Abstract
This paper presents a hybrid tabu search strategy for lot sizing problems. This strategy allows the exploitation of the quality of the well-known relax-and-fix heuristic, inside a tabu search framework which enforces diversity. The computational results show an advantage of this strategy when compared to a version of the relax-and-fix heuristic and to time constrained branch-and-bound.

Abstract
Number partitioning is a classical NP-hard combinatorial optimization problem, whose solution is challenging for both exact and approximative methods. This work presents a new algorithm for number partitioning, based on ideas drawn from tree search, breadth first search, and beam search. A new set of benchmark instances for this problem is also proposed. The behavior of the new method on this and other testbeds is analyzed and compared to other well known heuristics and exact algorithms.

Abstract
Sparse coding is an important optimization problem with numerous applications. In this paper, we describe the problem and the commonly used pursuit methods, and propose a best-first tree search algorithm employing multiple queues for unexplored tree nodes. We assess the effectiveness of our method in an extensive computational experiment, showing its superiority over other methods even for modest computational time. © 2012 Springer-Verlag.

Abstract
In this paper we present the framework Abstraction-Carrying CodE Platform for Timing validation (ACCEPT), designed for timing analysis of embedded real-time systems using the worst-case execution time (WCET) as the safety parameter. In the context of real-time embedded code safety, we describe in detail the component responsible for generating and checking the WCET certificates. In particular, the checking mechanism is efficiently designed so that code consumers can autonomously verify that the received code meet theirs internal real-time requirements. The certificate generation/checking mechanism is inspired in the Abstraction-Carrying Code framework and implemented using Abstract Interpretation and Linear Programming. © 2012 Springer-Verlag.

Abstract
One of the most important, applications of the Asymmetric Hamiltonian Path Problem is in scheduling. In this paper we describe a variant of this problem, and develop 1)011) a mathematical programming formulation and simple metaheuristics for solving it The formulation is based on a transformation of the input, data, in such a way that a standard mathematical programming model for the Asymmetric: Travelling Salesman Problem can be used on this slightly different problem. Two standard metaheuristics for the asymmetric travelling salesman are proposed and analysed on this variant: repeated random construction followed by local search with the 3-Exchange neighbourhood. and iterated local search based on the same neighbourhood and on a 4-Exchange perturbation. The computational results obtained show the interest, and the complementary merits of using a mixed-integer programming solver and an approximative method for the solution of this problem.

Abstract
In many sectors of industry, manufacturers posses warehouses where finished goods are stored, awaiting to fulfill a client order. We present a situation where these items are characterized by release and due dates, i.e. warehouse arrival for storage and client delivery, respectively. The warehouse has a number of positions available, where item can be placed on top of each other, forming stacks, For item manipulation, there is a single a stacking crane, able to carry one item at time. When in a given stack an item at the top is due at a date later than some item below it, it must be relocated to another stack, so that the item below can be delivered. In this problem the objective is to minimize the number of movements made by the crane.