This paper presents a trust path search algorithm based on random walk, which is able to improve the search by using the path information in the past.

In terms of given campaign sea area and required clearance probability through the sonar search model,emulation calculation is utilized to find the multi-AUV(Autonomous Underwater Vehicle)coordinated exercise method with the best efficiency-to-cost ratio in different sonar detecting probability,contrasting the two strategies of trapezoidal search and random search.

Used the random search algorithm to study the resource-leveling problem in project management,in view of the logic constraint and time constraint of the activities in network,presented a kind of improved random search algorithm, which based on the dynamic float,avoided producing the non-feasible solution.

The algorithm is based on random search and backtracking.

A stochastic search-based global convergence algorithm for constrained optimization problems;

A new method of constructing digital core named stochastic search algorithm based on majority operator is presented.

According to the ideas from stochastic search,this paper puts forward an algorithm BPMHS for learning Bayesian networks in the presence of missing data.

A new glob al optimization random searching al gorithm based on number-theory is proposed.

The self-adaptive step random search method is applied in this paper.