ANALYSIS AND COMPUTATIONAL ALGORITHM FOR QUEUES WITH STATE-DEPENDENT VACATIONS II： M（n）/G/1/K

We study a single-server queueing system with state-dependent arrivals and general service distribution, or simply M（n）/G/1/K, where the server follows an N policy and takes multiple vacations when the system is empty. We provide a recursive algorithm using the supplementary variable technique to numerically compute the stationary queue length distribution of the system. The only input requirements are the Laplace-Stieltjes transforms of the service time distribution and the vacation time distribution, and the state-dependent arrival rate. The computational complexity of the algorithm is O（K^3）.     

ANALYSIS AND COMPUTATIONAL ALGORITHM FOR QUEUES WITH STATE-DEPENDENT VACATIONS I： G/M（n）/1/K

In this paper we study a queueing system with state-dependent services and state-dependent vacations, or simply G/M（n）/1/K. Since the service rate is state-dependent, this system includes G/M/c and G/M/c/K queues with various types of station vacations as special cases. We provide a recursive algorithm using the supplementary variable technique to numerically compute the stationary queue length distribution of the system. The only input requirement is the Laplace-Stieltjes transform of the interarrival distribution as well as the state-dependent service rate and state-dependent vacation rate. In a subsequent companion paper, we study its dual system M（n）/G/1/K queue with statedependent vacations.     

Optimization of Additively Decomposed Function with Constraints

We propose a modified evolutionary computation method to solve the optimization problem of additively decomposed function with constraints, ft is based on factorized distribution instead of penalty function and any transformation to a linear model or others. The feasibility and convergence of the new algorithm are given. The numerical results show that the new algorithm gives a satisfactory performance.     

OPTIMAL CONTROL OF AN M/G/1 RETRIAL QUEUE WITH VACATIONS

In this note, we consider an M/G/1 retrial queue with server vacations, when retrial times, service times and vacation times are arbitrary distributed. The distribution of the number of customers in the system in stationary regime is obtained in terms of generating function. Next, we give heavy traffic approximation of such distribution. We show that the system size can be decomposed into two random variables, one of which corresponds to the system size of the ordinary M/G/1 FIFO queue without vacation. Such a stochastic decomposition property is useful for the computation of performance measures of interest. Finally, we solve simple problems of optimal control of vacation and retrial policies.     

A perishable inventory system with service facilities, <Emphasis Type="Italic">MAP</Emphasis> arrivals and <Emphasis Type="Italic">PH</Emphasis> — Service times

We consider a continuous review perishable （s,S） inventory system with a service facility consisting of a waiting hall of finite capacity and a single server. We assume two types of customers, ordinary and negative, arrive according to a Markovian Arrival Process （MAP）. An ordinary customer joins the queue and a negative customer instead of joining the queue removes one ordinary customer from the queue. The removal rule adopted in this paper is RCE （removal of a customer from the end）. The individual customer＇s unit demand is satisfied after a random time of service which is assumed to have a phase-type distribution. The life time of each item and the lead time of the reorders have been assumed to be independent exponential distributions. The joint probability distribution of the number of customers in the system and the inventory level is obtained for the steady state case. Various stationary system performance measures are computed and the total expected cost rate is calculated. The results are illustrated numerically.     

Cooperative Mechanism of Supply Chain Under Asymmetric Information

Abstract: The cooperative mechanism is one main issue in the decentralized supply chain system, especially in an asym-metric information structure. We analyze the non-cooperative game behavior of a 2-echelon distribution supply chain,compare the results with the system optimal solution, and give the supplier dominated cooperative mechanisms. We alsoanalyze the validity of our contract under the asymmetric retailers' holding cost information and give some useful conclu-sions.     

An ε-domination based two-archive 2 algorithm for many-objective optimization

The two-archive 2 algorithm(Two_Arch2) is a manyobjective evolutionary algorithm for balancing the convergence,diversity,and complexity using diversity archive(DA) and convergence archive(CA).However,the individuals in DA are selected based on the traditional Pareto dominance which decreases the selection pressure in the high-dimensional problems.The traditional algorithm even cannot converge due to the weak selection pressure.Meanwhile,Two_Arch2 adopts DA as the output of the algorithm which is hard to maintain diversity and coverage of the final solutions synchronously and increase the complexity of the algorithm.To increase the evolutionary pressure of the algorithm and improve distribution and convergence of the final solutions,an ε-domination based Two_Arch2 algorithm(ε-Two_Arch2) for many-objective problems(MaOPs) is proposed in this paper.In ε-Two_Arch2,to decrease the computational complexity and speed up the convergence,a novel evolutionary framework with a fast update strategy is proposed;to increase the selection pressure,ε-domination is assigned to update the individuals in DA;to guarantee the uniform distribution of the solution,a boundary protection strategy based on I_ε+ indicator is designated as two steps selection strategies to update individuals in CA.To evaluate the performance of the proposed algorithm,a series of benchmark functions with different numbers of objectives is solved.The results demonstrate that the proposed method is competitive with the state-of-the-art multi-objective evolutionary algorithms and the efficiency of the algorithm is significantly improved compared with Two_Arch2.     

