A model for determining machine requirements in a multistage manufacturing system with discretely distributed demand

A model is presented for resolving the problem of determining the optimum number of machines, and their discrete operating rates, required to meet discretely distributed production demands with a minimum total expected cost. The model is developed for a serial, multistage manufacturing system with both straight-time and overtime operating periods.     

Optimal threshold policies in a workload model with a variable number of service phases per job

We consider an M|E _N |1 queue in which there are two essential on-line decisions that have to be taken. The first one is the decision to either accept or reject new jobs. The second one is the decision to either continue or abort the service of a job. We show that under certain regularity conditions, there exist optimal threshold policies for these two types of decisions.     

A simulation optimization approach for a two-echelon inventory system with service level constraints

In this paper, we present a simulation optimization algorithm for solving the two-echelon constrained inventory problem. The goal is to determine the optimal setting of stocking levels to minimize the total inventory investment costs while satisfying the expected response time targets for each field depot. The proposed algorithm is more adaptive than ordinary optimization algorithms, and can be applied to any multi-item multi-echelon inventory system, where the cost structure and service level function resemble what we assume. Empirical studies are performed to compare the efficiency of the proposed algorithms with other existing simulation algorithms.     

Balancing stocks, flexible recipe costs and high service level requirements in a batch process industry: A study of a small scale model

Process industries often obtain their raw materials from mining or agricultural industries. These raw materials usually have variations in quality which often lead to variations in the recipes used for manufacturing a product. Another reason for varying the recipe is to minimize production costs by using the cheapest materials that still lead to a satisfactory quality in the product. A third reason for using recipe flexibility is that it may occur that not all materials for the standard recipe are available. If variations in supply and demand are large, keeping sufficient safety stock to cope with these variations may incur prohibitive high costs. This means that the costs of keeping safety stock should be balanced with the costs of sometimes using more expensive recipes. The question now is for what situations and to what extent the use of recipe flexibility is justified. In this paper we study this question by means of a small scale model. For this simple situation we derive a decision procedure to balance safety stock costs and flexibility costs. This procedure is applied to a range of different situations, that are characterized by a set of parameter values, in order to determine for which situations recipe flexibility should be used.     

A queueing model for customer rescheduling and no-shows in service systems

We study an M/M/1/K queue where customers can reschedule their appointments. Rescheduled customers show up with higher probabilities, incurring lower no-show costs, but rescheduling also frees up slots that may not be filled later, leading to wasted service capacity and lower throughput. The system manager aims to minimize the long-run average cost by controlling rescheduling policies. We derive conditions under which rescheduling should be allowed for different scenarios depending on whether customers can reschedule only once or multiple times.     

Sojourn and waiting times in a single-server system with state-dependent mean service rate

A birth-death queueing system with asingle server, first-come first-served discipline, Poisson arrivals and state-dependent mean service rate is considered. The problem of determining the equilibrium densities of the sojourn and waiting times is formulated, in general. The particular case in which the mean service rate has one of two values, depending on whether or not the number of customers in the system exceeds a prescribed threshold, is then investigated. A generating function is derived for the Laplace transforms of the densities of the sojourn and waiting times, leading to explicit expressions for these quantities. Explicit expressions for the second moments of the sojourn and waiting times are also obtained.     

A Python framework to create and simulate models with variable structure in common simulation environments

In modelling and simulation, model complexity increases with the complexity of real systems, often resulting in unfeasibly long simulation times. Variable-structure models, which can change their equation set during run-time, offer a solution. This article introduces an object-oriented approach that describes such models independent of a simulation environment. The problem of changing equations during run-time is addressed using a Python framework. Three tools are already integrated, namely, Dymola, OpenModelica and Matlab/Simulink. With this framework, existing models can be easily reused, and the advantages of different simulation tools can be leveraged. The framework is illustrated using a simple satellite launch example, along with instructions for how to use the framework. The main aim of the framework is to simulate complex models with a few mode changes and thus save simulation time. With two real-world examples and a scalability analysis, it is shown that the framework fulfils these requirements.     

A model for obtaining waiting time estimates in an interactive computing environment

A queueing theory model is described which serves as a management tool for evaluating the service efficiency of a computer installation. Analysis relies on standard data obtained at low cost. Application results are shown for the case of a Prime 750 system which supports an heterogeneous population of interactive users.     

Combining simulation and goal programming for healthcare planning in a medical assessment unit

This paper describes a detailed simulation model for healthcare planning in a medical assessment unit (MAU) of a general hospital belonging to the national health service (NHS), UK. The MAU is established to improve the quality of care given to acute medical patients on admission, and to provide the organisational means of rapid assessment and investigation in order to avoid unnecessary admissions. The simulation model enables different scenarios to be tested to eliminate bottlenecks in order to achieve optimal clinical workflow. The link between goal programming (GP) and simulation for efficient resource planning is explored. A GP model is developed for trade-off analysis of the results obtained from the simulation. The implications of MAU management preferences to various objectives are presented.     

Waiting times in a two-queue model with exhaustive and Bernoulli service

This paper deals with waiting times in a two-queue polling system in which one queue is served according to the Bernoulli service discipline and the other one attains exhaustive service. Exact results are derived for the LST's of the waiting time distributions via an iteration scheme. Based on those results the mean waiting times are expressed in the system parameters.     

