Patterns of discrimination in hiring job applicants with disabilities: The role of disability type, job complexity, and public contact.

Objective: To evaluate the effects of disability type, job complexity, and public contact on hiring decisions. Design and Participants: An Americans With Disabilities Act (ADA; 1990) fact sheet and matched resumes with vocational and medical histories including chronic mental illness, developmental disability, closed head injury, and back injury were provided to 295 undergraduate business-related majors, who rated the applicants' suitability for 2 job positions and work shifts. Results: Findings indicated disparities in ratings of employability as a function of disability type. Paired comparisons yielded complementary findings, with effects of disability type and Disability Type × Job Complexity, but no effects of public contact. Conclusions: Stereotyping and discrimination in employment decisions apparently persist, more than 10 years after the ADA. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Primal-dual Steepest-edge Method for Even-flow Harvest Scheduling Problems

The even-flow harvest scheduling problem arises when the forestry agency has evolved into a rigid non-declining even-flow policy. In this paper, we investigate model formulation and solution strategies for the even-flow harvest scheduling problem. A multiple-objective linear programming problem is formulated for even-flow harvest scheduling problems with multiple-site classes and multiple periods. The aim of this problem is to simultaneously maximize a desired harvest-volume per hectare for each period of planning horizon and the total economic return. A block diagonal constraint structure, with many sets of network sub-problems and a set of coupling constraints, is identified in this linear programming problem. A longest path method for each of network sub-problems and a primal-dual steepest-edge algorithm for the entire problem are developed. The developed algorithm has been coded in Borland C++ and implemented on a personal computer. An illustrative example is used to display the detailed procedure for the developed algorithm and a real-world case study is used to show the trade-off between desired even-flow harvest volume policy and total economic return. Results show the potential benefits of this approach.     

Modeling video sources for real-time scheduling

What is the impact of the autocorrelation of variable-bit-rate (VBR) sources on real-time scheduling algorithms? Our results show that the impact of long term, or interframe, autocorrelation is negligible, while the impact of short term, or intraframe, autocorrelation can be significant. Such results are essentially independent of the video coding scheme employed. To derive these results, video sequences are modeled as a collection of stationary subsequences called scenes. Within a scene, a statistical model is derived for both the sequence of frames and of slices. The model captures the distribution and the autocorrelation function of real-time video data. In previous work, the pseudoperiodicity of the slice level auto-correlation function made it difficult to develop a simple yet accurate model. We present a generalization of previous methods that can easily capture this pseudoperiodicity and is suited for modeling a greater variety of autocorrelation functions. By simply tuning a few parameters, the model reproduces the statistic behavior of sources with different types and levels of correlation on both the frame and the slice level.     

Infinite-horizon Scheduling Algorithms for Optimal Search for Hidden Objects

This paper considers discrete search problems in which a decision-maker has to find objects lost or hidden in a given set of locations so as to minimize the expected losses incurred. Given a chance to look for a hidden object in the same location infinitely many times, this type of problem, in contrast to standard scheduling problems, has an infinite sequence as its solution. Thus we are concerned to find an algorithm that yields an optimal solution, rather than the optimal sequence itself. Using combinatorial techniques, fast optimal algorithms for solving the problems are obtained, and optimality conditions are presented for search criteria, under which the local-search algorithms yield the global optimum.     

Petri net based process scheduling: A model of the control system of flexible manufacturing systems

