Abstract
In the concurrency theory, various semantic equivalences on transition systems are based on traces decorated with some additional observations, generally referred to as decorated traces. Using the generalized powerset construction, recently introduced by a subset of the authors (Silva et al. 2010 FSTTCS. LIPIcs 8 272-283), we give a coalgebraic presentation of decorated trace semantics. The latter include ready, failure, (complete) trace, possible futures, ready trace and failure trace semantics for labelled transition systems, and ready, (maximal) failure and (maximal) trace semantics for generative probabilistic systems. This yields a uniform notion of minimal representatives for the various decorated trace equivalences, in terms of final Moore automata. As a consequence, proofs of decorated trace equivalence can be given by coinduction, using different types of (Moore-) bisimulation (up-to context).

Abstract
Attribute Grammars are a powerfull, well-known formalism to implement and reason about programs which, by design, are conveniently modular. In this work we focus on a state of the art Zipper-based embedding of Attribute Grammars and further improve its performance through controlling attribute (re)evaluation by using memoization techniques. We present the results of our optimization by comparing their impact in various implementations of different, well-studied Attribute Grammars.

Abstract
Many stochastic search algorithms require relearning if the task changes slightly to adapt the solution to the new situation or the new context. Therefore in this research, we investigate the contextual stochastic search algorithms that can learn from multiple tasks simultaneously. Here, we want to find good parameter vectors for multiple related tasks, where each task is described by a continuous context vector. Hence, the objective function might change slightly for each parameter vector evaluation.

Abstract
This article presents the impacts of different storage technologies, their size as well as their location on the economic dispatch of a distribution system. The participation of the storage in distribution systems is evaluated over a period of 24 hours using a radial reconfiguration of the network. In order to meet this objective, a stochastic mixed integer linear problem (SMILP) is proposed, where the expected cost during the operation period is minimized. The model considers uncertainties in wind generation, load which is represented through a typical demand profile, conventional generation and storage systems. Results from a case study is presented for a distribution network with 28 buses, comprehensively describing the impacts of the location and the size of the storage system on the distribution network, as well as on the expected operation costs of the system.

Abstract

Abstract
Transmission Expansion Planning (TEP) is a complex optimization problem that has the purpose of determining how the transmission capacity of a network should be enlarged, satisfying the increasing demand. This problem has combinatorial nature and different alternative plans can be designed so that many algorithms can converge towards local optima. This feature drives the development of tools that combine high robustness and low computational effort. This paper presents a comparative analysis and a detailed review of the main Constructive Heuristic Algorithms (CHA) used in the TEP problem. This kind of tools combine low computational effort with reasonable quality solutions and can be associated with other tools to use in a subsequent step in order to improve the final solution. CHAs proved to be very effective and showed good performance as the test results will illustrate.