We develop a reserve design strategy to maximize the probability of species persistence predicted by a stochastic, individual-based, metapopulation model. Because the population model does not fit exact optimization procedures, our strategy involves deriving promising solutions from theory, obtaining promising solutions from a simulation optimization heuristic, and determining the best of the p...

In this paper, the sustainability of public debt is interpreted as the result of the interaction of fiscal policy with the economic environment, and not as a statistical concept as in most of the recent literature. If debt must not explode over time, policy makers have to respond to the changing conditions in the macroeconomic environment. This paper defines the conditions which will ensure com...

This bulletin is based on research conducted by Professor Gavin Wood and Dr Melek Cigdem at the AHURI Research Centre—RMIT University, and Ms Deb Batterham and Professor Shelley Mallett at Hanover Welfare Services. The research examined, for the first time, the geography of homelessness in Australia and its relationship to potential structural drivers of homelessness (specifically housing and l...

The Steiner tree problem with revenues, budget and hop constraints is a variant of the Steiner tree problem where, besides the costs associated with arcs, there are also revenues associated with the vertices. Budget and hop constraints impose limits on the total cost of the network and on the number of edges between any vertex and the root, respectively. This article introduces and compares sev...

We consider the problem of optimizing an expensive objective function when a finite budget of total evaluations is prescribed. In that context, the optimal solution strategy for Bayesian optimization can be formulated as a dynamic programming instance. This results in a complex problem with uncountable, dimension-increasing state space and an uncountable control space. We show how to approximat...

By exploring of the multi-stage network design problem of comprehensive traffic, the paper proposes a bi-level programming model with uncertain demand. The upper level problem is to maximize the consumer surplus of all demand scenarios with budget constraint. While under the network investment decisions of the upper level problem, the lower level problem is to maximize the consumer surplus of e...

We present in this paper a general decomposition framework to solve exactly adjustable robust linear optimization problems subject to polytope uncertainty. Our approach is based on replacing the polytope by the set of its extreme points and generating the extreme points on the fly within row generation or column-and-row generation algorithms. The novelty of our approach lies in formulating the ...

The strategic supply chain design problem which allows capacity shifts and budget limitations can be formulated as a linear program. Since facilities are allowed to be opened or shut down during the planning horizon, this problem is in fact a mixed integer problem. Choosing the optimal set of facilities to serve the customer demands is an NPhard combinatorial optimization problem. We present a ...