Learn More
We present a new concurrency control abstraction for real-time systems called preemptible atomic regions (PARs). PARs a transactional mechanism that improves upon lock-based mutual exclusion in several ways. First, and foremost, PARs provide strong correctness guarantees. Any sequence of operations declared atomic will not suffer interference from other(More)
This paper presents extensive experiments on a hybrid optimization algorithm (DEPSO) we recently developed by combining the advantages of two powerful population-based metaheuristics—differential evolution (DE) and particle swarm optimization (PSO). The hybrid optimizer achieves on-the-fly adaptation of evolution methods for individuals in a statistical(More)
—Differential evolution (DE) and particle swarm optimization (PSO) are two formidable population-based optimiz-ers (POs) that follow different philosophies and paradigms, which are successfully and widely applied in scientific and engineering research. The hybridization between DE and PSO represents a promising way to create more powerful optimizers,(More)
—In this paper, we propose an efficient rule-based heuristic to solve asset-based dynamic weapon-target assignment (DWTA) problems. The main idea of the proposed heuristic is to utilize the domain knowledge of DWTA problems to directly achieve weapon assignment, without large number of function evaluations. We update the saturation states of constraints in(More)
—The dynamic weapon-target assignment (DWTA) problem is a typical constrained combinatorial optimization problem with the objective of maximizing the total value of surviving assets threatened by hostile targets through all defense stages. A generic asset-based DWTA model is established, especially for the warfare scenario of force coordination, to(More)
—Global optimization process can often be divided into two subprocesses: exploration and exploitation. The tradeoff between exploration and exploitation (T:Er&Ei) is crucial in search and optimization, having a great effect on global optimization performance, e.g., accuracy and convergence speed of optimization algorithms. In this paper, definitions of(More)
Traditional dynamic program slicing techniques are code-centric, meaning dependences are introduced between executed statement instances, which gives rise to various problems such as space requirement is decided by execution length; dependence graphs are highly redundant so that inspecting them is labor intensive. In this paper, we propose a data-centric(More)
This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics——differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its(More)