FROM A MODEL OF CONCURRENCY TO A TEST MODEL: A GRAPH TRANSFORMATION BASED APPROACH

Maximality-based Labeled Transition Systems (MLTS) is semantic model for true concurrency. In other hand Mixed Refusal Graphs  (MRG)  are models  for  formal  testing.  In  this  paper, we  propose  an  approach  to  transform  an MLTS model  to  an equivalent  MRG  model.  Since  the  input  and  output  models  are  graphs,  we  use  graph  transformation  to  perform  this transformation automatically. So, we propose  two meta-models; one for the input model and the other for the output model. Then,  based  on  these meta-models we  propose  a  graph  grammar  that  deals with  the  transformation  process.    The meta-modeling tool ATOM3 is used. Our approach is illustrated through an example

A Tabu Search Algorithm with Direct Representation for Strip Packing

Date du colloque&nbsp;: 04/2009International audienceThis paper introduces a new tabu search algorithm for a two-dimensional (2D) Strip Packing Problem (2D-SPP). It integrates several key features: A direct representation of the problem, a satisfaction-based solving scheme, two different complementary neighborhoods, a diversification mechanism and a particular tabu structure. The representation allows inexpensive basic operations. The solving scheme considers the 2D-SPP as a succession of satisfaction problems. The goal of the combination of two neighborhoods is (to try) to reduce the height of the packing while avoiding solutions with (hard to fill) tall and thin wasted spaces. Diversification relies on a set of historically “interesting” packings. The tabu structure avoids visiting similar packings. To assess the proposed approach, experimental results are shown on a set of well-known benchmark instances and compared with previously reported tabu search algorithms as well as the best performing algorithms.</p

Queue-constrained packing: a vehicle ferry case study

We consider the problem of loading vehicles onto a ferry. The order in which vehicles arrive at the terminal can have a significant impact on the efficiency of the packing on the ferry as it may not be possible to place a vehicle in an optimal location if it is not at the front of one of the dockside queues at the right point in the loading process. As the arrival order of vehicles is stochastic, we model the loading process as a two-stage stochastic optimization problem where the objective is to reduce penalties incurred by failing to pack booked vehicles. The first stage consists of optimizing the yard policy for allocating vehicles to dockside queues while the second stage solves the packing problem for a realisation of the arrival process using the yard policy determined in stage one. A novel stage-wise iterative metaheuristic is introduced, which alternates between packing optimization for each of a training set of scenarios whilst fixing the yard policy and optimizing the yard policy whilst fixing the packing solutions. We introduce two novel packing encoders for the second stage packing problem. Termed Sequential Block Packing Encode (SOPE) and General Packing Encoder (GPE), the arrangements they produce are designed to be efficient and easy to implement for loading staff. Results show that the number of yard queues available is critical to the efficiency of the packing on board the ferry