In this paper, we propose a class of algorithms for the sub-optimal solution of a particular class of problems of process scheduling, particularly focusing on a case study in the area of flexible manufacturing systems (FMSs). The general class of problems we face in our approach is characterized as follows: there is a set of concurrent processes, each formed by a number of temporally related tasks (segments). Tasks are executable by alternate resource sets, different both in performance and costs. Processes and tasks are characterized by release times, due dates, and deadlines. Time constraints are also present in the availability of each resource in resource sets. It has been proven that such a problem does not admit an algorithm for an optimal solution in polynomial time. Our proposed algorithm finds a sub-optimal schedule according to a set of optimization criteria, based on task and process times (earliness, tardiness), and/or time independent costs of resources. Our approach to process scheduling is based on Timed Coloured Petri Nets. We describe the structure of the coordination and scheduling algorithms, concentrating on (i) the general-purpose component, and (ii) the application-dependent component. In particular, the paper focuses on the following issues: (i) theautomatic synthesis of Petri net models of the coordination subsystem, starting from the problem knowledge base; (ii) the dynamic behavior of the coordination subsystem, whose kernel is a High Level Petri net executor, a coordination process based on an original, general purpose algorithm; (iii) the structure of the real-time scheduling subsystem, based on particular heuristic sub-optimal multi-criteria algorithms. Furthermore, the paper defines the interaction mechanisms between the coordination and scheduling subsystems. Our approach clearly distinguishes the mechanism of the net execution from the decision support system. Two conceptually distinct levels, which correspond to two different, interacting implementation modules in the prototype CASE tool, have been defined: theexecutor and thescheduler levels. One of the outstanding differences between these levels is that the executor is conceived as a fast, efficient coordination process, without special-purpose problem-solving capabilities in case of conflicts. The scheduler, on the other hand, is the adaptive, distributed component, whose behavior may heavily depend on the problem class. If the scheduler fails, the executor is, in any case, able to proceed with a general-purpose conflict resolution strategy. Experimental results on the real-time performance of the kernel of the implemented system are finally shown in the paper. The approach described in this paper is at the basis of a joint project with industrial partners for the development of a CASE tool for the simulation of blast furnaces.     

An efficient heuristic for scheduling batches of parts in a flexible flow system

Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS—the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem—the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branch-and-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.     

The Role of Acceptance and Job Control in Mental Health, Job Satisfaction, and Work Performance.

Acceptance, the willingness to experience thoughts, feelings, and physiological sensations without having to control them or let them determine one's actions, is a major individual determinant of mental health and behavioral effectiveness in a more recent theory of psychopathology. This 2-wave panel study examined the ability of acceptance also to explain mental health, job satisfaction, and performance in the work domain. The authors hypothesized that acceptance would predict these 3 outcomes 1 year later in a sample of customer service center workers in the United Kingdom (N = 412). Results indicated that acceptance predicted mental health and an objective measure of performance over and above job control, negative affectivity, and locus of control. These beneficial effects of having more job control were enhanced when people had higher levels of acceptance. The authors discuss the theoretical and practical relevance of this individual characteristic to occupational health and performance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Stronger Complexity Result for the Single Machine Multi-Operation Jobs Scheduling Problem to Minimize the Number of Tardy Jobs

We consider the single machine multi-operation jobs scheduling problem to minimize the number of tardy jobs. Each job consists of several operations that belong to different families. In a schedule, each family of job operations may be processed in batches with each batch incurring a setup time. A job completes when all of its operations have been processed. The objective is to minimize the number of tardy jobs. In the literature, this problem has been proved to be strongly NP-hard for arbitrary due-dates. We show in this paper that the problem remains strongly NP-hard even when the due-dates are common and all jobs have the same processing time.     

Proactive resource allocation for asynchronous real-time distributed systems in the presence of processor failures

We present two proactive resource allocation algorithms, RBA^*-FT and OBA-FT, for fault-tolerant asynchronous real-time distributed systems. The algorithms consider an application model where task timeliness is specified by Jensen's benefit functions and the anticipated application workload during future time intervals is described by adaptation functions. In addition, we assume that reliability functions of processors are available a priori. Given these models, our objective is to maximize aggregate task benefit and minimize aggregate missed deadline ratio in the presence of processor failures. Since determining the optimal solution is computationally intractable, the algorithms heuristically compute sub-optimal resource allocations, but in polynomial time. Experimental results reveal that RBA^*-FT and OBA-FT outperform their non-fault-tolerant counterparts in the presence of processor failures. Furthermore, RBA^*-FT performs better than OBA-FT, although OBA-FT incurs better worst-case and amortized computational costs. Finally, we observe that both algorithms robustly withstand errors in the estimation of anticipated failures.     

半导体晶圆制造车间层控制的内容及方法

半导体晶圆制造企业是资本密集、技术密集型产业,晶圆制造厂也是公认生产最为复杂的工厂之一。产品更新换代快、市场竞争激烈等特点使得投资者对设备产能和设备利用率高度重视。这已不仅仅是技术问题,而是生产制造过程管理的问题。本文介绍了半导体晶圆制造车间层控制的内容及方法。