Different Number Of Jobs Research Articles

Makespan minimization of a flowshop sequence-dependent group scheduling problem

The flowshop sequence dependent group sched- uling problem with minimization of makespan as the objective (Fm|fmls, Splk, prmu|Cmax) is considered in this paper. It is assumed that several groups with different number of jobs are assigned to a flow shop cell that has m machines. The goal is to find the best sequence of processing the jobs in each group and the groups themselves with minimization of makespan as the objec- tive. A mathematical model for the research problem is developed in this paper. As the research problem is shown to be NP-hard, a hybrid ant colony optimization (HACO) algorithm is developed to solve the problem. A lower bounding technique based on relaxing a few constraints of the mathematical model developed for the original problem is proposed to evaluate the quality of the HACO algorithm. Three different problem structures, with two, three, and six machines, are used in the generation of the test problems to test the performance of the algorithm and the lower bounding technique developed. The results obtained from the HACO algorithm and those that have appeared in the published literature are also compared. The comparative results show that the HACO algorithm has a superior performance compared to the best available algorithm based on memetic algorithm with an average percentage deviation of around 1.0% from the lower bound.

Integrated Constraint Programming Scheduling Approach for Automated Wet-Etch Stations in Semiconductor Manufacturing

This article addresses a challenging resource constrained flow shop scheduling problem from automated wet-etch stations (AWSs) in wafer fabrication of semiconductor manufacturing facilities by means of a constraint programming (CP) methodology. Wet etching in wafer fabrication is a difficult process considering the material handling limitations and mixed intermediate policies. The proposed integrated approach consists of both a CP model and an efficient search strategy in order to handle the different features of the process. The domain-specific search strategy significantly improves the computational performance, a key aspect given the high combinatorial complexity of the problem. The search strategy objective is to avoid losing time due to early bad choices in the exploration and to produce good quality solutions with low computational effort. The applicability of the proposed integrated CP methodology is successfully tested with several examples taken from the literature, featuring a different number of jobs and baths.

HIV/AIDS–Related Sexual Risk Behaviors Among Rural Residents in China: Potential role of Rural–to–Urban Migration

The relationship between rural-to-urban migration and the spread of HIV is well described, although most studies focus on sexual risk behaviors among rural-to-urban migrants at the urban destination areas. Few studies have examined the sexual risk behaviors of migrants who have returned from urban areas to their rural homes ("return migrants") in comparison with those of local rural residents who have never migrated to cities ("nonmigrants"). This study examines the potential association between rural-to-urban migration and sexual risk behaviors by comparing sexual risk behaviors between 553 return migrants and 441 nonmigrants from same rural communities in China. Findings reveal that, after controlling for sociodemographic characteristics, return migrants in rural areas had higher levels of sexual risk, including unprotected sex, than nonmigrants. Among return migrants, sexual risk behaviors were associated with age, gender, marital status, and number of different jobs they had previously held in the cities. These findings underscore the importance for HIV/AIDS education and prevention efforts targeting the migrant population in urban destinations as well as the return-migrant population in rural areas.

Meta-heuristic approaches for minimizing total earliness and tardiness penalties of single-machine scheduling with a common due date

This study addresses a class of single-machine scheduling problems involving a common due date where the objective is to minimize the total job earliness and tardiness penalties. A genetic algorithm (GA) approach and a simulated annealing (SA) approach utilizing a greedy local search and three well-known properties in the area of common due date scheduling are developed. The developed algorithms enable the starting time of the first job not at zero and were tested using a set of benchmark problems. From the viewpoints of solution quality and computational expenses, the proposed approaches are efficient and effective for problems involving different numbers of jobs, as well as different processing time, and earliness and tardiness penalties.

Risk Factors for Recurrent Episodes of Work-Related Low Back Disorders in an Industrial Population

An observational longitudinal design. To characterize the rate of and risk factors for recurrent episodes of work-related low back disorder in industrial workers. Little data exist on risk factors for recurrent episodes of work-related low back disorders in employed persons. A total of 352 active hourly union employees who were diagnosed with a recent work-related low back disorder and who had at least one follow-up visit within 12 months enrolled for participation in a rehabilitation intervention study at the workplace. Information on clinical and job factors was obtained at each study visit. Job risk for low back disorder was quantified using the Lumbar Motion Monitor. The main outcome measure, recurrence of work-related low back pain, was derived from a computerized file of administrative records of visits to the plant's medical department. The rate of repeated episodes was 24.4%; an additional episode occurred in 2.3%. Adjusting for age, gender, health status and job exposures, lower levels of physical health, increasing back pain disability, spinal deformity, high stress, and increasing number of different jobs worked at the same plant were risk factors for a recurrent episodes of low back pain. Early identification of risk factors for a work-related low back disorder may signal the need for early and intense rehabilitation to prevent recurrent episodes. Because these findings were based on jobs with medium risk of low back disorders, other factors may be significant in higher risk jobs.

Fair Queuing and Other Probabilistic Allocation Methods

A server processes one job per unit of time and randomly schedules the jobs requested by a given set of users; each user may request a different number of jobs. Fair queuing (Shenker 1989) schedules jobs in successive round-robin fashion, where each agent receives one unit in each round until his demand is met and the ordering is random in each round. Fair queuing*, the reverse scheduling of fair queuing, serves first (with uniform probability) one of the users with the largest remaining demand. We characterize fair queuing* by the combination of lower composition—LC—(the scheduling sequence is history independent), demand monotonicity—DM—(increasing my demand cannot result in increased delay) and two equity axioms, equal treatment ex ante—ETEA (two identical demands give the same probability distribution of service) and equal treatment ex post—ETEP (two identical demands must be served in alternating fashion). The set of dual axioms (in which ETEA and ETEP are unchanged) characterizes fair queuing. We also characterize the rich family of methods satisfying LC, DM, and the familiar consistency—CSY—axiom. They work by fixing a standard of comparison (preordering) between a demand of xi units by agent i and one of xj units by agent j. The first job scheduled is drawn from the agents whose demand has the highest standard.

An effective heuristic for flow shop problems with total flow time as criterion

This research studies on application of genetic algorithms for flow shop problems with total flowtime as the criterion. There is still very little research focusing on total flow time for flow shop problems. We develop a genetic algorithm based heuristic for the problems, and use an integer programming model and an existing heuristic to evaluate the efficiency of the genetic algorithm based heuristic. We generate a set of problems with different numbers of machines, different numbers of jobs, and solve ten of each of the problems using the integer programming model, the existing heuristic, and the genetic algorithm based heuristic, respectively. The results are very encouraging and appear to indicate the genetic algorithms are efficient approaches for flow shop problems.