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Particle Swarm Optimization to Solve Unrelated Parallel Machine Schedulling Problems
Partical Swarm Optimization Algorithm Example
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Particle Swarm Optimization (PSO) Example in design and analysis of algorithm (PART 2)
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A discrete particle swarm optimization algorithm applied in constrained
The weapon-target assignment (WTA) problem is an important content in military operational research. In this paper, a discrete particle swarm optimization (DPSO) algorithm is presented to solve the constrained static weapon-target assignment (SWTA) problem subject to firing range constraint, weapon-target match constraint and so on. This constrained SWTA problem with upper bound on the number ...
UAV Cooperative Multiple Task Assignment Based on Discrete Particle
The combinatorial optimization problem of assigning cooperating unmanned aerial vehicles to multiple tasks is posed by a shared model. A discrete particle swarm optimization algorithm for solving such a problem is proposed. A matrix representation of the algorithm's position vector spaces is employed. A new update strategy for the position and speed of particle is applied in this algorithm ...
Solving Weapon-Target Assignment Problem using Discrete Particle Swarm
This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced into DPSO in which a priority set is constructed to control the local search and converge to the global optimum efficiently. Then the particles would be updated ...
Parameter Selection of Discrete Particle Swarm Optimization Algorithm
Quadratic Assignment Problems (QAPs) are the hardest of combinatorial optimization problems, with some problems of sizes of the order of 30 still remaining unsolved optimally. ... Keywords: Quadratic Assignment Problem; Discrete Particle Swarm Optimization; Taguchi’s robust design. 1. Introduction The Quadratic Assignment Problem (QAP ...
PDF A New Discrete Particle Swarm Optimization Algorithm
Particle Swarm Optimization, Discrete Optimization, Cate-gorical Optimization 1. INTRODUCTION Discrete optimization problems, such as feature selection or inference in Bayesian networks, represent an important and challenging set of problems. These di er from continu-ous problems in that each variable can take on only a nite number of states [6].
Advances on Particle Swarm Optimization in Solving Discrete
The problem induces efficient assignment of objects into a knapsack with maximum profit without exceeding the capacity of the knapsack. ... Nagari, A.L., et al.: Implementation of discrete particle swarm optimization algorithm in the capacitated vehicle routing problem. Jurnal Sistem dan Manajemen Industri 4, 117-128 (2020). https://doi.org ...
Particle swarm optimisation for discrete optimisation problems: a
In many optimisation problems, all or some of decision variables are discrete. Solving such problems are more challenging than those problems with pure continuous variables. Among various optimisation techniques, particle swarm optimisation (PSO) has demonstrated more promising performance in tackling discrete optimisation problems. In PSO, basic variants are merely applicable to continuous ...
Discrete Particle Swarm Optimization, illustrated by the Traveling
The classical Particle Swarm Optimization is a powerful method to find the minimum of a numerical function, on a continuous definition domain. As some binary versions have already successfully been used, it seems quite natural to try to define a framework for a discrete PSO. In order to better understand both the power and the limits of this ...
Solving weapon-target assignment problem using discrete particle swarm
A discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem and the concept of "permutation" is employed to the update strategy. This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced ...
Discrete particle swarm optimization based on estimation of
Terminal assignment problem (TEAP) is to determine minimum cost links to form a network by connecting a given set of terminals to a given collection of concentrators. This paper presents a novel discrete particle swarm optimization (PSO) based on estimation of distribution (EDA), named DPSO-EDA, for TEAP.
A discrete particle swarm optimization method for assignment of
In this study, in order to solve the assignment problem from supermarket resources to urban residential communities under the situation of the epidemic control, the discrete multi-objective particle swarm algorithm can be improved by introducing some new strategies, and the probability matrix can be used to simulate the many-to-many assignment ...
(PDF) Parameter Selection of Discrete Particle Swarm Optimization
As an improved version of PSO, Discrete Particle Swarm Optimization (DPSO) was developed for solving discrete optimization problems such as the minimum labeling Steiner tree problem, grid job ...
A discrete particle swarm optimization algorithm ...
A discrete particle swarm optimization (DPSO) algorithm is presented to solve the constrained static weapon-target assignment (SWTA) problem subject to firing range constraint, weapon- target match constraint and so on. The weapon-target assignment (WTA) problem is an important content in military operational research. In this paper, a discrete particle swarm optimization (DPSO) algorithm is ...
