Delay in communication wires causes design iterations in system-on-chip. Latency-insensitive design copes with this issue by encapsulating each core in a shell wrapper and inserting buffers in the wires to separate th...
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Delay in communication wires causes design iterations in system-on-chip. Latency-insensitive design copes with this issue by encapsulating each core in a shell wrapper and inserting buffers in the wires to separate the design of core from that of communication wires. Scheduling-based latency-insensitive protocol is a methodology which employs shift registers for periodic clock gating of blocks instead of the shell wrappers. In many cases, the bit sequences inside the shift registers are too long and therefore consume a large area. This study presents a heuristic algorithm that optimises the bit sequences and produces them with shorter lengths compared with the existing method. The algorithm steps are described and the accuracy is validated through several synthetic benchmarks as well as real systems. Simulation results show an average 44.7% reduction on the shift registers area and the synthetic analysis in the authors proposed approach show an average 12.8% reduction on the total system area compared with the existing method.
In this paper, the optimum assignment of crews among the bases in an airlift operation is considered. An airlift operation consists of transporting large quantities of equipment and personnel among various bases. The ...
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In this paper, the optimum assignment of crews among the bases in an airlift operation is considered. An airlift operation consists of transporting large quantities of equipment and personnel among various bases. The crews operating the aircraft rest for a constant period of time after arriving at the bases, before flying again. In order to minimize the waiting times of the aircraft at the bases for want of rested crews, the available crews are distributed initially among the bases. Using earlier results of the mean waiting time of an aircraft at a single base and the probability distribution of the inter-departure times of the aircraft from the base, the problem of optimum allocation of crews is formulated as a non-linear integer programming problem. A heuristic algorithm is developed using the Lagrange multiplier. Its solution is compared with the exact solution for a number of test cases, and the algorithm is found to perform well.
This paper presents a new heuristic method for solving constrained redundancy reliability optimization problems for complex systems and compares its performance with existing heuristic methods. The method consists of ...
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This paper presents a new heuristic method for solving constrained redundancy reliability optimization problems for complex systems and compares its performance with existing heuristic methods. The method consists of two steps: selection of an optimal path and then determination of optimal components in the chosen path. Computational results show that the proposed algorithm performs better than the considered existing algorithms. The proposed method requires less computational effort than the considered existing algorithms.
In this work, we propose a heuristic algorithm based on Genetic algorithm for the task-to-processor mapping problem in the context of local-memory multiprocessors with a hypercube interconnection topology. Hypercube m...
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In this work, we propose a heuristic algorithm based on Genetic algorithm for the task-to-processor mapping problem in the context of local-memory multiprocessors with a hypercube interconnection topology. Hypercube multiprocessors have offered a cost effective and feasible approach to supercomputing through parallelism at the processor level by directly connecting a large number of low-cost processors with local memory which communicate by message passing instead of shared variables. We use concepts of the graph theory (task graph precedence to represent parallel programs, graph partitioning to solve the program decomposition problem, etc.) to model the problem. This problem is NP-complete which means heuristic approaches must be adopted. We develop a heuristic algorithm based on Genetic algorithms to solve it.
With the continuous development of science and technology, people have put forward higher requirements for the use of engineering structures, and how to optimize the design of structures better on the basis of satisfy...
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With the continuous development of science and technology, people have put forward higher requirements for the use of engineering structures, and how to optimize the design of structures better on the basis of satisfying constraints has always been the goal pursued by the engineering community. This paper studies the heuristic algorithm for topology optimization of continuum structures. The optimization calculation starts with a simple design area, and the deletion and addition of elements are considered at the same time in the iteration process. The new elements are grown around the elements with high stress and the elements with low stress values are deleted at the same time, thus the self-growth and self-evolution of structures can be realized. The simulation experiments show that the heuristic evolutionary method proposed in this paper is equipped with the ability to obtain the optimal topology of the structure, thus proving the accuracy and effectiveness of the proposed method.
Sequencing and scheduling are forms of decision making which play a key role in manufacturing. This paper presents the description of a scheduling algorithm for the solution of the no-wait flow-shop problem. The goal ...
