Precise and Complete Propagation Based Local Search for Satisfiability Modulo Theories

Modern Satisfiability Modulo Theories (SMT)solvers are fundamental to many programanalysis, verification, design and testing tools. They are a goodfit for the domain of software and hardware engineering becausethey support many domains that are commonly used by the tools.The meaning of domains are captured by theories that can beaxiomatized or supported by efficient <i>theory solvers</i>.Nevertheless, not all domains are handled by all solvers andmany domains and theories will never be native to any solver.We here explore different theories that extend MicrosoftResearch's SMT solver Z3's basicsupport. Some can be directly encoded or axiomatized,others make use of user theory plug-ins.Plug-ins are a powerful way for tools to supply their custom domains.

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A Genetic Local Search Algorithm for the Graph Partitioning Problem with Cardinality Constraints

13th IFAC Symposium on Information Control Problems in Manufacturing ◽

10.3182/20090603-3-ru-2001.00335 ◽

2009 ◽

Author(s):

Kochetov, Yuri

Keyword(s):

Local Search ◽

Graph Partitioning ◽

Search Algorithm ◽

Local Search Algorithm ◽

Cardinality Constraints ◽

Graph Partitioning Problem ◽

Partitioning Problem ◽

Genetic Local Search

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Factual Power Loss Diminution by Enhanced Frog Leaping Algorithm

Journal of Applied Science, Engineering, Technology, and Education ◽

10.35877/454ri.asci112 ◽

2020 ◽

Vol 3 (2) ◽

pp. 114-118

Author(s):

Kanagasabai Lenin

Keyword(s):

Local Search ◽

Power Loss ◽

Reactive Power ◽

Test System ◽

Premature Convergence ◽

Speed Of Convergence ◽

Real Power ◽

The Real ◽

Simulation Results ◽

Power Problem

This paper proposes Enhanced Frog Leaping Algorithm (EFLA) to solve the optimal reactive power problem. Frog leaping algorithm (FLA) replicates the procedure of frogs passing though the wetland and foraging deeds. Set of virtual frogs alienated into numerous groups known as “memeplexes”. Frog’s position’s turn out to be closer in every memeplex after few optimization runs and certainly, this crisis direct to premature convergence. In the proposed Enhanced Frog Leaping Algorithm (EFLA) the most excellent frog information is used to augment the local search in each memeplex and initiate to the exploration bound acceleration. To advance the speed of convergence two acceleration factors are introduced in the exploration plan formulation. Proposed Enhanced Frog Leaping Algorithm (EFLA) has been tested in standard IEEE 14,300 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.

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