AN EFFICIENT HEURISTIC METHOD FOR STATE ASSIGNMENT OF LARGE SEQUENTIAL MACHINES

1992 ◽  
Vol 02 (01) ◽  
pp. 1-26 ◽  
Author(s):  
LECH JÓŹWIAK
Keyword(s):  
Heuristic Method ◽  
Logic Synthesis ◽  
Vlsi Design ◽  
Solution Space ◽  
Search Space ◽  
Heuristic Approach ◽  
Binary Representation ◽  
Strict Sense ◽  
State Assignment ◽  
Sequential Machines

VLSI circuit design is a “trial and error” process that consists of solving a number of design problems. An optimal state assignment is one of the most important problems in the logic synthesis for sequential machines and it consists of choosing a binary representation for symbolic internal states of a sequential machine, so that the resulting logic is optimal for a given objective. This problem belongs to the class of most complex computational problems in VLSI design – it is NP hard. In a strict sense, it has never been solved, except for exhaustive search, which is impossible for large machines even with a computer. A structural heuristic approach uses specific knowledge about the structure of a given problem in order to reduce the search space to a manageable size and to maintain high quality solutions at the same time. Using the state assignment problem as an example, we determined the importance of the structural heuristic approach in CAD for VLSI and we showed how to search for suitable heuristics. We discussed a new heuristic method for state assignments concentrating on heuristic aspects such as: the solution space, the generation procedure and its operators, the evaluation functions etc. We provided some experimental results to show that the new method is very efficient. The structural heuristic search can be highly efficient. Its efficiency is limited more by the capacity of the human brain to think heuristically than by the complexity of the problem itself.

scholarly journals Identification of Damage on Stringers By the PSO Method

2021 ◽  
Vol 29 (3) ◽  
pp. 9-14
Author(s):  
Martin Marton ◽  
Milan Sokol ◽  
Adrian Bekö ◽  
Cao Maosen
Keyword(s):  
Heuristic Method ◽  
Solution Space ◽  
Search Space ◽  
Position Vector ◽  
Comparison Function ◽  
Swarm Optimization ◽  
Common Solution ◽  
Cognitive Information ◽  
The Moment

Abstract The paper employs the particle swarm optimization (PSO) method for the identification of damage to a stringer web. This method is inspired by a swarm of bees or flock of birds which look for a common solution. It is a heuristic method, that utilizes a particle as a problem-solving candidate. The location of this particle in the search space represents the configuration of all the variables to possible solutions of the problem. As the particle moves into the solution space, the values of the variables change. The particle is defined by a position vector and a velocity vector. The resulting direction of the particle is determined by three components i.e. (1) the moment or inertia, (2) autobiographical or cognitive information and (3) social interaction. The quality of the particle is evaluated by a comparison function. In this study we tried to locate damage by using this method. The damage is represented by a rusted area on a stringer web, which was simulated as a change in the Young’s modulus. We used the modal calculation of the eigenfrequencies as an evaluation function.

Space Contraction and Partition Algorithm for Combinatorial Optimization

2011 ◽  
Vol 421 ◽  
pp. 559-563
Author(s):  
Yong Chao Gao ◽  
Li Mei Liu ◽  
Heng Qian ◽  
Ding Wang
Keyword(s):  
Combinatorial Optimization ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Solution Space ◽  
Search Space ◽  
Small Scale ◽  
Optimal Solutions ◽  
Solution Quality ◽  
Intelligent Algorithms ◽  
Combinatorial Optimization Problems

The scale and complexity of search space are important factors deciding the solving difficulty of an optimization problem. The information of solution space may lead searching to optimal solutions. Based on this, an algorithm for combinatorial optimization is proposed. This algorithm makes use of the good solutions found by intelligent algorithms, contracts the search space and partitions it into one or several optimal regions by backbones of combinatorial optimization solutions. And optimization of small-scale problems is carried out in optimal regions. Statistical analysis is not necessary before or through the solving process in this algorithm, and solution information is used to estimate the landscape of search space, which enhances the speed of solving and solution quality. The algorithm breaks a new path for solving combinatorial optimization problems, and the results of experiments also testify its efficiency.

