For the problem of lot-sizing on a tree with constant capacities, or stochastic lot-sizing with a scenario tree, we present various reformulations based on mixing sets. We also show how earlier results for uncapacitated problems involving (Q,SQ) inequalities can be simplified and extended. Finally some limited computational results are presented.

We introduce an automata-theoretic approach for the verification of multi-agent systems. We present a translation between branching time temporal-epistemic logic and alternating tree automata. Model checking an interpreted system against a temporal-epistemic formula is reduced to checking the non-emptiness of the composition of two tree automata. We exemplify this technique using a simple multi...

This paper addresses the minimax regret sink location problem in dynamic tree networks. In our model, a dynamic tree network consists of an undirected tree with positive edge lengths and uniform edge capacity, and the vertex supply which is a positive value is unknown but only the interval of supply is known. A particular realization of supply to each vertex is called a scenario. Under any scen...

One of the central issues for information extraction is the cost of customization from one scenario to another. Research on the automated acquisition of patterns is important for portability and scalability. In this paper, we introduce Tree-Based Pattern representation where a pattern is denoted as a path in the dependency tree of a sentence. We outline the procedure to acquire Tree-Based Patte...

The objective was to investigate the error sources of the airborne laser scanning based individual tree detection (ITD), and its effects on forest management planning calculations. The investigated error sources were detection of trees (etd), error in tree height prediction (eh) and error in tree diameter prediction (ed). The effects of errors were analyzed with Monte Carlo simulations. etd was...

A crucial issue for addressing decision-making problems under uncertainty is the approximate representation of multivariate stochastic processes in the form of scenario tree. This paper proposes a scenario generation approach based on the idea of integrating simulation and optimization techniques. In particular, simulation is used to generate outcomes associated with the nodes of the scenario t...

A challenging aspect of applying stochastic programming in a dynamic setting is to construct a set of discrete scenarios that well represents multivariate stochastic processes for uncertain parameters. Often this is done by generating a scenario tree using a statistical procedure and then reducing its size while maintaining its statistical properties. In this paper, we test a new scenario reduc...

In this paper, we propose a new approach to reduce the total running time (RT) of the progressive hedging algorithm (PHA) for solving multistage stochastic programs (MSPs) defined on a scenario tree. Instead of using the conventional scenario decomposition scheme, we apply a multi-scenario decomposition scheme and partition the scenario set in order to minimize the number of non-anticipativity ...