A High Speed Detection Scheme for Point Targets in a Multitarget Environment

The purpose of this paper is to develop a high speed detection scheme for moving and / or stationary point targets in a multitarget environment as registered in an IR image sequence. An iterative approximate 3-D line searching algorithm based upon the geometric representation of lines (for non-maneuvering targets in space) in a 3-D space is derived. The convergency of the algorithm is proved. An analysis is performed of the theoretical detection performance of the algorithm. The statistical experiment results show high effectiveness and computational efficiency of the algorithm in the case of low SNR. The idea may be employed to satisfy the real-time processing requirement of an IR system.     

ANALYSIS OF A PRODUCTION-INVENTORY MODEL WITH ERLANGIAN DEMAND ARRIVAL PROCESS

We study a production-inventory system having a machine, a storage facility. The demand for the product is governed by an Erlangian demand arrival process, where demand sizes are independent and identically distributed random variables. A two-criticalnumber policy (m, M) is used to control a machine‘s setups and shutdowns, namely, a machine is shut down whenever the inventory level reaches M, and resumes operating only when the inventory level falls below the critical number m(m ≤ M). We obtain the steady state distribution of the inventory process and some performance measures of the process.     

Many-server queues with customer abandonment: A survey of diffusion and fluid approximations

The performance of a call center is sensitive to customer abandonment.In this survey paper,we focus on G/GI/ n + GI parallel-server queues that serve as a building block to model call center operations.Such a queue has a general arrival process(the G ),independent and identically distributed(iid) service times with a general distribution(the first GI),and iid patience times with a general distribution(the +GI).Following the square-root safety staffing rule,this queue can be operated in the quality- and efficiency-driven(QED) regime,which is characterized by large customer volume,the waiting times being a fraction of the service times,only a small fraction of customers abandoning the system,and high server utilization.Operational efficiency is the central target in a system whose staffing costs dominate other expenses.If a moderate fraction of customer abandonment is allowed,such a system should be operated in an overloaded regime known as the efficiency-driven (ED) regime.We survey recent results on the many-server queues that are operated in the QED and ED regimes.These results include the performance insensitivity to patience time distributions and diffusion and fluid approximate models as practical tools for performance analysis.     

Practical integrated navigation fault detection algorithm based on sequential hypothesis testing

In detecting system fault algorithms,the false alarm rate and undectect rate generated by residual Chi-square test can affect the stability of filters.The paper proposes a fault detection algorithm based on sequential residual Chi-square test and applies to fault detection of an integrated navigation system.The simulation result shows that the algorithm can accurately detect the fault information of global positioning system(GPS),eliminate the influence of false alarm and missed detection on filter,and enhance fault tolerance of integrated navigation systems.     

在线订餐生产配送联合调度模型及算法

The delays of online meal ordering delivery are currently serious. How to coordinate the production and distribution to minimize arrival time has become an urgent problem for online meal ordering during the peak period. Considering the fact that the order information are unknown in advance, a parallel machine production and multi-trip vehicle distribution joint optimization model was established to minimize the makespan of total orders. Besides, a three phase heuristic algorithm was proposed. Through a series of experiments where the orders were generated based on Poisson distribution (),the results were compared with those of the traditional algorithm. Several enlightening findings are discovered: when the order arrival rate, the makespan of total orders of the three phase heuristic algorithm is shorter. Meanwhile with the growth of order arrival rate, the improvement amplitude increases gradually. The model and algorithms proposed are conducive to generating efficiently production and distribution joint scheduling solution during the peak period.     

THE M/M/c QUEUE WITH （e,d） SETUP TIME

The authors present a new queueing model with （e, d） setup time. Using the quasi-birth-and-death process and matrix-geometric method, the authors obtain the stationary distribution of queue length and the LST of waiting time of a customer in the system. Furthermore, the conditional stochastic decomposition results of queue length and waiting time are given.     

