Kevin R. Gue

Optimising space utilisation in block stacking warehouses

Block stacking storage is an inexpensive storage system widely used in manufacturing systems where pallets of stock keeping units (SKUs) are stored in a warehouse at the finite production rates. However, determining the optimal lane depth that maximises space utilisation under a finite production rate constraint has not been adequately addressed in the literature and is an open problem. In this research, we propose mathematical models to obtain the optimal lane depth for single and multiple SKUs where the pallet production rates are finite. A simulation model is used to evaluate performance of the proposed models under stochastic uncertainty in the major production parameters and the demand.

Optimal Wave Release Times for Order Fulfillment Systems with Deadlines

Service performance of an order fulfillment system is mainly determined by how quickly and accurately it fills customer orders. A higher service level can be offered with a later cutoff time, before which customers are assured of receiving their orders. However, the desire to offer a later cutoff time must be tempered by the need to provide service at low cost, which means taking advantage of economies of scale in picking operations. To strike this balance, many distribution centers release orders in large batches called waves. We develop analytical models to determine the timing and the number of order waves for fulfillment systems that operate against a daily deadline. In a case study, we apply our theoretical models to data from a large distribution center and show that optimal wave releases could significantly improve on time shipments compared to an intuitive method.

Solving large batches of traveling salesman problems with parallel and distributed computing

Gives a practical and effective method for computationally solving numerous TSP instances.Can use different TSP solvers we test an exact method and a heuristic.Can handle TSPs of differing sizes efficiently with a simple processing rule.This problem arises in design of transportation networks, distribution networks and warehouse facilities. In this paper, we describe and compare serial, parallel, and distributed solver implementations for large batches of Traveling Salesman Problems using the LinKernighan Heuristic (LKH) and the Concorde exact TSP Solver. Parallel and distributed solver implementations are useful when many medium to large size TSP instances must be solved simultaneously. These implementations are found to be straightforward and highly efficient compared to serial implementations. Our results indicate that parallel computing using hyper-threading for solving 150- and 200-city TSPs can increase the overall utilization of computer resources up to 25% compared to single thread computing. The resulting speed-up/physical core ratios are as much as ten times better than a parallel and concurrent version of the LKH heuristic using SPC3 in the literature. For variable TSP sizes, a longest processing time first heuristic performs better than an equal distribution rule. We illustrate our approach with an application in the design of order picking warehouses.

The impact of rack layout on visual experience in a retail store

ABSTRACT A retail stores layout affects a shoppers visual experience and correspondingly the time spent in the store, navigation through the aisles, and allocation of attention and money across departments and categories. We show that alternate rack layouts allow for more of a racks facing to appear in the shoppers visual field. To this end, we introduce a set of visual–spatial statistics comprised of visual measures (exposure and intensity) and spatial measures (space and aspect ratio) as a way to quantify the effect a retail layout has on a shoppers visual experience. We present both analytical and algorithmic approaches to capture the dynamics of a travelling shoppers field of regard with respect to a static rack layout. Results for the case of unidirectional shopper travel suggest that racks oriented at 30° from the direction of travel exhibit nearly 250% increase in exposure when compared to 90° racks; for bidirectional traffic, acute orientations still provide up to 150% higher exposure. Interestingly, rack orientations amenable to higher visual measures are not necessarily the best with respect to spatial measures. We illustrate the use of our approach to analyse a real-store layout from a nearby mass merchandiser.

How to Determine Slot Sizes in a Unit-Load Warehouse

Abstract Storage racks in a unit-load warehouse typically have slots of equal height, whereas the unit-loads themselves have heights that vary significantly. The result of this mismatch is unused vertical space and storage areas larger than they otherwise could be. We propose the use of storage racks with multiple slot heights to better match the distribution of pallet heights. The slot profile design problem seeks the best set of slot heights and their corresponding quantities such that a desired service level is met, where service level is the probability that all pallets present in a period can be stored. Using data from several companies, we found that the potential space savings of using multiple slot heights are between 29% and 45%.

A model to optimize rack layout in a retail store

Abstract The physical layout of a retail store is known to influence the attitude and behavior of shoppers and affect store performance. An important role of the stores layout is to expose shoppers to merchandise in order to facilitate consideration and ultimately purchasing of exposed products. This work focuses on determining which rack layouts maximize exposure of products to a shopper. To do this, we introduce the retail rack layout problem (RRLP), which identifies the optimal single or multi-column rack orientations in a constrained space in order to maximize exposure to the shopper. To solve this problem, we propose a mixed-integer, non-linear optimization model, which we solve using a particle swarm optimization (PSO) algorithm. Results indicate that an increase of exposure ranging from 213–226% (small head turns) and 17–18% (large head turns) over 90°-rack layouts can be achieved with angled-racks (acute or obtuse from a shoppers travel path) depending on the duration of exposure. The increase in exposure comes at the expense of loss of display space and is sensitive to the shoppers field of regard (angular limit and depth of vision). We also show that multiple competitive layout designs with 1-, 2-, and even 3-columns may exist for a given system configuration that offer similar exposure values.

An approximation model for sojourn time distributions in acyclic multi-server queueing networks

We develop an approximation model for the sojourn time distribution of customers or jobs arriving to an acyclic multi-server queueing network. The model accepts general interarrival times and general service times, and is based on the characteristics of phase-type distributions. The model produces excellent results for multi-server networks with a small to medium number of workstations, but is less accurate when the number of workstations is large. HighlightsWe model the steady-state distribution of sojourn time of customers in an acyclic, multi-stage, multi-server queueing network.We use phase-type distributions to approximate waiting times and general processing times.The model can be used to predict the probability that time in a system will exceed a specified time.The model is especially effective for small- and medium-sized systems.