PSO based test case generation for critical path using improved combined fitness function

Sahoo, Rashmi Rekha; Ray, Mitrabinda

doi:10.1016/j.jksuci.2019.09.010

Cited by 36 publications

(14 citation statements)

References 12 publications

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“…compared with the particle swarm optimization (PSO) described in document [22], the parallel genetic algorithm with the elite set (PGA) described in document [23], the simulated annealing genetic algorithm (SAGA) described in document [24], the deep intelligent ant colony optimization algorithm (ACA) described in document [25], and the chemical reaction algorithm (CRO) described in document [26]. Te algorithm parameters are shown in Table 1.…”

Section: The Simulation Experiments and The Comparison Of Resultsmentioning

confidence: 99%

Multi-UCAV Cooperative Target Allocation Based on Energy-Reserved Chemical Reaction Algorithm (CNCRO)

Dai

2022

Mathematical Problems in Engineering

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Aimed at the disadvantages of constrained processing technology in the cooperative target allocation of multiple unmanned combat aircraft (UCAV), the energy-reserved chemical reaction algorithm (CNCRO) is proposed to solve the constrained optimization problems. On the one hand, convert multiple constraint conditions of the multi-UCAV target allocation into optimization targets to transform the constrained processing problem into a multiobjective optimization problem including allocation goals and constrained optimization goals. On the other hand, the energy-reserved chemical reaction algorithm (CNCRO) is proposed, which introduces the environmental energy-reserved variables buffer into the ineffective collision, combination or splitting reactions between single molecule and multimolecules of CNCRO, which is used to boost energy for the low kinetic energy molecules, so as to reduce its kinetic energy in case of invalid collision of molecules and control it to gradually stabilize and converge. At the same time, the splitting reaction is inspired, to greatly change the structure of molecules, promote its search for more solution space, and improve the splitting reaction ability and its global optimization ability. Finally, the simulation experiment is completed by using MATLAB software. The advantages of CNCRO in accuracy are verified by 8 standard test functions, the influence of the weight coefficients in the cooperative target allocation function of UCAV is studied, which are revenue, loss, and voyage, and the target allocation schemes of traditional constrained processing and unconstrained multiobjective optimization methods based on different attack target number C i and total target number N are investigated, to obtain the control law, which can be used to guide the given parameters with different emphases.

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Section: The Simulation Experiments and The Comparison Of Resultsmentioning

confidence: 99%

Multi-UCAV Cooperative Target Allocation Based on Energy-Reserved Chemical Reaction Algorithm (CNCRO)

Dai

2022

Mathematical Problems in Engineering

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“…Once the power flow in the complex domain has been solved for each time period, as shown in ( 23 ), and the complex power generated by the

node for each time period has been determined, as shown in ( 25 ), the fitness function (an adaptation of the objective function common in metaheuristics [ 42 , 43 ]) is then calculated for each individual from the set of candidate solutions resulting in the master stage. The main advantage of using a fitness function instead of the original objective function is that it aids the proposed optimizer in exploring unfeasible regions in search of global optimal solutions in the promissory and unexplored feasible areas of the solution space [ 44 , 45 ].…”

Section: Methodology Proposedmentioning

confidence: 99%

Optimal Design of PV Systems in Electrical Distribution Networks by Minimizing the Annual Equivalent Operative Costs through the Discrete-Continuous Vortex Search Algorithm

Cortés-Caicedo

Molina-Martin

Grisales-Noreña

et al. 2022

Sensors

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This paper discusses the minimization of the total annual operative cost for a planning period of 20 years composed by the annualized costs of the energy purchasing at the substation bus summed with the annualized investment costs in photovoltaic (PV) sources, including their maintenance costs in distribution networks based on their optimal siting and sizing. This problem is presented using a mixed-integer nonlinear programming model, which is resolved by applying a master–slave methodology. The master stage, consisting of a discrete-continuous version of the Vortex Search Algorithm (DCVSA), is responsible for providing the optimal locations and sizes for the PV sources—whereas the slave stage employs the Matricial Backward/Forward Power Flow Method, which is used to determine the fitness function value for each individual provided by the master stage. Numerical results in the IEEE 33- and 69-node systems with AC and DC topologies illustrate the efficiency of the proposed approach when compared to the discrete-continuous version of the Chu and Beasley genetic algorithm with the optimal location of three PV sources. All the numerical validations were carried out in the MATLAB programming environment.

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“…To guarantee all constraints that comprise the problem studied here, we used the fitness function (FF) presented in Equation (12). It is important to mention that a fitness function is a common adaptation of the objective function used when working with metaheuristic techniques and should be evaluated using the constraints for each individual proposed by the master stage [24,25]. The implementation of a fitness function (instead of the original objective function) allows efficient exploration and exploitation of the solution space by the algorithm, since exploring not-feasible regions increases the chances of finding a solution of good quality, by reducing processing times in the majority of the cases [26,27].…”

Section: Mathematical Formulationmentioning

confidence: 99%

Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow

et al. 2022

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This document presents a master–slave methodology for solving the problem of optimal operation of photovoltaic (PV) distributed generators (DGs) in direct current (DC) networks. This problem was modeled using a nonlinear programming model (NLP) that considers the minimization of three different objective functions in a daily operation of the system. The first one corresponds to the minimization of the total operational cost of the system, including the energy purchasing cost to the conventional generators and maintenance costs of the PV sources; the second objective function corresponds to the reduction of the energy losses associated with the transport of energy in the network, and the third objective function is related to the minimization of the total emissions of CO2 by the conventional generators installed on the DC grid. The minimization of these objective functions is achieved by using a master–slave optimization approach through the application of the Vortex Search algorithm combined with a matrix hourly power flow. To evaluate the effectiveness and robustness of the proposed approach, two test scenarios were used, which correspond to a grid-connected and a standalone network located in two different regions of Colombia. The grid-connected system emulates the behavior of the solar resource and power demand of the city of Medellín-Antioquia, and the standalone network corresponds to an adaptation of the generation and demand curves for the municipality of Capurganá-Choco. A numerical comparison was performed with four optimization methodologies reported in the literature: particle swarm optimization, multiverse optimizer, crow search algorithm, and salp swarm algorithm. The results obtained demonstrate that the proposed optimization approach achieved excellent solutions in terms of response quality, repeatability, and processing times.

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PSO based test case generation for critical path using improved combined fitness function

Cited by 36 publications

References 12 publications

Multi-UCAV Cooperative Target Allocation Based on Energy-Reserved Chemical Reaction Algorithm (CNCRO)

Multi-UCAV Cooperative Target Allocation Based on Energy-Reserved Chemical Reaction Algorithm (CNCRO)

Optimal Design of PV Systems in Electrical Distribution Networks by Minimizing the Annual Equivalent Operative Costs through the Discrete-Continuous Vortex Search Algorithm

Optimal Operation of PV Sources in DC Grids for Improving Technical, Economical, and Environmental Conditions by Using Vortex Search Algorithm and a Matrix Hourly Power Flow

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