Remaining useful lifetime prediction for equipment based on nonlinear implicit degradation modeling

Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics.These features have an uncertain effect on the remaining useful life(RUL)prediction of the equipment.The current data-driven RUL prediction method has not systematically studied the nonlinear hidden degradation modeling and the RUL distribution function.This paper uses the nonlinear Wiener process to build a dual nonlinear implicit degradation model.Based on the historical measured data of similar equipment,the maximum likelihood estimation algorithm is used to estimate the fixed coefficients and the prior distribution of a random coefficient.Using the on-site measured data of the target equipment,the posterior distribution of a random coefficient and actual degradation state are step-by-step updated based on Bayesian inference and the extended Kalman filtering algorithm.The analytical form of the RUL distribution function is derived based on the first hitting time distribution.Combined with the two case studies,the proposed method is verified to have certain advantages over the existing methods in the accuracy of prediction.     

Analysis of batch arrival queue with randomized vacation policy and an un-reliable server

This paper examines an M^[x]G/1 queueing system with an unreliable server and a delayed repair,in which the server operates a randomized vacation policy with multiple vacations.Whenever the system is empty,the server immediately takes a vacation.If there is at least one customer found waiting in the queue upon returning from a vacation,the server will be immediately activated for service.Otherwise,if no customers are waiting for service at the end of a vacation,the server either remains idle with probability p or leaves for another vacation with probability 1-p.Whenever one or more customers arrive when the server is idle,the server immediately starts providing service for the arrivals.The server may also meet an unpredictable breakdown and the repair may be delayed.For such a system the authors derive the distributions of some important system characteristics,such as the system size distribution at a random epoch and at a departure epoch,the system size distribution at the busy period initiation epoch,and the distribution of the idle period and the busy period.The authors perform a numerical analysis for changes in the system characteristics,along with changes in specific values of the system parameters.A cost effectiveness maximization model is constructed to explain the benefits of such a queueing system.     

Iterative learning based fault detection and estimation in nonlinear systems

Aiming at a class of nonlinear systems that contains faults,a novel iterative learning scheme is applied to fault detection,and a novel algorithm of fault detection and estimation is proposed.This algorithm first constructs residual signals by the output of the practical system and the output of the designed fault tracking estimator,and then uses the residuals and the differencevalue signal of the adjacent two residuals to gradually revise the introduced virtual faults,which can cause the virtual faults to close to the practical faults in systems,thereby achieving the goal of fault detection for systems.This algorithm not only makes full use of the existing valid information of systems and has a faster tracking convergent speed than the proportional-type(P-type) algorithm,but also calculates more simply than the proportional-derivative-type(PD-type) algorithm and avoids the unstable effects of differential operations in the system.The final simulation results prove the validity of the proposed algorithm.     

MULTIPLICITY-PRESERVING TRIANGULAR SET DECOMPOSITION OF TWO POLYNOMIALS

In this paper, a multiplicity-preserving triangular set decomposition algorithm is proposed for a system of two polynomials, which involves only computing the primitive polynomial remainder sequence of two polynomials once and certain GCD computations. The algorithm decomposes the unmixed variety defined by two polynomials into square free and disjoint （for non-vertical components, see Definition 4） algebraic cycles represented by triangular sets which may have negative multiplicities. Thus, the authors can count the multiplicities of the non-vertical components. In the bivariate case, the amthors give a complete algorithm to decompose tile system into zeros represented by triangular sets with multiplicities. The authors also analyze the complexity of the algorithm in the bivariate ease. The authors implement the algorithm and show the effectiveness of the method with extensive experiments.     

Robust location algorithm for NLOS environments

One of the main problems facing accurate location in wireless communication systems is non-line-of- sight （NLOS） propagation. Traditional location algorithms are based on classical techniques under minimizing a least-squares objective function and it loses optimality when the NLOS error distribution deviates from Gaussian distribution. An effective location algorithm based on a robust objective function is proposed to mitigate NLOS errors. The proposed method does not require the prior knowledge of the NLOS error distribution and can give a closed-form solution. A comparison is performed in different NLOS environments between the proposed algorithm and two additional ones （LS method and Chan＇s method with an NLOS correction）. The proposed algorithm clearly outperforms the other two.     

Transient Distribution of the Length and Waiting Time of GI／G／1 Queueing System

The paper is a succession of [1, 2]. Using MSP, we give a new approach to calculate the transient distribution of the length and waiting time of GI/G/1 queueing system.     

Optimal redundancy allocation for reliability systems with imperfect switching

The problem of stochastically allocating redundant com- ponents to increase the system lifetime is an important topic of reliability. An optimal redundancy allocation is proposed, which maximizes the expected lifetime of a reliability system with sub- systems consisting of components in parallel. The constraints are minimizing the total resources and the sizes of subsystems. In this system, each switching is independent with each other and works with probability p. Two optimization problems are studied by an incremental algorithm and dynamic programming technique respectively. The incremental algorithm proposed could obtain an approximate optimal solution, and the dynamic programming method could generate the optimal solution,