Robust multi-market newsvendor models with interval demand data

We present a robust model for determining the optimal order quantity and market selection for short-life-cycle products in a single period, newsvendor setting. Due to limited information about demand distribution in particular for short-life-cycle products, stochastic modeling approaches may not be suitable. We propose the minimax regret multi-market newsvendor model, where the demands are only known to be bounded within some given interval. In the basic version of the problem, a linear time solution method is developed. For the capacitated case, we establish some structural results to reduce the problem size, and then propose an approximation solution algorithm based on integer programming. Finally, we compare the performance of the proposed minimax regret model against the typical average-case and worst-case models. Our test results demonstrate that the proposed minimax regret model outperformed the average-case and worst-case models in terms of risk-related criteria and mean profit, respectively.     

On the comparison of risk-neutral and risk-averse newsvendor problems

The objective of this paper is to investigate and compare the relationship between risk-neutral and risk-averse newsvendor problems under three different decision criteria: expected utility (EU) maximization, mean-variance (MV) analysis, and conditional value-at-risk (CVaR) minimization. Several models in the literature have shown that for special cases of the newsvendor problem (eg, no salvage value, no shortage penalty, and with recourse option), a risk-averse newsvendor orders less than a risk-neutral newsvendor. First, we present an observation about the EU maximization models with such special cases where a risk-averse newsvendor orders less than a risk-neutral one. We note that this observation does not extend to the newsvendor problem with positive shortage penalty. Using several counterexamples, we demonstrate that the common wisdom that a risk-averse newsvendor orders less than a risk-neutral newsvendor is not true in general. Second, we demonstrate, analytically where possible and numerically if not, that the comparison of the optimal order quantities of risk-neutral and risk-averse newsvendors depends on the key assumptions regarding the model inputs, namely, the decision criterion, the demand distribution and the cost parameters such as shortage penalty and unit ordering cost. Third, we show that EU and the MV criteria yield consistent results while EU and CVaR criteria may yield consistent or conflicting results depending on the loss function used for the CVaR criterion.     

Competitive newsvendor problems with the same Nash and Stackelberg solutions

Consider two newsvendors: (i) they compete satisfying substitutable demands searching Nash equilibrium or (ii) one is the leader deciding first, the other responds optimally playing a Stackelberg game. The leader profits more than she does in (i). We present conditions under which the leader's profit does not improve from (i) to (ii).     

Dispatch planning using newsvendor dual problems and occupation times: Application to hydropower

We consider price-driven dispatch planning under price uncertainty: A storable commodity is optimally sold and purchased over time. First, we consider models where the storage level is constrained in expectation. The dual of the corresponding optimization problem is related to the newsvendor problem. Exact solutions of bang-bang type are given. The second methodology is for high-frequency dispatch decisions in multistage stochastic programming models: To overcome the curse of dimensionality, prices are modeled by occupation times at price levels. In a case study, we consider a pumped-storage hydropower plant: Numerical solutions are given, which have similar patterns as for the first, exactly solvable problems.     

Superlinear discrete problems

The aim of this paper is to present an existence result of two positive solutions for a nonlinear difference problem by variational methods. The conclusion is achieved by assuming, together with the super-linearity at infinity, a suitable algebraic condition on the nonlinear term, which is more general than the sub-linearity at zero.     

A discrete time inventory system with postponed demands

In this article, we consider a discrete-time inventory model in which demands arrive according to a discrete Markovian arrival process. The inventory is replenished according to an (s,S)$(s,S)$ policy and the lead time is assumed to follow a discrete phase-type distribution. The demands that occur during stock-out periods either enter a pool which has a finite capacity N(<∞)$N(<\infty )$ or leave the system with a predefined probability. Any demand that arrives when the pool is full and the inventory level is zero, is assumed to be lost. The demands in the pool are selected one by one, if the on-hand inventory level is above s+1$s+1$, and the interval time between any two successive selections is assumed to have discrete phase-type distribution. The joint probability distribution of the number of customers in the pool and the inventory level is obtained in the steady state case. The measures of system performance in the steady state are derived and the total expected cost rate is also calculated. The results are illustrated numerically.     

The effect of supply uncertainty in price-setting newsvendor models

We consider a price-setting newsvendor model in which a firm needs to make joint inventory and pricing decisions before the selling season. The supply process is uncertain such that the received quantity is the product of the order quantity and a random yield rate. Two cost structures are investigated, the in-house production case in which the firm pays for the input quantity and the procurement case in which the firm pays for the quantity received only. Our objective is to investigate the effect of yield randomness on optimal decisions and expected profit. By using the theory of stochastic comparisons, we find that under both cost structures, a less variable yield rate leads to a lower optimal price and a higher expected profit. Moreover, we show that in the in-house production case, a stochastically larger yield rate also results in a lower optimal price and a higher profit, but this is not true in the procurement case. Examples show that the effect of supply uncertainty on optimal order quantity is not universal.     

