A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided. For the given n jobs to be processed on m machines, it is assum...
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A method for modeling the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure is provided. For the given n jobs to be processed on m machines, it is assumed that the processing times and the due dates are nonnegative fuzzy numbers and all the weights are positive, crisp numbers. Based on credibility measure, three parallel machine scheduling problems and a goal-programming model are formulated. Feasible schedules are evaluated not only by their objective values but also by the credibility degree of satisfaction with their precedence constraints. The genetic algorithm is utilized to find the best solutions in a short period of time. An illustrative numerical example is also given. Simulation results show that the proposed models are effective, which can deal with the parallel machine scheduling problems with fuzzy parameters and precedence constraints based on credibility measure.
A national and interregional programming model analyzes the effects of banning chlordane and heptachlor from USA agriculture. The model has sectors for land and water resources, crop and livestock production, commodit...
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A national and interregional programming model analyzes the effects of banning chlordane and heptachlor from USA agriculture. The model has sectors for land and water resources, crop and livestock production, commodity transportation and domestic and foreign demand. The central Corn Belt would lose production to other regions. Soybeans and small grains would replace corn on low lands and the value of land would decline. Crop rotations would include somewhat less corn.
n this paper, a primal dual programming model of international coking coal trade is constructed to test for non-competitive market behaviour. World trade in 1996 is simulated under perfect competition and various non-...
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n this paper, a primal dual programming model of international coking coal trade is constructed to test for non-competitive market behaviour. World trade in 1996 is simulated under perfect competition and various non-competitive market structures. Statistical tests are used to compare simulated trade flows with actual data. Assuming Cournot-Nash behaviour, an all consumer oligopsony market structure is preferred to alternative models. Under an all consumer oligopsony world coking coal prices and trade are lower than under perfect competition. Under an oligopsonistic structure welfare gains from productivity increases in Australian coal mines might largely accrue to coal buyers. (C) 1999 Published by Elsevier Science.
This paper addresses the problem of locating concentrators in a computer communications network where a concentrator could be connected to another concentrator in a hierarchy. A mathematical programming model is devel...
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This paper addresses the problem of locating concentrators in a computer communications network where a concentrator could be connected to another concentrator in a hierarchy. A mathematical programming model is developed. The objective is to minimize the costs of setting up and operating the. communications network subject to capacity constraints. A Lagrangian relaxation approach is used to develop a heuristic solution procedure which is both efficient and effective. Extensive computational experiments were conducted to test the performance of the solution procedure. Problems with up to 200 terminal and 10 potential concentrator locations were studied. The gap between the feasible solution value and the best lower bound was used to judge the quality of the procedure. The mean gaps were in the range of 3-12% across a wide range of problem structures.
This paper discusses heuristic “branch and bound” methods for solving mixed integer linear programming problems. The research presented on here is the follow on to that recorded in [3].After a resumé of the con...
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This paper discusses heuristic “branch and bound” methods for solving mixed integer linear programming problems. The research presented on here is the follow on to that recorded in [3].After a resumé of the concept of pseudo-costs and estimations, new heuristic rules for generating a tree which make use of pseudo-costs and estimations are presented. Experiments have shown that models having a low percentage of integer variables behave in a radically different way from models with a high percentage of integer variables. The new heuristic rules seem to apply generally to the first type of ***, other heuristic rules are presented that are used with models having a high percentage of integer variables and with models having a special structure (models including special ordered sets.)The rules introduced here have been implemented in the IBM Mathematical programming System Extended/370. They are used to solve large mixed integer linear programming *** results that permit comparisons to be made among the different rules are provided and discussed.
Data-Centric Synchronization (DCS) shifts the reasoning about concurrency restrictions from control structures to data declaration. It is a high-level declarative approach that abstracts away from the actual concurren...
