Product form in networks of queues with batch arrivals and batch services

A product form equilibrium distribution is derived for a class of queueing networks in either discrete or continuous time, in which multiple customers arrive simultaneously and batches of customers complete service simultaneously.     

考虑加工速率相互干扰的平行机调度最优策略研究

随着智能互联网的应用深入、个性化消费时代的来临,制造服务企业开始注重利用网络平台为客户提供个性化的定制服务,在此过程中派生出了产品设计师可与多名客户在线同步交互的一种新型服务模式。本文根据设计师服务效率受并行服务客户数量影响的特征,将问题刻画为机器处理速度相互影响的一类平行机调度模型,以最小化总完工时间为优化目标,研究设计最优调度方案。首先,对于只有两名设计师且各自同时处理最多两个任务的情形,提出了改进的SPT调度规则,运用归纳法证明了该规则可以生成最优加工方案。其次,对改进的SPT规则进行任务分配方式的适当松驰以便更加易于操作,并证明松驰后的新分配方案保持了解的最优性。最后,将相关结论推广至多名设计师的一般情形。上述研究为个性化在线定制服务模式下的有效调度策略制定提供了良好的理论支撑。     

Poisson Traffic Processes in RGSMP and Generalized Networks

1.Introductiontrafficprocessesinqueueingnetworksareanimportantoperatingfacetofsuchmodels,aswellasvaluableinthestudyofvaliddecompositionsofnetworks.IfwefindsometrafficprocessesinanetworkPoisson,thenitoftenrendersthemathematicalanalysistractable.Generalized…     

Minisum collection depots location problem with multiple facilities on a network

We investigate the problem of locating a set of service facilities that need to service customers on a network. To provide service, a server has to visit both the demand node and one of several collection depots. We employ the criterion of minimizing the weighted sum of round trip distances. We prove that there exists a dominating location set for the problem on a general network. The properties of the solution on a tree and on a cycle are discussed. The problem of locating service facilities and collection depots simultaneously is also studied. To solve the problem on a general network, we suggest a Lagrangian relaxation imbedded branch-and-bound algorithm. Computational results are reported.     

A fuzzy goal programming and meta heuristic algorithms for solving integrated production: distribution planning problem

Integrated production–distribution planning is one of the most important issues in supply chain management (SCM). We consider a supply chain (SC) network to consist of a manufacturer, with multiple plants, products, distribution centers (DCs), retailers and customers. A multi-objective linear programming problem for integrating production–distribution, which considers various simultaneously conflicting objectives, is developed. The decision maker’s imprecise aspiration levels of goals are incorporated into the model using a fuzzy goal programming approach. Due to complexity of the considered problem we propose three meta-heuristics to tackle the problem. A simple genetic algorithm and a particle swarm optimization (PSO) algorithm with a new fitness function, and an improved hybrid genetic algorithm are developed. In order to show the efficiency of the proposed methods, two classes of problems are considered and their instances are solved using all methods. The obtained results show that the improved hybrid genetic algorithm gives us the best solutions in a reasonable computational time.     

线型/圈型网络上单台车辆分群调度问题

本文研究线型/圈型网络上单台车辆分群调度问题。给定一个线型/圈型网络,若干客户分布其中。所有客户被划分成若干个子集,每个子集称为一个群。每个客户有一个释放时间和一个服务时间。给定一台车辆,其需要服务所有客户,且每个群内的客户连续服务。问题的要求是计算一个时间表,使得车辆能够按要求服务完所有客户并返回初始出发位置所花费的时间最少。针对该问题,就线型网络和圈型网络,分别给出一个7/4和一个13/7近似算法。     

A Model for Advanced Reservations for Large Scale Conferencing Services

This note describes a model for advanced reservations extended to systems which can serve many customers at the same time. The new model has been developed for a communication network which provides intercity visual conferencing services via a satellite capable of accommodating many conferences simultaneously. Each customer calls in advance to reserve time on a future date. A scheduler either satisfies the request, or offers available alternatives which may or may not be acceptable to the customer. The model is used to examine different measures of quality-of-service and system utilization.     

Synchronized reneging in queueing systems with vacations

In this paper we present a detailed analysis of queueing models with vacations and impatient customers, where the source of impatience is the absence of the server. Instead of the standard assumption that customers perform independent abandonments, we consider situations where customers abandon the system simultaneously. This is, for example, the case in remote systems where customers may decide to abandon the system, when a transport facility becomes available.     

