_{1}

^{*}

In the classical Newsboy problem, we provide a new proof for the tight range of optimal order quantities for the newsboy problem when only the mean and standard deviation of demand are available. The new proof is only based on the definition of the optimal solution therefore it is the most straightforward method. It is also shown that the classical Scarf’s rule is the mid-point of the range of optimal order quantities. This provides an additional understanding of Scarf’s order rule as a distribution free decision.

The classical newsboy problem assumes that there is a single purchase decision before the selling season and the demand D is an unknown random variable. The objective is to decide the order quantity Q to maximize the expected profit. In Newsboy problem, the expected profit can be expressed as

where c > 0 is the unit cost, p is the selling price, s is the salvage value, G is the cumulative distribution function of demand. In (1), is the expected value and is defined as when Q is greater than D and zero otherwise. Furthermore, let p = c(1 + m) > c where m is the mark up, and s = (1 – d)c < c where d is the discount, (1) can be expressed as

To maxmize the above expected profit, it is equivalent to mininize the following cost function

To determine the order quantity Q, G is frequently assumed to be normally distributed in many OM/OR literatures ([1-3]). However, this assumption may not be true in many situations. Technically, it is much harder to obtain the entire distribution information than only part of the distribution information such as mean and standard deviation of G. Scarf [

In 1993, Gallego and Moon [

Consider a family of distributions with common mean and standard deviation. Scarf’s order rule is based upon the least favorable distribution in the family, which minimizes the objective function for any given Q. However, there are infinite distributions with common mean and standard deviation in and each distribution has its optimal solution. Therefore if we can obtain a tight range of the optimal solutions in family and find the relationship between the Scarf’s rule and this range, we can better understand the distribution free Newsboy problem and the demand distribution information’s value. The question of the tight range of optimal order quantities for all distributions in the family is answered by the following theorem.

Theorem. For any, the optimal order quantity G^{*} must be between the tight range [Q_{l}, Q_{u}] where the lower bound is

and the upper bound is

Coincidently, Scarf’s order rule is the midpoint of this tight optimal solution range.

In our previous research [

Proof: For a cumulative distribution, if Q^{*} is the optimal order quantity which minimizes C(Q) in (2), then Q^{*} must satisfy the relation that the first derivative of C(Q) is zero. We have

If demand D is a continuous random variable, Q^{*} satisfies (5) when the first derivative of (4) is set to be zero. We have

That is,

When D is discrete, for general G(D), Q^{*} is an optimal order quantity if and only if either

or

, , (7)

where > 0. In general, no matter D is continuous or discrete, the necessary condition of the optimal order quantity is

To determine the range of optimal order quantities, it is equivalent to find the smallest (and the largest) Q^{*} which satisfies condition (8), and simultaneously show that the distribution G is in. To find such a smallest Q^{*}, we have the following optimization formulation:

s.t.

It is easy to verify that for a two point distribution with weight [m/(m + d)] on Q_{l} and weight [d/(m + d)] on Q_{u} any Q between Q_{l} and Q_{u} is an optimal solution since it satisfies condition (7}). Therefore Q_{l} and Q_{u} are two achievable optimal order quantities. We now prove that an optimal Q^{*} can not be outside of [Q_{l}, Q_{u}]. Assume that (Q_{l} –) (where > 0) is an optimal order quantity for a cumulative distribution function, from (10) we have

From (11) we have

Also,

From (12) we have

and

From (13), (14), (15), (16), and (17), the cumulative distribution function G_{1}(D) must simultaneously satisfy:

and

We have

According to (18) and (19), we have

and

Use the fact that

combine with (22) and (23), (21) becomes

This contradicts (20). Therefore Q_{l} –(with >0) cannot be an optimal order quantity for. Similarly, we can prove that optimal order quantity cannot be larger than Q_{u}. To prove this optimal solution range is a tight range, we consider a two point distribution with the weight of [m/(d + m)] at point Q_{l} and weight of [d/(d + m)] at point Q_{u}, we can easily verify that this two point distribution is in the family of, and has the optimal solution at any point between Q_{l} and Q_{u}.

To obtain a distribution free, and robust order quantity based upon the range of optimal order quantities of [Q_{l}, Q_{u}], one can simply use the average of Q_{l} and Q_{u}. We can see that the robust order quantity is exactly the same as Scarf’s order quantity. Therefore, Scarf’s order quantity is not only the solution of the min-max approach, but also the mid-point of the range of optimal order quantities. This provides an added dimension of our understanding of Scarf’s order rule as the optimal rule based on a distribution free procedure.

This Research provides a new direct proof of the tight range of the optimal solution range for the Newsboy problem with only demand distribution mean and standard deviation available. This new proof only uses the definition of the optimal solution. The Scarf’s order rule turns out to be the midpoint of this tight range and which is another indicator of the robustness of the Scarf’s rule. In practice, if only the demand distribution mean and standard deviation are available, we can find the upper and lower bounds of the optimal solution range and compare them with the Scarf’s rule. If the range is not too large, order decision by Scarf’s rule will be a good decision. If the range is very large, Scarf’s rule will be very risky and it is recommended to obtain the entire distribution information to decide the order quantity.