Detection of low molecular weight toxins using an optical phase method of ellipsometry

The method of total internal reflection ellipsometry (TIRE), which records simultaneously two parameters Δ and Ψ related to the amplitudes and phases of p- and s-components of polarised light, respectively, was exploited here for detection of mycotoxins (T-2 and zearalenone). The above mycotoxins in sub-ppb concentrations were detected using TIRE in both direct and competitive immunoassay. The study of immune reaction kinetics allowed the evaluation of adsorption/desorption rates and the association constant for zearalenone. The investigation of grain products samples revealed the presence of high concentrations of T-2 (>600 ng/ml) in mould products.     

Bottleneck-based heuristics to minimize total tardiness for the flexible flow line with unrelated parallel machines

This paper considers the flexible flow line problem with unrelated parallel machines at each stage and with a bottleneck stage on the line. The objective of the problem is to minimize the total tardiness. Two bottleneck-based heuristics with three machine selection rules are proposed to solve the problem. The heuristics first develop an indicator to identify a bottleneck stage in the flow line, and then separate the flow line into the upstream stages, the bottleneck stage, and the downstream stages. The upstream stages are the stages ahead of the bottleneck stage and the downstream stages are the stages behind the bottleneck stage. A new approach is developed to find the arrival times of the jobs at the bottleneck stage. Using the new approach, the bottleneck-based heuristics develop two decision rules to iteratively schedule the jobs at the bottleneck stage, the upstream stages, and the downstream stages. In order to evaluate the performance of the bottleneck-based heuristics, seven commonly used dispatching rules and a basic tabu search algorithm are investigated for comparison purposes. Seven experimental factors are used to design 128 production scenarios, and ten test problems are generated for each scenario. Computational results show that the bottleneck-based heuristics significantly outperform all the dispatching rules for the test problems. Although the effective performance of the bottleneck-based heuristics is inferior to the basic tabu search algorithm, the bottleneck-based heuristics are much more efficient than the tabu search algorithm. Also, a test of the effect of the experimental factors on the dispatching rules, the bottleneck-based heuristics, and the basic tabu search algorithm is performed, and some interesting insights are discovered.     

Genetic algorithm-based heuristics for an open shop scheduling problem with setup,processing, and removal times separated

This report proposes a solution to the open shop scheduling problem with the objective of minimizing total job tardiness in the system. Some practical processing restrictions, such as independent setup and dependent removal times, are taken into account as well. The addressed problem is first described as a 0–1 integer programming model, and is then solved optimally. Subsequently, some hybrid genetic-based heuristics are proposed to solve the problem in an acceptable computation time. To demonstrate the adaptability of these heuristics, some performance comparisons are made with solutions provided by running either a mathematical programming model or certain classic meta-heuristics such as genetic algorithm, simulated annealing, and tabu search in various manufacturing scenarios. The experimental results show that the hybrid genetic-based heuristics perform well, especially the DGA. However, these heuristics require some more additional computations but are still acceptable.     

Some First-Order Algorithms for Total Variation Based Image Restoration

This paper deals with first-order numerical schemes for image restoration. These schemes rely on a duality-based algorithm proposed in 1979 by Bermùdez and Moreno. This is an old and forgotten algorithm that is revealed wider than recent schemes (such as the Chambolle projection algorithm) and able to improve contemporary schemes. Total variation regularization and smoothed total variation regularization are investigated. Algorithms are presented for such regularizations in image restoration. We prove the convergence of all the proposed schemes. We illustrate our study with numerous numerical examples. We make some comparisons with a class of efficient algorithms (proved to be optimal among first-order numerical schemes) recently introduced by Y. Nesterov.     