Selective capacitated location-routing problem with incentive-dependent returns in designing used products collection network

This paper addresses a generalization of the capacitated location-routing problem (CLRP) arising in the design of a collection network for a company engaged in collecting used products from customer zones. The company offers customers a financial incentive per unit of used products. This incentive determines the quantity of used products which are returned by customers. Moreover, it is not necessary for the company to visit all customer zones or to collect all returns in each visited customer zone. The objective is to simultaneously find the location of collection centers, the routes of vehicles, the value of incentive offered and the amount of used products collected from customer zones, so as to maximize the company's overall profit. We develop two mixed integer linear programming formulations of the problem and a heuristic algorithm based on iterated local search. Extensive computational experiments on this problem demonstrate the effectiveness of the proposed algorithm.     

Optimal allocation of stock levels and stochastic customer demands to a capacitated resource

This paper considers a new class of stochastic resource allocation problems that requires simultaneously determining the customers that a capacitated resource must serve and the stock levels of multiple items that may be used in meeting these customers’ demands. Our model considers a reward (revenue) for serving each assigned customer, a variable cost for allocating each item to the resource, and a shortage cost for each unit of unsatisfied customer demand in a single-period context. The model maximizes the expected profit resulting from the assignment of customers and items to the resource while obeying the resource capacity constraint. We provide an exact solution method for this mixed integer nonlinear optimization problem using a Generalized Benders Decomposition approach. This decomposition approach uses Lagrangian relaxation to solve a constrained multi-item newsvendor subproblem and uses CPLEX to solve a mixed-integer linear master problem. We generate Benders cuts for the master problem by obtaining a series of subgradients of the subproblem’s convex objective function. In addition, we present a family of heuristic solution approaches and compare our methods with several MINLP (Mixed-Integer Nonlinear Programming) commercial solvers in order to benchmark their efficiency and quality.     

Supply chain network design: partner selection and production/distribution planning using a systematic model

In this paper, a novel multi-phase mathematical approach is presented for the design of a complex supply chain network. From the point of network design, customer demands, and for maximum overall utility, the important issues are to find suitable and quality companies, and to decide upon an appropriate production/distribution strategy. The proposed approach is based on the genetic algorithm (GA), the analytical hierarchy process (AHP), and the multi-attribute utility theory (MAUT) to satisfy simultaneously the preferences of the suppliers and the customers at each level in the network. A case study with a good quality solution is provided to confirm the efficiency and effectiveness of the proposed approach. Finally, to demonstrate the performance of the proposed approach, a comparative numerical experiment is performed by using the proposed approach and the common single-phase genetic algorithm (SGA). Empirical analysis results demonstrate that the proposed approach can outperform the SGA in partner selection and production/distribution planning for network design.     

The plant location problem with demand-dependent setup costs and centralized allocation

Suppose that customers are situated at the nodes of a transportation network, and a service company plans to locate a number of facilities that will serve the customers. The objective is to minimize the sum of the total setup cost and the total transportation cost. The setup cost of a facility is demand-dependent, that is, it depends on the number of customers that are served by the facility. Centralized allocation of customers to facilities is assumed, that is, the service company makes a decision about allocation of customers to facilities. In the case of a general network, the model can be formulated as a mixed integer programming problem. For the case of a tree network, we develop a polynomial-time dynamic programming algorithm.     

Periodic capacitated arc-routing problem with inventory constraints

The purpose of this paper is to study the periodic arc-routing problem when the arcs of a network behave as customers, and sufficient material is delivered so that each achieves its desired inventory level. Therefore, routing and inventory decisions are made simultaneously. Applications include dust suppression in open-pit mines or forest roads and plant watering along sidewalks or street medians. A truck periodically sprays water along the edges of a network. The humidity reaches a desired level and is then consumed over time until water is delivered again. The quantity of water delivered can be fixed or variable; we consider both scenarios and propose a mathematical model for each. Results are reported to validate the model. The contribution of this paper is the first mathematical model that combines inventory and routing decisions in the arc-routing domain.     

A framework for solving network revenue management problems with customer choice behavior

Revenue management is the process of understanding, anticipating and influencing consumer behavior in order to maximize revenue. Network revenue management models attempt to maximize revenue when customers buy bundles of multiple resources. The dependence among the resources in such cases is created by customer demand. Network revenue management can be formulated as a stochastic dynamic programming problem whose exact solution is computationally intractable. Solutions are based on approximations of various types. Customer choice behavior modeling has been gaining increasing attention in the revenue management. A framework for solving network revenue management problems with customer choice behavior is proposed. The modeling and solving framework is composed from three inter-related network structures: basic network model, Petri net, and neural net.     

