Resource allocation

Allocation problems involve the distribution of resources among competing alternatives in order to minimize total costs or maximize total return. Such problems have the following components: a set of resources available in given amounts; a set of jobs to be done, each consuming a specified amount of resources; and a set of costs or returns for each job and resource. The problem is to determine how much of each resource to allocate to each job.

If more resources are available than needed, the solution should indicate which resources are not to be used, taking associated costs into account. Similarly, if there are more jobs than can be done with available resources, the solution should indicate which jobs are not to be done, again taking into account the associated costs.

If each job requires exactly one resource (e.g., one person) and each resource can be used on only one job, the resulting problem is one of assignment. If resources are divisible, and if both jobs and resources are expressed in units on the same scale, it is termed a transportation or distribution problem. If jobs and resources are not expressed in the same units, it is a general allocation problem.

An assignment problem may consist of assigning workers to offices or jobs, trucks to delivery routes, drivers to trucks, or classes to rooms. A typical transportation problem involves distribution of empty railroad freight cars where needed or the assignment of orders to factories for production. The general allocation problem may consist of determining which machines should be employed to make a given product or what set of products should be manufactured in a plant during a particular period.

In allocation problems the unit costs or returns may be either independent or interdependent; for example, the return from investing a dollar in selling effort may depend on the amount spent on advertising. If the allocations made in one period affect those in subsequent periods, the problem is said to be dynamic, and time must be considered in its solution.

Linear programming

Linear programming (LP) refers to a family of mathematical optimization techniques that have proved effective in solving resource allocation problems, particularly those found in industrial production systems. Linear programming methods are algebraic techniques based on a series of equations or inequalities that limit a problem and are used to optimize a mathematical expression called an objective function. The objective function and the constraints placed upon the problem must be deterministic and able to be expressed in linear form. These restrictions limit the number of problems that can be handled directly, but since the introduction of linear programming in the late 1940s, much progress has been made to adapt the method to more complex problems.

Since linear programming is probably the most widely used mathematical optimization technique, numerous computer programs are available for solving LP problems. For example, LP techniques are now used routinely for such problems as oil and chemical refinery blending, choosing vendors or suppliers for large, multiplant manufacturing corporations, determining shipping routes and schedules, and managing and maintaining truck fleets.

Inventory control

Inventories include raw materials, component parts, work in process, finished goods, packing and packaging materials, and general supplies. The control of inventories, vital to the financial strength of a firm, in general involves deciding at what points in the production system stocks shall be held and what their form and size are to be. As some unit costs increase with inventory size—including storage, obsolescence, deterioration, insurance, investment—and other unit costs decrease with inventory size—including setup or preparation costs, delays because of shortages, and so forth—a good part of inventory management consists of determining optimal purchase or production lot sizes and base stock levels that will balance the opposing cost influences. Another part of the general inventory problem is deciding the levels (reorder points) at which orders for replenishment of inventories are to be initiated.

Inventory control is concerned with two questions: when to replenish the store and by how much. There are two main control systems. The two-bin system (sometimes called the min-max system) involves the use of two bins, either physically or on paper. The first bin is intended for supplying current demand and the second for satisfying demand during the replenishment period. When the stock in the first bin is depleted, an order for a given quantity is generated. The reorder-cycle system, or cyclical-review system, consists of ordering at fixed regular intervals. Various combinations of these systems can be used in the construction of an inventory-control procedure. A pure two-bin system, for example, can be modified to require cyclical instead of continuous review of stock, with orders being generated only when the stock falls below a specific level. Similarly, a pure reorder-cycle system can be modified to allow orders to be generated if the stock falls below the reorder level between the cyclical reviews. In yet another variation, the reorder quantity in the reorder-cycle system is made to depend on the stock level at the review period or the need to order other products or materials at the same time or both.

The classic inventory problem involves determining how much of a resource to acquire, either by purchasing or producing it, and whether or when to acquire it to minimize the sum of the costs that increase with the size of inventory and those that decrease with increases in inventory. Costs of the first type include the cost of the capital invested in inventory, handling, storage, insurance, taxes, depreciation, deterioration, and obsolescence. Costs that decrease as inventory increases include shortage costs (arising from lost sales), production setup costs, and the purchase price or direct production costs. Setup costs include the cost of placing a purchase order or starting a production run. If large quantities are ordered, inventories increase but the frequency of ordering decreases, hence setup costs decrease. In general, the larger the quantity ordered the lower the unit purchase price because of quantity discounts and the lower production cost per unit resulting from the greater efficiency of long production runs. Other relevant variables include demand for the resource and the time between placing and filling orders.

Inventory problems arise in a wide variety of contexts; for example, determining quantities of goods to be purchased or produced, how many people to hire or train, how large a new production or retailing facility should be or how many should be provided, and how much fluid (operating) capital to keep available. Inventory models for single items are well developed and are normally solved with calculus. When the order quantities for many items are interdependent (as, for example, when there is limited storage space or production time) the problem is more difficult. Some of the larger problems can be solved by breaking them into interacting inventory and allocation problems. In very large problems simulation can be used to test various relevant decision rules.

Japanese approaches

In the 1970s several Japanese firms, led by the Toyota Motor Corporation, developed radically different approaches to the management of inventories. Coined the “just-in-time” approach, the basic element of the new systems was the dramatic reduction of inventories throughout the total production system. By relying on careful scheduling and the coordination of supplies, the Japanese ensured that parts and supplies were available in the right quantity, with proper quality, at the exact time they were needed in the manufacturing or assembly process.

Two things made just-in-time work—a dogged attention to quality at all levels of the total system obviated the need for parts inventories to cover defectives found in the manufacturing process, and a close coordination of information and plans with suppliers and vendors permitted them to align their schedules and shipments with the last-minute needs of the manufacturer. Elements of the just-in-time approach now have been adopted by numerous companies in the United States and Europe, although many cannot use the system to its fullest extent because their supplier networks are larger and more widely dispersed than in Japan.

A second Japanese technique, called kanban (“card”), also permits Japanese firms to schedule production and manage inventories more effectively. In the kanban system, cards or tickets are attached to batches, racks, or pallet loads of parts in the manufacturing process. When a batch is depleted in the assembly process, its kanban is returned to the manufacturing department and another batch is shipped immediately. Since the total number of parts or batches in the system is held constant, the coordination, scheduling, and control of the inventory is greatly simplified.