Operational models often balance assignment and capacity decisions under data uncertainty. For example, in operating room scheduling the decision maker must define appropriate limits for personnel overtime while accounting for random surgery durations. Typical approaches to hedge against...

Many of the analyses of time series that arise in real-life situations require the adoption of various simplifying assumptions so as to cope with the complexity of the phenomena under consideration. Whilst accepting that these simplifications lead to heuristics providing less accurate processing...

We consider optimization problems for minimizing conditional value-at-risk (CVaR) from a computational point of view, with an emphasis on financial applications. As a general solution approach, we suggest to reformulate these CVaR optimization problems as two-stage recourse problems of...

The allocation of a specific amount of a given resource among competitive alternatives can often be modelled as a knapsack problem. This model formulation is extremely efficient because it allows convex cost representation with bounded variables to be solved without great computational efforts....

From personal interest and also on behalf of the Mathematical Programming Society I have been trying to keep afloat in the flood of writing that followed Khachian's "Polynomial Time Algorithm for Linear Programming" (Khachian, L. G. 1979. A polynomial algorithm in linear programming. Dokl. Akad....

This paper deals with a mathematical model designed to provide guidelines for managing a land resource over an extended period of time. We develop a framework which permits sequences of management decisions to be conveniently formulated, and their associated costs and benefits specified. This...