A Markov Renewal Based Model for Wireless Networks

We propose a queueing network model which can be used for the integration of the mobility and teletraffic aspects that are characteristic of wireless networks. In the general case, the model is an open network of infinite server queues where customers arrive according to a non-homogeneous Poisson process. The movement of a customer in the network is described by a Markov renewal process. Moreover, customers have attributes, such as a teletraffic state, that are driven by continuous time Markov chains and, therefore, change as they move through the network. We investigate the transient and limit number of customers in disjoint sets of nodes and attributes. These turn out to be independent Poisson random variables. We also calculate the covariances of the number of customers in two sets of nodes and attributes at different time epochs. Moreover, we conclude that the arrival process per attribute to a node is the sum of independent Poisson cluster processes and derive its univariate probability generating function. In addition, the arrival process to an outside node of the network is a non-homogeneous Poisson process. We illustrate the applications of the queueing network model and the results derived in a particular wireless network.     

The <Emphasis Type="Italic">M</Emphasis>/<Emphasis Type="Italic">M</Emphasis>/1 queue with synchronized abandonments

In this paper we present a detailed analysis of a single server Markovian queue with impatient customers. Instead of the standard assumption that customers perform independent abandonments, we consider situations where customers abandon the system simultaneously. Moreover, we distinguish two abandonment scenarios; in the first one all present customers become impatient and perform synchronized abandonments, while in the second scenario we exclude the customer in service from the abandonment procedure. Furthermore, we extend our analysis to the M/M/c queue under the second abandonment scenario.     

Sequencing Games with Slack Due Windows and Group Technology Considerations

We study sequencing situations in which the customers are initially sequenced to be served by a single server. We consider both slack due windows and group technology simultaneously. We introduce two division rules to divide among the customers the cost saving from resequencing the customers to follow the optimal sequence and characterize the rules axiomatically. Applying cooperative game theory to analyze the sequencing games corresponding to the sequencing situations, we use the theory’s solution concepts to solve the games.     

An efficient three-level heuristic for the large-scaled multi-product production routing problem with outsourcing

A classic production routing problem (PRP), in which a plant produces and distributes a single product to a set of customers over a finite time horizon, consists of planning simultaneously the production, inventory and routing activities to minimize the total cost. The last few decades have witnessed the increasing efforts made to solve such a complex problem. In this paper, we investigate a generalized PRP by considering multiple products and outsourcing (MPRP-OS). The newly studied problem is first formulated into a mixed integer linear program. Then a three-level mathematical-programming-based heuristic called TLH is developed to solve it. TLH combines a two-phase iterative method, a repairing strategy and a fix-and-optimize procedure to find near-optimal solutions. In addition, it is adaptable to solve the classic PRP. Computational experiments on 225 newly generated MPRP-OS instances with up to 200 customers, 20 vehicles, 6 periods and 12 products show the effectiveness and efficiency of the proposed heuristic. The performance of TLH is further demonstrated by testing 1530 classic PRP benchmark instances with up to 200 customers, 13 vehicles and 20 periods. Experimental results indicate that TLH is able to solve large-sized MPRP-OS instances within short computation times. In addition, TLH provides new best solutions for 283 out of 1530 benchmark instances.     

The impact of breakdowns disciplines and repeated attempts on performances of Small Cell Networks

This paper aims at presenting an approach to study performance and reliability of Small Cell Networks, taking into account the retrial phenomenon, the finite number of customers (mobiles) served in a cell and the random breakdowns of the base station channels. We consider the classical disciplines namely, active and dependent breakdowns and moreover we propose new breakdowns disciplines, in which we give to the interrupted customers due to a channel failure, a higher priority compared to other customers. To this end, we use the Generalized Stochastic Petri Nets (GSPNs) model as a support. However, one of the major drawbacks of this high-level formalism in performance evaluation of large networks is the state space explosion problem which increases when considering repeated calls and multiple unreliable channels. Hence, the novelty of this investigation is the presentation, for the different breakdowns disciplines with and without priority, of an approach which allows a direct computing of the infinitesimal generator describing the customers behavior and the channels allocation in as small cell, neither generating nor storing the reachability set. In addition, we develop the formulas of the main stationary performance and reliability indices, as a function of the network parameters, the stationary probabilities and independently of the reachability set markings. Through numerical examples, we discuss the effect of retrials, breakdowns disciplines and the priority on performances.     

Scheduling networks of queues: Heavy traffic analysis of a simple open network

We consider a queueing network with two single-server stations and two types of customers. Customers of type A require service only at station 1 and customers of type B require service first at station 1 and then at station 2. Each server has a different general service time distribution, and each customer type has a different general interarrival time distribution. The problem is to find a dynamic sequencing policy at station 1 that minimizes the long-run average expected number of customers in the system.The scheduling problem is approximated by a dynamic control problem involving Brownian motion. A reformulation of this control problem is solved, and the solution is interpreted in terms of the queueing system in order to obtain an effective sequencing policy. Also, a pathwise lower bound (for any sequencing policy) is obtained for the total number of customers in the network. We show via simulation that the relative difference between the performance of the proposed policy and the pathwise lower bound becomes small as the load on the network is increased toward the heavy traffic limit.