基于结构张量的自适应CTV彩色图像恢复模型

讨论一种基于非线性扩散方程的彩色图像去噪方法。在图像去噪的3个基本要求的基础上,总结出调和项模型和彩色总变差去噪模型中的不足,利用图像的局部信息构造函数使得模型在接近图像边缘处各向异性平滑并保持边界。在平坦区域各向同性平滑,防止阶梯效应的产生,并利用角点信息保持了角点形状。实验结果表明,所建模型能够较好地保持图像中目标的几何结构,同时具有良好的去噪能力。     

TV改进算法及其在人脸识别中的应用

针对传统全变分（TV）模型在测试过程中存在的问题,将弹性网引入TV模型中,采用二次多项式对TV模型所丢弃的人脸低频信息进行光照归一化处理,并提取图像的高频信息,在YaleB图像库中测试其性能,仿真实验结果表明,相对于TV模型,TV＋二次多项式模型能够有效提高图像识别率。     

Scheduling a batching machine with convex resource consumption functions

In various industries jobs undergo a batching, or burn in, process where different tasks are grouped into batches and processed simultaneously. The processing time of each batch is equal to the longest processing time among all jobs contained in the batch. All to date studies dealing with batching machines have considered fixed job processing times. However, in many real life applications job processing times are controllable through the allocation of a limited resource. The most common and realistic model assumes that there exists a non-linear and convex relationship between the amount of resource allocated to a job and its processing time. The scheduler?s task when dealing with controllable processing times is twofold. In addition to solving the sequencing problem, one must establish an optimal resource allocation policy. We combine these two widespread models on a single machine setting, showing that both the makespan and total completion time criteria can be solved in polynomial time. We then show that our proposed approach can be applied to general bi-criteria objective comprising of the makespan and the total completion time.     

Note on “Unrelated parallel-machine scheduling with deteriorating maintenance activities”

In this note, we prove that both problems studied by Cheng et al. [Cheng, T. C. E., Hsu, C.-J., & Yang, D.-L. (2011). Unrelated parallel-machine scheduling with deteriorating maintenance activities. Computers and Industrial Engineering, 60, 602–605] can be solved in O(n^m+3) time no matter what the processing time of a job after a maintenance activity is greater or less than its processing time before the maintenance activity, where m is the number of machines and n is the number of jobs.     

Bi-criteria minimization for the permutation flowshop scheduling problem with machine-based learning effects

In traditional scheduling problems, the processing time for the given job is assumed to be a constant regardless of whether the job is scheduled earlier or later. However, the phenomenon named “learning effect” has extensively been studied recently, in which job processing times decline as workers gain more experience. This paper discusses a bi-criteria scheduling problem in an m-machine permutation flowshop environment with varied learning effects on different machines. The objective of this paper is to minimize the weighted sum of the total completion time and the makespan. A dominance criterion and a lower bound are proposed to accelerate the branch-and-bound algorithm for deriving the optimal solution. In addition, the near-optimal solutions are derived by adapting two well-known heuristic algorithms. The computational experiments reveal that the proposed branch-and-bound algorithm can effectively deal with problems with up to 16 jobs, and the proposed heuristic algorithms can yield accurate near-optimal solutions.     

Exact and heuristic algorithms for the aerial refueling parallel machine scheduling problem with due date-to-deadline window and ready times

The Aerial Refueling Scheduling Problem (ARSP) can be defined as determining the refueling completion times for fighter aircrafts (jobs) on multiple tankers (machines) to minimize the total weighted tardiness. ARSP can be modeled as a parallel machine scheduling with ready times and due date-to-deadline window to minimize total weighted tardiness. ARSP assumes that the jobs have different ready times and a due date-to-deadline window between refueling due date and a deadline to return without refueling. In this paper, we first formulate the ARSP as a mixed integer programming model. The objective function is a piece-wise tardiness cost that takes into account due date-to-deadline windows and job priorities. Since ARSP is NP-hard, two heuristics are proposed to obtain solutions in reasonable computation times, namely (1) modified ATC rule (MATC), (2) a simulated annealing method (SA). The proposed heuristic algorithms are tested in terms of solution quality and CPU time through computational experiments with data randomly generated to represent aerial refueling operations of an in-theater air operation. Solutions provided by both algorithms were compared to optimal solutions for problems with up to 12 jobs and to each other for larger problems with up to 60 jobs. The results show that, MATC is more likely to outperform SA especially when the problem size increases, although it has significantly worse performance than SA in terms of deviation from optimal solution for small size problems. Moreover CPU time performance of MATC is significantly better than SA in both cases.