Modular architecture of the microfactories for automatic micro-assembly

The construction of a new generation of MEMS which includes micro-assembly steps in the current microfabrication process is a big challenge. It is necessary to develop new production means named micromanufacturing systems in order to perform these new assembly steps. The classical approach called “top-down” which consists in a functional analysis and a definition of the tasks sequences is insufficient for micromanufacturing systems. Indeed, the technical and physical constraints of the microworld (e.g. the adhesion phenomenon) must be taken into account in order to design reliable micromanufacturing systems. A new method of designing micromanufacturing systems is presented in this paper. Our approach combines the general “top-down” approach with a “bottom-up” approach which takes into account technical constraints. The method enables to build a modular architecture for micromanufacturing systems. In order to obtain this modular architecture, we have devised an original identification technique of modules and an association technique of modules. This work has been used to design the controller of an experimental robotic micro-assembly station.     

A heuristic to solve the synchronized log-truck scheduling problem

We present a synchronized routing and scheduling problem that arises in the forest industry, as a variation of the log-truck scheduling problem. It combines routing and scheduling of trucks with specific constraints related to the Canadian forestry context. This problem includes aspects such as pick-up and delivery, multiple products, inventory stock, multiple supply points and multiple demand points. We developed a decomposition approach to solve the weekly problem in two phases. In the first phase we use a MIP solver to solve a tactical model that determines the destinations of full truckloads from forest areas to woodmills. In the second phase, we make use of two different methods to route and schedule the daily transportation of logs: the first one consists in using a constraint-based local search approach while the second one is a hybrid approach involving a constraint programming based model and a constraint-based local search model. These approaches have been implemented using COMET2.0. The method, was tested on two industrial cases from forest companies in Canada.     

A variable neighborhood descent heuristic for arc routing problems with time-dependent service costs

This paper proposes a variable neighborhood descent heuristic for solving a capacitated arc routing problem with time-dependent service costs. The problem is motivated by winter gritting applications where the timing of each intervention is crucial. The variable neighborhood descent is based on neighborhood structures that manipulate arcs or sequences of arcs. Computational results are reported on problems derived from classical capacitated arc routing problem instances. A comparison is also provided with an alternative approach where the arc routing problem is solved after being transformed into an equivalent node routing problem.     

Treatment in corrections: Martinson was wrongp.

Argues that there is a substantial body of evidence that clearly indicates that various types of interventions can reduce the recorded criminal activity of offenders and that the treatment literature is decidedly superior in terms of effectiveness, cost efficiency, and methodological rigor to the alternative, deterrence, advocated by "nothing works" proponents (e.g., R. M. Martinson, 1976). (French abstract) (60 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An efficient variable neighborhood search heuristic for very large scale vehicle routing problems

In this paper, we present an efficient variable neighborhood search heuristic for the capacitated vehicle routing problem. The objective is to design least cost routes for a fleet of identically capacitated vehicles to service geographically scattered customers with known demands. The variable neighborhood search procedure is used to guide a set of standard improvement heuristics. In addition, a strategy reminiscent of the guided local search metaheuristic is used to help escape local minima. The developed solution method is specifically aimed at solving very large scale real-life vehicle routing problems. To speed up the method and cut down memory usage, new implementation concepts are used. Computational experiments on 32 existing large scale benchmarks, as well as on 20 new very large scale problem instances, demonstrate that the proposed method is fast, competitive and able to find high-quality solutions for problem instances with up to 20,000 customers within reasonable CPU times.     

An efficient heuristic for reliability design optimization problems

This paper develops an efficient heuristic to solve two typical combinatorial optimization problems frequently met when designing highly reliable systems. The first one is the redundancy allocation problem (RAP) of series-parallel binary-state systems. The design goal of the RAP is to select the optimal combination of elements and redundancy levels to maximize system reliability subject to the system budget and to the system weight. The second problem is the expansion-scheduling problem (ESP) of multi-state series-parallel systems. In this problem, the study period is divided into several stages. At each stage, the demand is represented as a piecewise cumulative load curve. During the system lifetime, the demand can increase and the total productivity may become insufficient to assume the demand. To increase the total system productivity, elements are added to the existing system. The objective in the ESP is to minimize the sum of costs of the investments over the study period while satisfying availability constraints at each stage. The heuristic approach developed to solve the RAP and the ESP is based on a combination of space partitioning, genetic algorithms (GA) and tabu search (TS). After dividing the search space into a set of disjoint subsets, this approach uses GA to select the subspaces, and applies TS to each selected subspace. Numerical results for the test problems from previous research are reported and compared. The results show the advantages of the proposed approach for solving both problems.     

Improvement of the position resolution of the CCD for X-ray use

The authors report here experimental results relating X-ray interaction location and event splitting. The X-ray interaction location can be localized at subpixel scale using the mesh technique. The authors found that the center of gravity of the split event is well-correlated with the X-ray interaction location. They analyzed the data using two models for the charge cloud shape: one is the rectangular model and the other is the Gaussian model. Although the authors could not distinguish between these models, they measured a root mean square charge cloud size of 1 to 2 μm for X-rays of Y-L (1.9 keV), Ag-L (3.0 keV), and Ti-K (4.5 keV). When the X-rays enter near the pixel boundary, the charge splits into adjacent pixels, allowing determination of the X-ray interaction location with an accuracy of 1.5 to 2.2 μm. The authors, therefore, expect that the X-ray CCD can function as an X-ray imager with subpixel resolution, which will be especially useful in applications involving very high spatial resolution optics     

Efficient heuristics for the design of ring networks

In telecommunications, the Ring Design Problem (RDP) lies at the heart ofmetropolitan area network design. We propose an integer programming formulation for the RDP, as well as several ring construction and post-optimization heuristics. These heuristics are tested and compared on a series of test problems.     

Synchronous tabu search parallelization strategies for multicommodity location-allocation with balancing requirements

We study and compare synchronous parallelization strategies for tabu search. We identify the most promising parallelization approaches, and evaluate the impact on performance and solution quality of some important algorithmic design parameters: length of the synchronization steps, number of processors, handling of exchanged information, etc. Parallelization approaches are implemented and compared by using a tabu search algorithm for multicommodity location-allocation problems with balancing requirements.     

Centralized and decentralized stochastic routing models in telecommunication networks

With the advent of non-hierarchical routing in circuit-switched telecommunication networks, on-line routing policies have been developed with the objective of optimizing some measure of gain or performance. These policies are decentralized. However, traditional planning models are centralized models. We present a decentralized routing model to be used in network planning. We compare it theoretically and empirically with a centralized multicommodity flow model previously presented. The two models are solved by the same type of algorithm, a convex simplex implementation, adapted differently according to the model. Comparative results between planning models reproducing the two policies are discussed.