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Sequencing and scheduling are forms of decision making which play a key role in manufacturing. This paper presents the description of a scheduling algorithm for the solution of the no-wait flow-shop problem. The goal of the heuristic is to minimise the sum of the total flow-times, a criterion which at the same time minimises the average processing time. This is a sensible target in applications such as agile manufacturing where jobs are constantly added to the job list. When evaluated over a large number of problems of various sizes, the heuristic is found to be very effective in yielding near-optimal solutions. (C) 2000 Elsevier Science B.V. All rights reserved.
A heuristic algorithm is developed for finding the maximum independent set of vertices in an undirected graph. To this end, the technique of finite partially ordered sets is used, in particular, the technique of parti...
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A heuristic algorithm is developed for finding the maximum independent set of vertices in an undirected graph. To this end, the technique of finite partially ordered sets is used, in particular, the technique of partitioning such a set into a minimum number of chains. A special digraph is constructed and a solution algorithm is proposed on the basis of a hypothesis about its properties. Some experimental data are presented for well-known examples.
Purpose - The purpose of this paper is to present an efficient heuristic algorithm based on the 3-neighborhood approach. In this paper, search is made from sides of both feasible and infeasible regions to find near-op...
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Purpose - The purpose of this paper is to present an efficient heuristic algorithm based on the 3-neighborhood approach. In this paper, search is made from sides of both feasible and infeasible regions to find near-optimal solutions. Design/methodology/approach - The algorithm performs a series of selection and exchange operations in 3-neighborhood to see whether this exchange yields still an improved feasible solution or converges to a near-optimal solution in which case the algorithm stops. Findings - The proposed algorithm has been tested on complex system structures which have been widely used. The results show that this 3-neighborhood approach not only can obtain various known solutions but also is computationally efficient for various complex systems. Research limitations/implications - In general, the proposed heuristic is applicable to any coherent system with no restrictions on constraint functions;however, to enforce convergence, inferior solutions might be included only when they are not being too far from the optimum. Practical implications - It is observed that the proposed heuristic is reasonably proficient in terms of various measures of performance and computational time. Social implications - Reliability optimization is very important in real life systems such as computer and communication systems, telecommunications, automobile, nuclear, defense systems, etc. It is an important issue prior to real life systems design. Originality/value - The utilization of 3-neighborhood strategy seems to be encouraging as it efficiently enforces the convergence to a near-optimal solution;indeed, it attains quality solutions in less computational time in comparison to other existing heuristic algorithms.
This paper investigates using heuristic algorithms to solve Multi-Objective Optimization Problem (MOOP). The primary goal is to minimize the electricity cost for a set of air conditioners in residential or commercial ...
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ISBN:
(纸本)9781467384636
This paper investigates using heuristic algorithms to solve Multi-Objective Optimization Problem (MOOP). The primary goal is to minimize the electricity cost for a set of air conditioners in residential or commercial buildings. The second objective is to minimize the discomfort factor. The algorithm, also, enhances the utilization of local renewable power. This allocation problem can be formulated using a static technique such as Mixed Integer Linear Programming (MILP), but solving MILP-based MOOP could be impracticable in heavy problems due to the hardness of the problem. Accordingly, a trade-off between cost and runtime is required. Our algorithm uses an MILP-based heuristic algorithm and LP relaxation and an innovative rounding technique called, Minimum Deviation Rounding (MDR) to get a sub-optimal solution. The result reveals that our algorithm can solve a massive problem in few seconds and gives a superb sub-optimal solution.
This paper focuses on the integrated problem of long-term planning and short-term scheduling in a largescale refinery-petrochemical complex,and considers the overall manufacturing process from the upstream refinery to...
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This paper focuses on the integrated problem of long-term planning and short-term scheduling in a largescale refinery-petrochemical complex,and considers the overall manufacturing process from the upstream refinery to the downstream petrochemical *** time scales are incorporated from the planning and scheduling *** the end of each discrete time period,additional constraints are imposed to ensure material balance between different time *** time representation is applied to the planning subproblem,while continuous time is applied to the scheduling of ethylene cracking and polymerization processes in the petrochemical *** enterprise-wide mathematical model is formulated through mixed integer nonlinear *** solve the problem efficiently,a heuristic algorithm combined with a convolutional neural network(CNN),is *** variables are used as the CNN input,leading to the integration of a data-driven approach and classical optimization by which a heuristic algorithm is *** results do not only illustrate the detailed operations in a refinery and petrochemical complex under planning and scheduling,but also confirm the high efficiency of the proposed algorithm for solving large-scale problems.
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