each criterion, respectively. Then, a new discordance intuitionistic index is introduced, which is extended from the concept of the fuzzy distance measure. Outranking relations are defined by pairwise comparisons and a decision graph is depicted to determine which alternative is preferable, incomparable or indifferent in the intuitionistic fuzzy environment. Finally, a comprehensive sensitivity analysis is employed to further study regarding the impact of threshold values on the final evaluation, and a comparative analysis is demonstrated with an application example in flexible manufacturing systems between the proposed ELECTRE method and the existing intuitionistic fuzzy technique for order preference by similarity to ideal solution (IF-TOPSIS) method.     

On the numerical feasibility of continuation methods for nonlinear programming problems

In the present paper the radius of convergence of a class of locally convergent nonlinear programming algorithms (containing Robinson's and Wilson's methods) applied to a parametric nonlinear programming problem is estimated. A consequence is the numerical feasibility of globalizations of Robinson's and Wilson's methods by means of continuation techniques.     

基于演化博弈的公共交通、共享汽车与私家车的博弈分析

出行者的选择行为分析是交通系统中的一项重要内容,随着城市的发展,交通出行方式大体分为三大类:公共交通出行、辅助公共交通出行和私人交通出行。本文在以往的研究基础上,采用演化博弈的方法研究公共交通、共享汽车以及私家车三者之间的博弈关系,模拟出行者的选择行为,分析博弈均衡点稳定性及参数条件。通过模型仿真实验,演化结果中各项比例大小取决于各项收益、补贴、损失以及额外收益,要增加公共交通的配套设施,增收拥堵费以及增加对共享汽车的补贴及配套服务。     

甲型H1N1流感的死亡率高吗——Bayes计量分析框架下的建模与估算

在全球甲型H1N1流感大流行背景下,本文在充分考虑各国甲流感死亡率可能存在个体混合效应、独立效应、相关效应及空间相关效应基础上,运用Bayes计量分析框架下的模型选择标准确定描述各国甲流感死亡率的最优模型,并基于该模型对不同国家甲流感死亡率进行估算。结果显示:个体独立、空间相关效应模型能很好拟合各国甲流感疫情统计数据,利用该模型估算的全球甲流感平均死亡率为0.577%。     

Stigmergy in comparative settlement choice and palaeoenvironment simulation

Decisions on settlement location in the face of climate change and coastal inundation may have resulted in success, survival or even catastrophic failure for early settlers in many parts of the world. In this study, we investigate various questions related to how individuals respond to a palaeoenvironmental simulation, on an interactive tabletop device where participants have the opportunity to build a settlement on a coastal landscape, balancing safety, and access to resources, including sea and terrestrial foodstuffs, while taking into consideration the threat of rising sea levels. The results of the study were analyzed to consider whether decisions on settlement were predicated to be near to locations where previous structures were located, stigmergically, and whether later settler choice would fare better, and score higher, as time progressed. The proximity of settlements was investigated and the reasons for clustering were considered. The interactive simulation was exhibited to thousands of visitors at the 2012 Royal Society Summer Science Exhibition at the “Europe's Lost World” exhibit. 347 participants contributed to the simulation, providing a sufficiently large sample of data for analysis. © 2014 Wiley Periodicals, Inc. Complexity 21: 59–73, 2016     

Mathematical models for job-shop scheduling problems with routing and process plan flexibility

As a result of rapid developments in production technologies in recent years, flexible job-shop scheduling problems have become increasingly significant. This paper deals with two NP-hard optimization problems: flexible job-shop scheduling problems (FJSPs) that encompass routing and sequencing sub-problems, and the FJSPs with process plan flexibility (FJSP-PPFs) that additionally include the process plan selection sub-problem. The study is carried out in two steps. In the first step, a mixed-integer linear programming model (MILP-1) is developed for FJSPs and compared to an alternative model in the literature (Model F) in terms of computational efficiency. In the second step, one other mixed-integer linear programming model, a modification of MILP-1, for the FJSP-PPFs is presented along with its computational results on hypothetically generated test problems.     

A practical weight sensitivity algorithm for goal and multiple objective programming

This paper presents a weight sensitivity algorithm that can be used to investigate a portion of weight space of interest to the decision maker in a goal or multiple objective programme. The preferential information required from the decision maker is an initial estimate of their starting solution, with an equal weights solution being used as a default if this is not available, and preference information that will define the portion of weight space on which the sensitivity analysis is to be conducted. The different types of preferential information and how they are incorporated by the algorithm are discussed. The output of the algorithm is a set of distinct solutions that characterise the portion of weight space searched. The possible different output requirements of decision makers are detailed in the context of the algorithm.The methodology is demonstrated on two examples, one hypothetical and the other relating to predicting cinema-going behaviour. Conclusions and avenues for future research are given.     

Solving the Huff-Based Competitive Location Model on a Network with Link-Based Demand

This paper shows a computational method for optimizing the location of a store on a network in a competitive environment, assuming that consumers probabilistically choose stores following the Huff model (1963) and that the store can be located on a continuum of a network. This method gives the exact optimal solution with the computational order of n _N ² logn _N where n _N is the number of nodes of the network.