A discrete event simulation model in the case of managing a software project

The design and development of large-scale software projects is a complex endeavor, often facing problems like cost and schedule overruns as well as low quality. Over the last years the management of software development projects has been recognized as the cornerstone point of seeking improvement and solutions. Simulation modeling of the software project process is gaining interest among academics and practitioners, as a method to tackle the complex questions with which relevant enterprises are confronted. It offers support on several issues, such as defining software product development strategies, decision-making regarding process improvement and training, in a time span ranging from a short portion of the life cycle to long term product evolution, with organization-wide implications. The aim of this work is to implement a model simulating a core part of a software project process, enabling the estimation of several project development details such as delivery times and quality metrics. The purpose of the model is to assist project managers in control and monitoring, but also in identifying the best planning alternatives. The model scope covers a portion of the life cycle of an incremental software development venture.     

A sufficient condition and a necessary condition for the diffusion approximations of multiclass queueing networks under priority service disciplines

We establish a sufficient condition for the existence of the (conventional) diffusion approximation for multiclass queueing networks under priority service disciplines. The sufficient condition relates to a sufficient condition for the weak stability of the fluid networks that correspond to the queueing networks under consideration. In addition, we establish a necessary condition for the network to have a continuous diffusion limit; the necessary condition is to require a reflection matrix (of dimension equal to the number of stations) to be completely-S. When applied to some examples, including generalized Jackson networks, single station multiclass queues, first-buffer-first-served re-entrant lines, a two-station Dai–Wang network and a three-station Dumas network, the sufficient condition coincides with the necessary condition.     

Sojourn time analysis for a cyclic-service tandem queueing model with general decrementing service

A sojourn time analysis is provided for a cyclic-service tandem queue with general decrementing service which operates as follows: starting once a service of queue 1 in the first stage, a single server continues serving messages in queue 1 until either queue 1 becomes empty, or the number of messages decreases to k less than that found upon the server's last arrival at queue 1, whichever occurs first, where 1 ≤ k ≤ ∞. After service completion in queue 1, the server switches over to queue 2 in the second stage and serves all messages in queue 2 until it becomes empty. It is assumed that an arrival stream is Poissonian, message service times at each stage are generally distributed and switch-over times are zero. This paper analyzes joint queue-length distributions and message sojourn time distributions.     

Combining discrete-event simulation and system dynamics in a healthcare setting: A composite model for Chlamydia infection

This paper presents a composite model in which two simulation approaches, discrete-event simulation (DES) and system dynamics (SD), are used together to address a major healthcare problem, the sexually transmitted infection Chlamydia. The paper continues an on-going discussion in the literature about the potential benefits of linking DES and SD. Previous researchers have argued that DES and SD are complementary approaches and many real-world problems would benefit from combining both methods. In this paper, a DES model of the hospital outpatient clinic which treats Chlamydia patients is combined with an SD model of the infection process in the community. These two models were developed in commercial software and linked in an automated fashion via an Excel interface. To our knowledge this is the first time such a composite model has been used in a healthcare setting. The model shows how the prevalence of Chlamydia at a community level affects (and is affected by) operational level decisions made in the hospital outpatient department. We discuss the additional benefits provided by the composite model over and above the benefits gained from the two individual models.     

A probabilistic quality of service constraint for a location model of switches in ATM communications networks

We formulate a model for the optimal location of switches in ATM communications networks. The networks are designed in such a way that, at their arrival to the switches, ATM cells find free space in a buffer of length b, with a probability α. The model avoids the impairment to the communication caused by both cell loss (because of shorter buffers) and cell-delay variations (because of longer buffers). It is also shown how to transform a non-linear, probabilistic, constraint into a linear form. Computational experience is provided for the model. This revised version was published online in June 2006 with corrections to the Cover Date.     

Efficient computation of time-based customer service levels in a multi-item, multi-echelon supply chain: A practical approach for inventory optimization

Time-based item fill rates, or “channel” fill rates, are the building blocks needed to evaluate steady-state compliance with time-based customer service agreements. Exact computation of channel fill rates is both difficult and time-consuming, yet their accurate assessment is essential for system-wide inventory optimization. We describe and validate a practical method for computing channel fill rates in a multi-item, multi-echelon service parts distribution system. A simulation study is presented which shows that, in a three-echelon setting, our estimation errors are very small over a wide range of base stock level vectors. A more accurate, though less efficient, approximation method is also evaluated for comparison.     

A two warehouse inventory model for deteriorating items with a linear trend in demand and shortages

In this paper, we develop a deterministic inventory model with two warehouses (one is the existing storage known as own warehouse (OW) and the other is hired on rental basis known as rented warehouse (RW). The model allows different levels of item deterioration in both warehouses. The demand rate is supposed to be a linear (increasing) function of time and the replenishment rate is infinite. The stock is transferred from RW to OW in continuous release pattern and the associated transportation cost is taken into account. Shortages in OW are allowed and excess demand is backlogged. For the general model, we give the equations for the optimal policy and cost function and we discuss some special cases. A numerical example is given to illustrate the solution procedure of the model. Finally, based on this example, we conduct a sensitivity analysis of the model.     

A difference equation approach for analysing a batch service queue with the batch renewal arrival process

We consider an infinite buffer single server queue wherein customers arrive according to the batch renewal arrival process and are served in batches following the random serving capacity rule. The service-batch times follow exponential distribution. This model has been studied in the past using the embedded Markov chain technique and probability generating function. In this paper we provide an alternative yet simple methodology to carry out the whole analysis which is based on the supplementary variable technique and the theory of difference equations. The procedure used here is simple in the sense that it does not require the complicated task of constructing the transition probability matrix. We obtain explicit expressions of the steady-state system-content distribution at pre-arrival and arbitrary epochs in terms of roots of the associated characteristic equation. We also present few numerical results in order to illustrate the computational procedure.