Application of the Cube-Per-Order Index Rule for Stock Location in a Distribution Warehouse

Abstract

Consider a distribution warehouse divided into reserve storage and staging areas. The warehouse stores a variety of items and receives orders for any combination of items. Goods are moved from reserve storage to staging area, where they are selected to fill the given orders. The problem is to locate items in the staging area in order to minimize the expected labor costs of order selection. Several years ago, J. L. Heskett [Heskett, J. L. 1963. Cube-per-order index—A key to warehouse stock location. Transportation and Distribution Management 3 (April) 27–31.] proposed a criterion, called the cube-per-order index (CPO) rule, for solving this problem. The criterion was justified heuristically by means of numerical examples. Recently [Kallina, C. 1976. Optimality of the cube-per-order index rule for stock location in a distribution warehouse. Working paper, American Can Company, March.], one of the authors has shown that the class of problems considered by Heskett can be formulated as a linear program, and that the CPO rule is in fact the optimal solution. In this present paper, we will (1) summarize some basic background material, (2) describe the computational steps for implementation of the CPO rule, and (3) discuss some practical conclusions gathered from experience in actually applying the rule to assist in warehouse layout.

Order Picking: A Survey of Planning Problems and Methods

“…Here, the turnover or demand frequency of an item type is equal to the number of times it appears in a customer order during a specific period of time. It can be expected that the distribution of these frequency has a direct influence on the extent to which alternative storage policies affect picking times and costs (Kallina/Lynn, 1976;Malmborg, 1996). The distribution is usually represented by an ABC curve, which -in this context -can be characterized by a percentage ratio such as 20/80 which means that 20% of the item types are responsible for 80% of the demand frequencies (for details see Malmborg, 1996, pp.…”

“…Heskett (1963Heskett ( , 1964 introduced the so-called cube-per-order index (COI) which is defined as the ratio of the required storage space to be allocated to an item type to its demand frequency per period (also see Ballou, 1967;Kallina/Lynn, 1976). The concept of the COI is to locate compact, high-frequency item types (low COI) close to the input-output point, and shift bulky, slow-moving items to remote storage locations.…”

Desarrollo de un modelo heurístico para la optimización en el manejo de material en estibas en una bodega

“…En [7] se presenta un problema interesante que es el proceso de selección de los productos en las áreas de Picking, con mínimas distancias. J. L Heskett propuso un algoritmo heurístico llamado Cube-per-order (CPO), que presenta una solución a la localización de ítems en la bodega con el fin de minimizar los costos involucrados en el tiempo de espera para la selección de los productos de una orden recibida.…”

Demand Point Aggregation Analaysis for Location Models

“…In this way, the advantages of dedicated storage still hold, but the disadvantages are only minor because dedicated storage is applied only to a small area (Koster et al 2007). Kallina and Lynn (1976) discussed the implementation of the COI rule in practice. The COI rule is easy to implement and has the intuitive appeal of locating compact, fast-moving items in readily accessible locations.…”

“…This section lists some real industrial case studies, which not only provide applications of the various design and operation methods in practical contexts, but more Zeng et al (2002) Storage location assignment; warehouse dimensioning; storage and order picking policy A distribution center Van Oudheusden et al (1988) Storage location assignment; batching; routing A man-on-board AS/RS in an integrated steel mill Kallina and Lynn (1976) Storage location assignment using the COI rule A distribution center importantly also identify possible future research challenges from the industrial point of view. Table 18.1 lists these case studies with the problems and the types of warehouse they investigated.…”