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.     

漫谈钛合金在舰船上的应用

钛合金优良的耐海水腐蚀性能、高的比强度、无磁性等特点,使其在船用领域大有潜力可为,我国的船用钛合金经过近40年的研究开发,基本能满足舰艇不同强度级别的需求,在舰船上应用具有明显的社会效益和经济效益,值得进一步应用推广。本文介绍了国内外舰船用钛合金的开发及应用情况。对钛合金在鱼雷发射水缸、高压气瓶、一回路危急冷却器、声扫雷具、二回路泵、阀及管系、声纳导流罩、螺旋桨等方面的应用作了重点介绍。     

CCUS in a net-zero U.S. power sector: Policy design,rates, and project finance

Carbon capture utilization and storage is an important technology option to rapidly and profoundly decarbonize the power sector, but will not deploy without substantial incentives or regulation. Assessment of U.S. policy options reveals that current incentives only partially close the finance gap and are most sensitive to fuel type and ownership structure. Recent proposed legislation would in some designs attract private investment for many projects, leading to widespread deployment of CCUS in the power sector. Additional constraints and concerns (including technology options and presence of CO₂ infrastructure) could play an important secondary role. This study discusses the specific US incentive policies that can provide investors and lenders with net cash flows that are adequate to attract private capital to CCUS power projects in the US.     

Single-machine parallel-batching scheduling with family jobs to minimize weighted number of tardy jobs

We consider the problem of scheduling n jobs in batches on a single parallel-batching machine, where the jobs are partitioned into jobs families and the jobs in each family have the same due date. The objective is to minimize the weighted number of tardy jobs. We first devise an efficient pseudo-polynomial time and a fully polynomial time approximation scheme for the weighted problem. Then we present $O(n^2)$-time and $O(n\log n)$-time algorithms for the case where the jobs have the same weight and for the case where the jobs have the same processing time, respectively.     

Competitive online adaptive scheduling for sets of parallel jobs with fairness and efficiency

We study online adaptive scheduling for multiple sets of parallel jobs, where each set may contain one or more jobs with time-varying parallelism. This two-level scheduling scenario arises naturally when multiple parallel applications are submitted by different users or user groups in large parallel systems, where both user-level fairness and system-wide efficiency are of important concerns. To achieve fairness, we use the well-known equi-partitioning algorithm to distribute the available processors among the active job sets at any time. For efficiency, we apply a feedback-driven adaptive scheduler that periodically adjusts the processor allocations within each set by consciously exploiting the jobs’ execution history. We show that our algorithm achieves asymptotically competitive performance with respect to the set response time, which incorporates two widely used performance metrics, namely, total response time and makespan, as special cases. Both theoretical analysis and simulation results demonstrate that our algorithm improves upon an existing scheduler that provides only fairness but lacks efficiency. Furthermore, we provide a generalized framework for analyzing a family of scheduling algorithms based on feedback-driven policies with provable efficiency. Finally, we consider an extended multi-level hierarchical scheduling model and present a fair and efficient solution that effectively reduces the problem to the two-level model.     

用高分子材料修复舰艇大轴

舰艇大轴在海水中严重腐蚀后,采用粘接技术,选用国产高强度金属修补剂,对大轴局部腐蚀部位进行修理,对提高大轴使用寿命,防止大轴再腐蚀起到有效作用.     

A robust hybrid approach based on particle swarm optimization and genetic algorithm to minimize the total machine load on unrelated parallel machines

This paper dealt with an unrelated parallel machines scheduling problem with past-sequence-dependent setup times, release dates, deteriorating jobs and learning effects, in which the actual processing time of a job on each machine is given as a function of its starting time, release time and position on the corresponding machine. In addition, the setup time of a job on each machine is proportional to the actual processing times of the already processed jobs on the corresponding machine, i.e., the setup times are past-sequence-dependent (p-s-d). The objective is to determine jointly the jobs assigned to each machine and the order of jobs such that the total machine load is minimized. Since the problem is NP-hard, optimal solution for the instances of realistic size cannot be obtained within a reasonable amount of computational time using exact solution approaches. Hence, an efficient method based on the hybrid particle swarm optimization (PSO) and genetic algorithm (GA), denoted by HPSOGA, is proposed to solve the given problem. In view of the fact that efficiency of the meta-heuristic algorithms is significantly depends on the appropriate design of parameters, the Taguchi method is employed to calibrate and select the optimal levels of parameters. The performance of the proposed method is appraised by comparing its results with GA and PSO with and without local search through computational experiments. The computational results for small sized problems show that the mentioned algorithms are fully effective and viable to generate optimal/near optimal solutions, but when the size of the problem is increased, the HPSOGA obtains better results in comparison with other algorithms.     

在线求职招聘平台的设计与实现

求职招聘网站在信息产业高速发展、信息流高速传递的今天,对于求职者和招聘单位都越来越重要,系统应该为用户提供充分的信息管理和方便的搜索查询手段。传统的现场招聘会虽然在一定程度上解决了双方的交流信息。但是,这种交流是属于低效、窄幅流动的,不能适应现今社会的要求。该文针对传统的求职招聘管理方式存在的问题,提出了在线求职招聘平台的解决方案。     

Single machine scheduling with simple linear deterioration to minimize total absolute deviation of completion times

We consider a single machine scheduling problem with simple linear deterioration. Job processing times are assumed to be a simple linear function of a job-dependent growth rate and the job's starting time. We seek an optimal schedule, so as to minimize the total absolute deviation of completion times (TADC). We prove several interesting properties of an optimal schedule, and introduce two efficient heuristics which are tested against a lower bound.     

Single-machine scheduling with deteriorating jobs under a series–parallel graph constraint

This paper considers single-machine scheduling problems with deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting times. In addition, the jobs are related by a series–parallel graph. It is shown that for the general linear problem to minimize the makespan, polynomial algorithms exist. It is also shown that for the proportional linear problem of minimization of the total weighted completion time, polynomial algorithms exist, too.