This paper demonstrates that a class of two-person games with ratio payoff functions can be solved using equivalent primal-dual linear programming formulations. The game's solution contains specialized information which may be used to conduct the efficiency evaluation currently done by the CCR...

This paper develops an order-up-to S inventory model that is designed to handle multiple items, resource constraints, lags in delivery, and lost sales without sacrificing computational simplicity. Mild conditions are shown to ensure that the expected average holding cost and the expected average...

Traditional sensitivity analysis in linear programming usually focuses on variations of one coefficient or term at a time. The tolerance approach was proposed to provide a decision maker with an effective and easy-to-use method to summarize the effects of simultaneous and independent changes in...

Sequential meta-heuristic implementations for the irregular stock-cutting problem have highlighted a number of common problems. The literature suggests a consensus that it is more efficient to allow configurations with overlapping pieces in the solution space and to penalise these in the...

The literature in the field of interior point methods for Linear Programming has been almost exclusively algorithmic oriented. Very few contributions have been made towards the theory of Linear Programming itself. In particular none of them offer a simple, self-contained introduction to the...

Merton, Perrakis and Ryan, Levy, and Ritchken have established option pricing bounds under first and second stochastic dominance preferences. These bounds are particularly important for valuing contingent claims when continuous trading in the claim and/or underlying security does not exist. This...

The purpose of this paper is to demonstrate that a portfolio optimization model using the L₁ risk (mean absolute deviation risk) function can remove most of the difficulties associated with the classical Markowitz's model while maintaining its advantages over equilibrium models. In particular,...

The Linear Programming Problem is by far the most widely used optimization model. Its impact on economic and government modeling is immense. The Simplex Method for solving the Linear Programming (LP) Problem, due to George Dantzig, has been an extremely efficient computational tool for almost...

The emphasis in this article is to exploit the fact that precision requirements for solutions of most economic models in practice are moderate only. A simple approach is introduced for solving linearly constrained partial equilibrium models based on an iterative scheme similar to the simplex...

This paper presents an effective solution strategy for an important category of personnel scheduling problems. Specifically, we address the restricted starting-time tour-scheduling problem (RSTP), which involves the determination of the hours of the day (shifts) and days of the week (days on)...