Comparing Three Different Modularity Methods

2003 ◽  
Author(s):  
Katja M. M. Holtta ◽  
Mikko P. Salonen
Keyword(s):  
Heuristic Method ◽  
Modular Function ◽  
Heuristic Approach ◽  
Design Structure Matrix ◽  
Commercial Products ◽  
Product Families ◽  
Structure Matrix ◽  
Design Structure ◽  
Strategic Factors

Modularity has many advantages but few methods exist to partition a product into modules, and no knowledge on which method to use and when. This study compares the heuristic method, the design structure matrix, and modular function deployment. The methods are applied on four commercial products. The disturbing result is that, given the same inputs, all methods partition the products differently. Some consider functionality and interface simplicity whereas others focus on strategic factors. A method developed for single products is poorly suited to modularizing product families. The methods find almost no common module boundaries that would be ideal regardless of the method used. This result is not due to poor application of the methods: the repeatability of each method was analyzed. It varied from 68% to nearly perfect. Modular function deployment was the least repeatable whereas the computerized design structure matrix the most repeatable. The heuristic approach fell in between.

scholarly journals Evolutionary Observer Ensemble for Leak Diagnosis in Water Pipelines

Processes ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 913 ◽  
Author(s):  
A. Navarro ◽  
J. A. Delgado-Aguiñaga ◽  
J. D. Sánchez-Torres ◽  
O. Begovich ◽  
G. Besançon
Keyword(s):  
Heuristic Method ◽  
Pressure Head ◽  
Search Space ◽  
Observation Error ◽  
State Variables ◽  
Test Bed ◽  
Interior Node ◽  
Water Pipelines ◽  
Exponentially Stable ◽  
Integral Observation

This work deals with the Leak Detection and Isolation (LDI) problem in water pipelines based on some heuristic method and assuming only flow rate and pressure head measurements at both ends of the duct. By considering the single leak case at an interior node of the pipeline, it has been shown that observability is indeed satisfied in this case, which allows designing an observer for the unmeasurable state variables, i.e., the pressure head at leak position. Relying on the fact that the origin of the observation error is exponentially stable if all parameters (including the leak coefficients) are known and uniformly ultimately bounded otherwise, the authors propose a bank of observers as follows: taking into account that the physical pipeline parameters are well-known, and there is only uncertainty about leak coefficients (position and magnitude), a pair of such coefficients is taken from a search space and is assigned to an observer. Then, a Genetic Algorithm (GA) is exploited to minimize the integration of the square observation error. The minimum integral observation error will be reached in the observer where the estimated leak parameters match the real ones. Finally, some results are presented by using real-noisy databases coming from a test bed plant built at Cinvestav-Guadalajara, aiming to show the potentiality of this method.

Hybrid Simulate Annealing Algorithm Based Dynamic Crew Scheduling Research

2013 ◽  
Vol 411-414 ◽  
pp. 2359-2363
Author(s):  
Jie Fang ◽  
Hong Shan Xia
Keyword(s):  
Simulated Annealing Algorithm ◽  
Solution Space ◽  
Emergency Situation ◽  
Search Space ◽  
Crew Scheduling ◽  
Experimental Result ◽  
Hybrid Simulated Annealing ◽  
Resource Cost ◽  
Annealing Algorithm ◽  
Algorithm Search

Dynamic crew scheduling optimize the crew plan and save the human resource cost in emergency situation. On the basis of considering crew plan regulations and crew cost, the research construct dynamic crew scheduling model, using heuristic pretreatment method to generate dynamic crew routing for reducing the solution space. It form hybrid simulated annealing algorithm to solve the dynamic crew scheduling problem. The experimental result confirm the method could effectively reduce algorithm search space and calculation time and improve the operation efficiency.

