Queue Storage Research Articles

Heuristic, storage space minimization methods for facility layouts served by looped AGV systems

Abstract An analytical method for predicting work-in-process storage requirements resulting from a fixed number of looping, automated guided vehicles (AGVs) serving a line layout is described. The method is based on a model of storage queue dynamics that predicts material flow rates and vehicle response times resulting from vehicle dispatching within a single loop system. The method is applied in the development of two heuristic, random number driven procedures designed to perform sequential search for WIP storage minimizing line layouts over alternative AGV fleet sizes. The first algorithm is a greedy, ‘CRAFT like’ procedure based on local improvement in storage requirements using random, pairwise exchanges of workcentre locations. The second algorithm is a modification to the greedy procedure using simulated annealing methods designed to avoid trapping at local minima. Limited computational studies using the methods are reported.

Stochastic Models of Queue Storage

We study a model of queue storage in which items (requests for single units of storage) arrive in a Poisson stream and are accommodated by the first available location in a linear scan of storage. The processing times of items are independent, exponentially distributed random variables. The set of occupied locations (identified by their indices) at time t forms a random subset Si, of [1,2,.…]. The extent of the fragmentation in Si, i.e., the alternating holes and occupied regions of storage, is measured by Wt, = max St, – |St|.

A Random-Walk Model of a Queue Storage Problem

Abstract—A probability model of queue storage allocation problems is devised and an analysis is provided based on the theory of random walks. Two types of queue storage allocation are discussed and analyzed, after which examples are given to illustrate their relative advantages and disadvantages.