Robust discrete optimization and network flows

We propose an approach to address data uncertainty for discrete optimization and network flow problems that allows controlling the degree of conservatism of the solution, and is computationally tractable both practically and theoretically. In particular, when both the cost coefficients and the data in the constraints of an integer programming problem are subject to uncertainty, we propose a robust integer programming problem of moderately larger size that allows controlling the degree of conservatism of the solution in terms of probabilistic bounds on constraint violation. When only the cost coefficients are subject to uncertainty and the problem is a 0–1 discrete optimization problem on n variables, then we solve the robust counterpart by solving at most n+1 instances of the original problem. Thus, the robust counterpart of a polynomially solvable 0–1 discrete optimization problem remains polynomially solvable. In particular, robust matching, spanning tree, shortest path, matroid intersection, etc. are polynomially solvable. We also show that the robust counterpart of an NP-hard -approximable 0–1 discrete optimization problem, remains -approximable. Finally, we propose an algorithm for robust network flows that solves the robust counterpart by solving a polynomial number of nominal minimum cost flow problems in a modified network. The research of the author was partially supported by the Singapore-MIT alliance.The research of the author is supported by a graduate scholarship from the National University of Singapore.Mathematics Subject Classification (2000): 90C10, 90C15     

Nonlinear discrete Sturm-Liouville problems

In this paper we study nonlinear boundary value problems of the form

     

The effect of demand uncertainty in a price-setting newsvendor model

We study the effects of demand uncertainty on optimal decisions and the expected profit of a price-setting newsvendor who faces either additive or multiplicative stochastic demand. Our key findings are as follows. (1) A stochastically larger demand may even lead to a smaller order size and a lower profit when price is endogenous. (2) A stochastically larger demand will lead to a higher selling price in general for the additive demand case but to a lower selling price under certain mild conditions for the multiplicative demand case. Moreover, if the larger demand can be represented by a transformation of the lower one, it will lead to a higher expected profit for both demand cases. However, except for the setting with a zero shortage cost, a larger demand may not necessarily result in a higher expected profit in general. (3) Under mild conditions, a less variable demand will lead to a higher and lower selling price for the additive and multiplicative demand case, respectively, and a higher expected profit for both cases.     

The discrete picard condition for discrete ill-posed problems

We investigate the approximation properties of regularized solutions to discrete ill-posed least squares problems. A necessary condition for obtaining good regularized solutions is that the Fourier coefficients of the right-hand side, when expressed in terms of the generalized SVD associated with the regularization problem, on the average decay to zero faster than the generalized singular values. This is the discrete Picard condition. We illustrate the importance of this condition theoretically as well as experimentally.This work was carried out during a visit to Dept. of Mathematics, UCLA, and was supported by the Danish Natural Science Foundation, by the National Science Foundation under contract NSF-DMS87-14612, and by the Army Research Office under contract No. DAAL03-88-K-0085.     

Solving problems of discrete tomography

This is a summary of the most important results presented in the author's PhD thesis. This thesis, written in French, was defended on 24 November 2004 and supervised by Marie-Christine Costa and Christophe Picouleau. This thesis consists in developing the study of discrete tomography problems. It aims at reconstructing discrete objects (matrices, images, discrete sets, etc) that are accessible only through few projections. A copy of the thesis is available on "http: //cedric.cnam.fr/AfficheArticle.php?id = 698". Received: April 2005 AMS classification: 90B70, 68Q17, 52C15, 05B50     

Vector network equilibrium problems with elastic demands

We consider vector models for complex systems with spatially distributed elements which arise in communication and transportation networks. In order to describe the flow distribution within such a network, we utilize the equilibrium approach, which extends the shortest path one. Being based on this approach, we investigate several networking control problems, with taking into account many factors. As a result, general vector equilibrium problems models with complex behavior of elements are suggested. In particular, they involve elastic demand functions. Due to the presence of many factors, we utilize multicriteria models with respect to different preference relations. The corresponding problems admit efficient solution methods within optimization and equilibrium frameworks.     

Sharp discrete inequalities and applications to discrete variational problems

Some new discrete inequalities involving monotonic or convex functions are obtained. While these are interesting inequalities in their own right, they can be applied to solving certain types of discrete variational problems effectively.     

On constant discrete programming problems

Let H be a subset of the set S_n of all permutations

$\text{1}\text{2}\text{???}\text{n}\text{s(1)}\text{s(2)}\text{???}\text{s(n)}$

C=6c_ij6 a real n?n matrix L_c(s)=c_1s(1)+c_2s(2)+???+c_ns(n) for s ? H. A pair (H, C) is the existencee of reals a₁,b₁,a₂,b₂,…a_n,b_n, for which c_ij=a₁+b_j if (i,j)?D(H), where D(H)={(i,j):(?h?H)(j=h(i))}.For a pair (H,C) the specifity of it is proved in the case, when H is either a special cyclic class of permutations or a special union of cyclic classes. Specific pairs with minimal sets H are in some sense described.     

Solving discrete zero point problems

In this paper we present two theorems on the existence of a discrete zero point of a function from the n-dimensional integer lattice ℤⁿ to the n-dimensional Euclidean space ℝⁿ. The theorems differ in their boundary conditions. For both theorems we give a proof using a combinatorial lemma and present a constructive proof based on a simplicial algorithm that finds a discrete zero point within a finite number of steps. This research was carried out when Gerard van der Laan and Zaifu Yang were visiting the CentER of Tilburg University in the summer of 2004. The visit of Zaifu Yang has been made possible by financial support of CentER and the Netherlands Organization for Scientific Research (NWO). The authors gratefully acknowledge the inspiring and helpful remarks of the referees.     

Some problems in discrete optimization

The present paper concentrates on several problems of network flows and discrete optimization. Progress has been made on some of the problems while little is known about others. Some of the problems discussed are shortest paths, multi-commodity flows, traveling salesman problems, m-center problem, telepak problems and binary trees.This paper was presented at the 7th Mathematical Programming Symposium 1970, The Hague, The Netherlands.Sponsored by the United States Army under Contract No.: DA-31-124-ARO-D-462 and the National Science Foundation, GJ-28339.     

Eigenvalue problems for anisotropic discrete boundary value problems

In this paper, we prove the existence of a continuous spectrum for a family of discrete boundary value problems. The main existence results are obtained by using critical point theory. The equations studied in the paper represent a discrete variant of some recent anisotropic variable exponent problems, which deserve as models in different fields of mathematical physics.