A hybrid genetic approach for airborne sensor vehicle routing in real-time reconnaissance missions

Berger, Jean; Barkaoui, Mohamed; Boukhtouta, Abdeslem

doi:10.1016/j.ast.2006.12.006

Cited by 20 publications

(8 citation statements)

References 14 publications

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“…Past experience has proved these parameters to be fairly acceptable for a variety of problems, and therefore, turn out to be a natural choice for both approaches. Information on operator combinations for HGA and HGA Myopic can be found in [25]. In fitness, evaluation and insertion cost functions:…”

Section: Setting Of Hga and Hga Myopicmentioning

confidence: 99%

“…Two crossover operators Q5 are developed, namely IB X and LNSB X, and a suite of five mutation operators is proposed, namely EE M, RS M, IEE M, RSR M and RC M. Each operator is briefly described next. The parameter values and more details on the genetic operators for the proposed genetic operators are presented in [25].…”

Section: Algorithmmentioning

confidence: 99%

“…HGA and HGA Myopic parameter values are selected according to [25]. Both methods use crossover and mutation rates of 0.8 and 0.6, respectively.…”

Section: Setting Of Hga and Hga Myopicmentioning

confidence: 99%

“…The customer satisfaction function is then introduced. Section 3 presents the proposed problem-solving approach whereas Section 4 conveys the main concepts of the revisited hybrid genetic algorithm reported in [25], capturing customer satisfaction possibly resulting from multiple visits. The basic principles and features of the problem-solving process and the underlying algorithm are described in details.…”

Section: Introductionmentioning

confidence: 99%

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Customer satisfaction in dynamic vehicle routing problem with time windows

Barkaoui

Berger

Boukhtouta

2015

Applied Soft Computing

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Section: Setting Of Hga and Hga Myopicmentioning

confidence: 99%

Section: Algorithmmentioning

confidence: 99%

“…HGA and HGA Myopic parameter values are selected according to [25]. Both methods use crossover and mutation rates of 0.8 and 0.6, respectively.…”

Section: Setting Of Hga and Hga Myopicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Customer satisfaction in dynamic vehicle routing problem with time windows

Barkaoui

Berger

Boukhtouta

2015

Applied Soft Computing

Self Cite

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“…Their algorithm was tested on 3-10 targets, where each target has exactly three tasks. A hybrid genetic approach is proposed by Berger et al [3], who allow 15-min of runtime for their test cases. Shetty et al [20] apply tabu search to test problems with up to 15 targets and four resources.…”

Section: Solution Approaches For Related Problemsmentioning

confidence: 99%

A branch‐and‐bound‐based solution approach for dynamic rerouting of airborne platforms

Murray

Karwan

2013

Naval Research Logistics

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This article is a sequel to a recent article that appeared in this journal, "An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations" [17], in which an integer programming formulation to the problem of rescheduling in-flight assets due to changes in battlespace conditions was presented. The purpose of this article is to present an improved branch-and-bound procedure to solve the dynamic resource management problem in a timely fashion, as in-flight assets must be quickly re-tasked to respond to the changing environment. To facilitate the rapid generation of attractive updated mission plans, this procedure uses a technique for reducing the solution space, supports branching on multiple decision variables simultaneously, incorporates additional valid cuts to strengthen the minimal network constraints of the original mathematical model, and includes improved objective function bounds. An extensive numerical analysis indicates that the proposed approach significantly outperforms traditional branch-and-bound methodologies and is capable of providing improved feasible solutions in a limited time. Although inspired by the dynamic resource management problem in particular, this approach promises to be an effective tool for solving other general types of vehicle routing problems.

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An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations

Murray

Karwan

2010

Naval Research Logistics

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Unmanned aerial vehicles (UAVs), increasingly vital to the success of military operations, operate in a complex and dynamic environment, sometimes in concert with manned aircraft. We present an extensible modeling framework for the solution to the dynamic resource management (DRM) problem, where airborne resources must be reassigned to time-sensitive tasks in response to changes in battlespace conditions. The DRM problem is characterized by diverse tasks with time windows, heterogeneous resources with fuel-and payload-capacity limitations, and multiple competing objectives. We propose an integer linear programing formulation for this problem, where mathematical feasibility is guaranteed. Although motivated by airborne military operations, the proposed general modeling framework is applicable to a wide array of settings, such as disaster relief operations. Additionally, land-or water-based operations may be modeled within this framework, as well as any combination of manned and unmanned vehicles.

show abstract

A hybrid genetic approach for airborne sensor vehicle routing in real-time reconnaissance missions

Cited by 20 publications

References 14 publications

Customer satisfaction in dynamic vehicle routing problem with time windows

Customer satisfaction in dynamic vehicle routing problem with time windows

A branch‐and‐bound‐based solution approach for dynamic rerouting of airborne platforms

An extensible modeling framework for dynamic reassignment and rerouting in cooperative airborne operations

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