A HEURISTIC APPROACH FOR SOLVING SERIALLY DISTRIBUTED STORAGE DEPOTS UNDER GENERAL-INTEGER POLICY

2007 ◽  
Vol 24 (04) ◽  
pp. 479-497 ◽  
Author(s):  
FANG-CHUAN LEE ◽  
UE-PYNG WEN
Keyword(s):  
Structure Analysis ◽  
Distribution System ◽  
Lot Sizing ◽  
Distributed Storage ◽  
Heuristic Method ◽  
Heuristic Approach ◽  
Cost Curve ◽  
Solution Approach ◽  
Curve Structure ◽  
Comparison Of The Results

In this study, we present the problems of shipping a single product from a single supply origin, through a serial system of storage depots, to a single demand destination by trucks or ships, and aim to minimize the sum of ordering, inventory and transportation costs over an infinite time horizon. We formulate the problem consisting of general-integer (GI), stationary and nested replenishment policies for the multistage inventory/distribution system. This paper presents the near-optimal cost-curve structure analysis for this serially distributed storage depot problem (SDSDP) and show that the ordering quantities for each storage depot always comply with the GI replenishment policy. Moreover, we develop a heuristic approach, which is based on an efficient search procedure to obtain satisfactory results. A comparison of the results obtained from the proposed heuristic method has been made with that from the LINGO® software on randomly generated problems. The proposed heuristic is the first solution approach in the literature to solve the single link problems based on the cost-curve structure analysis. Furthermore, we provide an important foundation for carrying out investigations on lot sizing and distribution problems with other supply chain configurations.

scholarly journals Analysis and Characterization of State Assignment Techniques for Sequential Machines

VLSI Design ◽  
1994 ◽  
Vol 2 (1) ◽  
pp. 81-88 ◽  
Author(s):  
R. Z. Makki ◽  
S. Su
Keyword(s):  
Simple Technique ◽  
Propagation Delay ◽  
State Machines ◽  
Complex State ◽  
Silicon Area ◽  
State Assignment ◽  
Propagation Delay Time ◽  
Sequential Machines ◽  
Finite State

In this paper, we study the problem of state assignment as it relates to silicon area, propagation delay time and testability of finite state machines. The results of a study involving various FSM benchmarks show that the simple technique of one-hot encoding often produces better results than those attained by complex state assignment algorithms.

scholarly journals A Computationally Improved Heuristic Algorithm for Transmission Switching Using Line Flow Thresholds for Load Shed Reduction

2021 ◽  
Author(s):  
Tanveer Hussain ◽  
S M Shafiul Alam ◽  
Timothy M. Hansen ◽  
Siddharth Suryanarayanan
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Heuristic Method ◽  
Search Space ◽  
Load Shedding ◽  
Mesh Topology ◽  
Transmission Switching ◽  
Computational Performance ◽  
Topology Changes ◽  
Line Flow

A computationally improved algorithm to find the best transmission switching (TS) candidate for load shed reduction after (<i>N</i>-2) contingencies is presented. TS is a planned line outage and research from the past shows that changing transmission system's mesh topology changes the power flows and removes post contingency violations (PCVs). One of the major challenges is to find the best TS candidate in a suitable time. Here, the best TS candidate is determined by using a novel heuristic method by decreasing the search space based on proximity to load shedding bus (LSB). The proposed method is capable of finding the best TS candidate faster than the well-known existing algorithm in the literature and guarantees removal of PCVs. Moreover, proposed algorithm is compatible with both AC and DC optimal power flow (OPF) formulations. Finally, the proposed method is implemented by modifying the topology of the transmission system after (<i>N</i>-2) contingencies in the IEEE 39-bus, IEEE 118-bus, and Polish 2383-bus test systems. Two metrics are used to compare results from the proposed method with those from state-of-the-art to show the speedup and accuracy achieved. Parallel computing is used to increase the computational performance of the proposed algorithm.

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