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Data-Centric Synchronization (DCS) shifts the reasoning about concurrency restrictions from control structures to data declaration. It is a high-level declarative approach that abstracts away from the actual concurrency control mechanism(s) in use. Despite its advantages, the practical use of DCS is hindered by the fact that it may require many annotations and/or multiple implementations of the same method to cope with differently qualified parameters. To overcome these limitations, in this paper we present AtomiS, a new DCS approach that requires only qualifying types of parameters and return values in interface definitions, and of fields in class definitions. The latter may also be abstracted away in type parameters, rendering class implementations virtually annotationfree. From this high level specification, a static analysis infers the atomicity constraints that are local to each method, considering valid only the method variants that are consistent with the specification, and performs code generation for all valid variants of each method. The generated code is then the target for automatic injection of concurrency control primitives that are responsible for ensuring the absence of data-races, atomicity-violations and deadlocks. We provide a Java implementation and showcase the applicability of AtomiS in real-life code. For the benchmarks analysed, AtomiS requires fewer annotations than the original number of regions requiring locks, as well as fewer annotations than Atomic Sets (a reference DCS proposal).
In this paper, the author propose viewing a program as a collection of "free" objects, each of which has its own thread of control and executes its operations within atomic transactions. Such objects would c...
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In this paper, the author propose viewing a program as a collection of "free" objects, each of which has its own thread of control and executes its operations within atomic transactions. Such objects would communicate by asynchronous message passing with futures - objects that encapsulate the results of server invocations and let clients retrieve them while hiding the actual state of readiness from the client. Except for the unleashing of newly created free objects, theres no need for specific language constructs other than those already available in 00 languages. After all, C++ has been successful in part because it looked like C, Java has been successful in part because it looked like C++, and C# looks like both. With free objects, the program looks exactly like a traditional OO program, with one exception: certain object creations fork new activity threads and must be distinguished as such. This column discusses how to do that.
Cellular automata proved to be a promising model to simulate several complex systems: the requirement is that space and time, taken into account, have to be discretizable, while the system to be simulated has to satis...
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Cellular automata proved to be a promising model to simulate several complex systems: the requirement is that space and time, taken into account, have to be discretizable, while the system to be simulated has to satisfy locality and uniformity in the evolutionary space. Often, in dealing with the simulation of real complex systems some properties of locality are lost and consequently standard CA model application is very difficult. For this reason it is useful to extend the classical CA model and introduce feasible mechanisms in order to take advantage of the parallelism source of this computational model. With this aim the Cellular Automata Network (CAN) model was conceived that includes the advantages of classical CA models and introduces a new source of parallelism, i.e. the network of cellular automata. In this paper we deal with a sort of heuristics in order to map CA applications into CANs. This mapping can also be extremely useful as a proposal of a methodology to drive the modeling and simulation activity of complex phenomena that can be easily fragmented according to local interaction and components. (C) 2002 Elsevier Science B.V. All rights reserved.
We analyze a mathematical programming model of a fractional flow process which consists ofn sectors and all possible time-dependent streams of flow between, into and out of the sectors. Assuming specific constraints o...
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We analyze a mathematical programming model of a fractional flow process which consists ofn sectors and all possible time-dependent streams of flow between, into and out of the sectors. Assuming specific constraints on flow, least cost policies are determined for control of the system transactions involved over a given finite time horizon and over an infinite horizon. Several applications of the model are presented and discussed.
Non-uniform sampling two-dimensional convolution (NUSC) maps spatially sampling data with irregular distribution to a regular grid by convolution. As the data scale and growth rate continue to increase, accelerating N...
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Non-uniform sampling two-dimensional convolution (NUSC) maps spatially sampling data with irregular distribution to a regular grid by convolution. As the data scale and growth rate continue to increase, accelerating NUSC with the heterogeneous computing platform is a feasible way. However, the complex hardware architecture and storage hierarchy of the heterogeneous computing platform poses a challenge to programming and performance tuning. Therefore, this paper proposes a heterogeneous parallel programming model and runtime framework named AutoNUSC. For the programming difficulties of NUSC in heterogeneous computing environments, AutoNUSC abstracts and encapsulates the parallel execution process of NUSC. Task scheduling, data division, node communication, fault-tolerant recovery, and other parallelization tasks are managed by AutoNUSC. For the performance tuning issues of NUSC, this paper implements performance optimization strategies for AutoNUSC, including vectorization, memory access optimization, data reuse, etc. The experiments show that AutoNUSC effectively reduces the workload of users in developing NUSC applications in heterogeneous computing environments. Performance acceleration of up to 339 times is achieved within a single node compared to the serial program. AutoNUSC can efficiently perform task scheduling and fault-tolerant recovery across multiple nodes, with desirable scalability and robustness.
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