Analysis on Random Fuzzy Queueing Systems with Finite Capacity

This paper discusses random fuzzy queueing systems with finite capacity, where the interarrival times and service times are characterized as random fuzzy variables. Fuzzy simulation techniques are designed to estimate the membership degree, the expected value of system length, and the credibility measure that the system length does not exceed a predetermined level. Furthermore, the rough figures of the membership function and credibility distribution function of the system length can be obtained. Finally, an example is given to illustrate the effectiveness of the presented techniques

Approximate Common Knowledge Based on Uncertain Measure

This paper studies that how an uncertain event can be outlined as an approximate common knowledge. By replacing “know” with “know with certainty α” in standard definitions of common knowledge, approximate common knowledge with some certainty, defined iteratively and mutually, iteratively known and mutually known with some certainty, are explored. Examples are constructed to show that an event which is not common knowledge can be analyzed as an approximate common knowledge with some certainty. An application in the principal-agent model is investigated to show that approximate common knowledge based on uncertain measure can be applied to improve the behavior of an economic model

A Birandom Job Search Problem with Risk Tolerance

This paper considers a novel class of birandom job search problem, in which the job offers are sampled by the job searcher from a finite job set with equivalent probability and their wages are characterized as independent but maybe not identically nonnegative random variables. The job searcher knows the job offer's wage distribution when he samples the job offer. Since the offered wage is a random variable and the reservation wage is a deterministic number, it is meaningless to make comparison directly. In order to rank the random wage and the reservation wage and provide decision support, a risk tolerance criterion is designed, and the job searcher then accepts or rejects the sampled job offer depending on whether the risk tolerance criterion is met or not. Since the offered wages are random variables and the search process is random, it's impossible to obtain the job searcher's real return; in this case, its expected value can be calculated via birandom theory. Simultaneously, some propositions on the expected return as well as the average search times are also studied which may provide some valuable suggestions to the job searcher. Numerical examples are given to illustrate the decision process of the risk tolerance-based birandom job search problem