Indoor Air Quality: Exploring Policy Options to Reduce Human Exposures

Deciding between the different policy approaches available for reducing human exposures to indoor pollutants is an exceptionally complex task. These options can range from waiting until more definitive information is available to enacting regulatory standards, with many variations in between. This paper presents some of the factors policy-makers must consider in establishing indoor air quality policies, and the role researchers should play in ensuring that indoor air policies are based on the best available scientific information.     

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.     

Communications on energy: Fighting London's cold war

This communication illustrates the work of the London Energy and Employment Network. LEEN has the twin aims of promoting a rational energy policy for London and, in the process, generating much needed employment. In cooperation with Hackney, one of Britain's poorest boroughs, LEEN organized Hackney's Cold War — a series of initiatives showing the practical measures, informational back-up and funding sources necessary for a local energy policy. LEEN intends to repeat this project in other London Boroughs, with the eventual aim of helping to persuade central government to adopt a more comprehensive approach to energy conservation nationally.     

A decision-making approach to the operation of flexible manufacturing systems

This paper introduces a generic decision-making framework for assigning resources of a manufacturing system to production tasks. Resources are broadly defined production units, such as machines, human operators, or material handling vehicles; and tasks are activities performed by resources. In the specific context of FMS, resources correspond to individual machines; tasks correspond to operations to be performed on parts. The framework assumes a hierarchical structure of the system and calls for the execution of four consecutive steps to make a decision for the assignment of a resource to a task. These steps are 1) establishment of decision-making criteria, 2) formation of alternative assignments, 3) estimation of the consequences of the assignments, and 4) selection of the best alternative assignment. This framework has been applied to an existing FMS as an operational policy that decides what task will be executed on which resource of this FMS. Simulation runs provide some initial results of the application of this policy. It is shown that the policy provides flexibility in terms of system performance and computational effort.     

Energy conservation in the industrial sector of developing countries

This paper begins by examining the most energy-intensive industries and methods by which fuel efficiency can be improved. Next the author analyses the economics of energy conservation using specific case studies drawn from India. It is shown that investing in energy efficiency is more economical Btu per Btu than investing in the enhancement of domestic energy resources. The author also assesses changes in the economics of conservation for private firms when there are government incentives. Finally government policies that can overcome economic and non-economic disincentives for investing in energy conservation are examined.     

信息安全策略实施困难的原因与对策分析

随着企业生产规模的扩大,其所掌控的资产也越来越多。信息作为企业重要的资产,其安全性正得到越来越多的企业的关注,很多企业为了保证自身信息的安全与保密性,也制订了自身的信息安全策略。然而,很多企业的信息安全策略常常形同虚设,没有发挥其应有的作用,甚至存在着严重的漏洞,为企业的健康发展埋下了不小的隐患。笔者结合自身多年的工作经验,就企业信息安全策略实施过程中存在的问题进行分析,并针对性的提出几点对策,希望对相关人士能有所帮助。     

在嵌入式系统中实现热备份

在要求高可靠性的系统设计中要求系统能够实现双机热备份,从而保证在出现问题时能够快速恢复服务。详细解读了在开发的调度机中如何实现热备份。     

Grid resource brokering algorithms enabling advance reservations and resource selection based on performance predictions

We present algorithms, methods, and software for a Grid resource manager, that performs resource brokering and job scheduling in production Grids. This decentralized broker selects computational resources based on actual job requirements, job characteristics, and information provided by the resources, with the aim to minimize the total time to delivery for the individual application. The total time to delivery includes the time for program execution, batch queue waiting, and transfer of executable and input/output data to and from the resource. The main features of the resource broker include two alternative approaches to advance reservations, resource selection algorithms based on computer benchmark results and network performance predictions, and a basic adaptation facility. The broker is implemented as a built-in component of a job submission client for the NorduGrid/ARC middleware.     

A modified teaching–learning-based optimisation algorithm for bi-objective re-entrant hybrid flowshop scheduling

In this paper, a modified teaching–learning-based optimisation (mTLBO) algorithm is proposed to solve the re-entrant hybrid flowshop scheduling problem (RHFSP) with the makespan and the total tardiness criteria. Based on the simple job-based representation, a novel decoding method named equivalent due date-based permutation schedule is proposed to transfer an individual to a feasible schedule. At each generation, a number of superior individuals are selected as the teachers by the Pareto-based ranking phase. To enhance the exploitation ability in the promising area, the insertion-based local search is embedded in the search framework as the training phase for the TLBO. Due to the characteristics of the permutation-based discrete optimisation, the linear order crossover operator and the swap operator are adopted to imitate the interactions among the individuals in both the teaching phase and the learning phase. To store the non-dominated solutions explored during the search process, an external archive is used and updated when necessary. The influence of the parameter setting on the mTLBO in solving the RHFSP is investigated, and numerical tests with some benchmarking instances are carried out. The comparative results show that the proposed mTLBO outperforms the existing algorithms significantly.