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.     

The Effects of Filtered Channel Quality Feedback on Throughput of Proportional Fair Algorithm

1　IntroductionSchedulingalgorithmsarewidelystudiedforwirelesspacketdatasystems,whichgenerallyhavetwobasiccategories,oneisoptimizedforsystemthroughputandfairness[1～ 2 ] ,andtheotherisforthequalityofservice[3～6] .Forsystemswherepack etdataaretimedivisionmultiplexedacrossusersonthedownlink ,orfromBaseStation (BS)tomultipleMobileStations(MS) ,theBSusesschedulingalgo rithmstodecidewhichuseristransmittedto .ItisindicatedinRefs.[7,8]thatschedulingonlyoneus eratatimeisoptimalfromthepointofviewo…     

The Lazy Cook Problem, or Scheduling Two Parallel Machines to Optimize Vehicle Utilization

A cook has to prepare n cakes using an oven with two racks. According to the recipe, the i-th cake has to be baked for exactly a _i minutes. Cakes to be cooked are taken from a table and carried to the oven, and once cooked are carried back to the table by means of a trolley that can carry two cakes at a time. What is the minimum number q ^* of round trips required of the cook? This problem has application to the operation scheduling of transportation systems and to material cutting. A different problem arises according to whether the cook accepts or not to stay near the oven for awhile with the trolley. If the trolley cannot be idle at the oven, an optimum schedule with no oven idle-time always exists: consequently, the trolley schedule is trivial, and the problem is transformed into a set packing. For this case, we propose and test a heuristic method which generates all of the promising columns of the set packing, and solves the resulting problem by branch-and-bound. Instead, if the trolley can be idle at the oven for a limited amount of time, a problem arises to find an optimal schedule of the trolley: in this case we show how to use a scaling technique in order to obtain a very good feasible solution by the method above.     

Experiences with a parallel algorithm for data flow analysis

We have designed a family of parallel data flow analysis algorithms for execution on distributed-memory MIMD machines, based on general-purpose, hybrid algorithms for data flow analysis [Marlowe and Ryder 1990]. We exploit a natural partitioning of the hybrid algorithms and explore a static mapping, dynamic scheduling strategy. Alternative mapping-scheduling choices and refinements of the flow graph condensation used are discussed. Our parallel hybrid algorithm family is illustrated on Reaching Definitions, although parallel algorithms also exist for many interprocedural (e.g., Aliasing) and intraprocedural (e.g., Available Expressions) problems [Marlowe 1989]. We have implemented the parallel hybrid algorithm for Reaching Definitions on an Intel iPSC/2. Our empirical results suggest the practicality of parallel hybrid algorithms.An earlier version of this paper was presented at Supercomputing '90.The research reported here was supported, in part, by the New Jersey Commission on Science and Technology and the CAIP Center's Industrial Members, by Siemens Research Corporation and by National Science Foundation grant CCR-8920078.     

天生桥梯级水电站联合调度决策支持系统建设经验

决策支持系统是水库优化调度实用化的发展方向，对于提高水电站生产效益和水库调度管理水平具有重要意义。结合国电公司重点科技项目“天生桥梯级水电站联合调度决策支持系统”的开发，阐述了开发水电调度决策支持系统实现水库调度实用化的经验:正确反映用户需求、增强用户对系统的控制、用模拟仿真弥补优化调度的不足、用数据库技术扩展水库优化调度实用化功能。     

A classification of predictive-reactive project scheduling procedures

The vast majority of the project scheduling research efforts over the past several years have concentrated on the development of workable predictive baseline schedules, assuming complete information and a static and deterministic environment. During execution, however, a project may be subject to numerous schedule disruptions. Proactive-reactive project scheduling procedures try to cope with these disruptions through the combination of a proactive scheduling procedure for generating predictive baseline schedules that are hopefully robust in that they incorporate safety time to absorb anticipated disruptions with a reactive procedure that is invoked when a schedule breakage occurs during project execution. In this paper we discuss the results obtained by a large experimental design set up to evaluate several predictive-reactive resource-constrained project scheduling procedures under the composite objective of maximizing both the schedule stability and the timely project completion probability.     

Minimizing total weighted completion time when scheduling orders in a flexible environment with uniform machines

We consider the scheduling of orders in an environment with m uniform machines in parallel. Each order requests certain amounts of k different product types. Each product type can be produced by any one of the m machines. No setup is required if a machine switches over from one product type to another. Different product types intended for the same order can be produced at the same time (concurrently) on different machines. Each order is released at time zero and has a positive weight. Preemptions are allowed. The completion time of an order is the finish time of the product type that is completed last for that order. The objective is to minimize the total weighted completion time. We propose heuristics for the non-preemptive as well as the preemptive case and obtain worst case bounds that are a function of the number of machines as well as the differences in the speeds of the machines. Even though the worst-case bounds we showed for the two heuristics are not very tight, our experimental results show that they yield solutions that are very close to optimal.