A hybrid adaptively genetic algorithm for task scheduling problem in the phased array radar

Zhang, Haowei; Xie, Junwei; Ge, Jiaang; Zhang, Zhaojian; Zong, Binfeng

doi:10.1016/j.ejor.2018.07.012

Cited by 55 publications

(24 citation statements)

References 27 publications

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“…Elshafei et al (2004) presented integer pro-gramming models for the multi-target tracking system. More recently, Zhang et al (2019a) developed a hybrid genetic algorithm for scheduling a phased array radar, and Zhang et al (2019b) provided an online algorithm for a radar system having multiple inputs and multiple outputs.…”

Section: Introductionmentioning

confidence: 99%

Scheduling coupled tasks with exact delays for minimum total job completion time

Chen

Zhang

2020

J Sched

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Section: Introductionmentioning

confidence: 99%

Scheduling coupled tasks with exact delays for minimum total job completion time

Chen

Zhang

2020

J Sched

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“…The radar task model is shown in (5) and Table 1 [19], and k i T is the k-th task in the i-th scheduling interval. , } Fig.1 shows the radar task life cycle.…”

Section: Radar Task Modelmentioning

confidence: 99%

Phased-Array Radar Task Scheduling Method for Hypersonic-Glide Vehicles

Meng¹,

Tian²

2020

IEEE Access

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“…By the process of genetic change, the survival of the fittest population may well adapt to the environment [58,59]. GA has attracted the attention of researchers to use for the PSP and its extensions [60,61].…”

Section: Genetic Algorithm (Ga)mentioning

confidence: 99%

Designing a resource-constrained project scheduling model considering multiple routes for flexible project activities: meta-heuristic algorithms

2019

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Resource constrained project scheduling problem with multiple routes for flexible project activities (RCPSP-MR) is a generalization of the RCPSP, in which for the implementation of each flexible activity in main structure of the project, several exclusive sub-networks are considered. Each sub-network is regarded as a route for the flexible activity. The routes are considered for each flexible activity that are varied in terms of: 1) Number of activities required to execute; 2) Precedence relationship between activates; 3) Allocation of different renewable and nonrenewable resources to each activity; and 4) Effectiveness on the duration and cost of project completion. In this paper, a new mathematical formulation of RCPSP-MR is firstly presented. Then, two solving approaches based on particle swarm optimization (PSO) and genetic algorithm (GA) are proposed to minimize costs of project completion. To evaluate the effectiveness of these proposed approaches, 50 problems (in very small, small, medium, and large-sized test problems) are designed and then are solved. Finally, comparisons are provided. Computational results show that the proposed GA generates high-quality solutions in a timely fashion. Keywords: Resource constrained project scheduling problem (RCPSP), flexible activities, multiple routes, particle swarm optimization (PSO), genetic algorithm (GA) 0,1, 2,..., 1 JN  1 J Set of total project fixed activities, 1 JJ  2 J Set of total flexible project activities, 21 J J J    Set of routes of each flexible activity 2 J   h  Set of total sub network for flexible activity

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A hybrid adaptively genetic algorithm for task scheduling problem in the phased array radar

Cited by 55 publications

References 27 publications

Scheduling coupled tasks with exact delays for minimum total job completion time

Scheduling coupled tasks with exact delays for minimum total job completion time

Phased-Array Radar Task Scheduling Method for Hypersonic-Glide Vehicles

Designing a resource-constrained project scheduling model considering multiple routes for flexible project activities: meta-heuristic algorithms

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