A Discrete Particle Swarm Optimization for Storage Location Assignment
The optimization model of the storage location assignment problem (SLAP) for retail e-commerce is firstly established based on the principles of efficiency priority, shelf stability and similar products adjacency. Then, a new discrete particle swarm optimization (DPSO) algorithm is proposed to solve the NP-hard SLAP.
Particle swarm optimisation for discrete optimisation problems: A review
Abstract and Figures. In many optimisation problems, all or some of decision variables are discrete. Solving such problems are more challenging than those problems with pure continuous variables ...
PDF A Novel Discrete Particle Swarm Optimization Algorithm for the
The Particle Swarm Optimization (PSO) is a population-based optimization method first proposed by Kennedy and Eberhart [22]. A swarm, in this context, is a population of several solutions of a given problem, and each solution is seen as an organism in a social environment, also called particle.
Solving Weapon-Target Assignment Problem using Discrete Particle Swarm
This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced into DPSO in which a priority set is constructed to control the local search and converge to the global optimum efficiently. Then the particles would be updated ...
Frequency assignment problem using discrete particle swarm model
The problem of the fixed-spectrum frequency assignment, where the objective is to minimize the cost due to the interference arising in a solution, is studied and solved in this paper using a discrete particle swarm optimization which is refined by a deterministic local search heuristic. Computational results, obtained for eight well-known benchmarks problem, confirm the effectiveness of ...
Computation
Goksal et al. describe how a discrete PSO was implemented for solving combinatorial optimization problems in supply chains, such as the Travelling Sales Problem (TSP), scheduling problems and VRP; even a discrete PSO for the VRP with simultaneous pickup and delivery (VRPSPD) was developed. Moreover, a permutation encoding was implemented to ...
A discrete particle swarm optimization algorithm for the no-wait
The swarm population is constructed as follows: starting from the first job of an identity permutation (1, 2, …, n), the NN heuristic is applied to build a complete NN permutation; then the first phase of the NEH heuristic is ignored and the second phase of the NEH heuristic is applied to the NN permutation to generate a final permutation of the particle so as to be included in the swarm ...
@article{Ahmed2024SurrogateassistedCH, title={Surrogate-assisted constrained hybrid particle swarm optimization algorithm for propane pre-cooled mixed refrigerant LNG process optimization}, author={Rasel Ahmed and Shuhaimi Mahadzir and Jannatul Ferdush and Fahad Matovu and Adrian Mota Babilioni and Rendra Hakim Hafyan}, journal={Energy}, year ...
A Discrete Particle Swarm Optimization for Storage Location Assignment
The optimization model of the storage location assignment problem (SLAP) for retail e-commerce is firstly established based on the principles of efficiency priority, shelf stability and similar products adjacency. Then, a new discrete particle swarm optimization (DPSO) algorithm is proposed to solve the NP-hard SLAP.
A Novel Discrete Particle Swarm Optimization Algorithm for the
The Discrete Particle Swarm Optimization, DPSO, will change the PSO algorithm so it can be applied to discrete optimization problems. This alteration will focus on the velocity update equation. The DPSO was tested in an instance of the Traveling Salesman Problem, att48, 48 points problems proposed by Padberg and Rinaldi, which showed some ...
On modeling and discrete particle swarm optimization for task
Task assignment of cooperating multi Unmanned Aerial Vehicles (UAVs) is a hot problem recently. Considering the main factors include the attack order of UAV, kill probability, survival probability and attack path, the target assignment model in different stages for multi-UAVs is established. Discrete particle swarm optimization (DPSO) algorithm is introduced to solve the complex task ...
A unit commitment method of pumped storage in renewable ...
The problem of unit commitment of pumped storage power stations (UCPS) is rarely discussed in existing works of multi-energy hybrid systems scheduling. It goes against accurately evaluating the operation performance and reliability of the pumped storage unit (PSU). This study proposes a co-optimization scheduling method for a Wind-Photovoltaic-Pumped storage system based on a twofold particle ...
A Combined Marine Predators and Particle Swarm Optimization ...
PSO is a nature inspired meta-heuristic global optimization approach based on swarm intelligence [33].In PSO, the set of candidate solutions to optimization problem is represented as swarm of particles, which may flow via search space determining trajectories which are driven by their performance and their neighbor's best performance.
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COMMENTS
The weapon-target assignment (WTA) problem is an important content in military operational research. In this paper, a discrete particle swarm optimization (DPSO) algorithm is presented to solve the constrained static weapon-target assignment (SWTA) problem subject to firing range constraint, weapon-target match constraint and so on. This constrained SWTA problem with upper bound on the number ...
The combinatorial optimization problem of assigning cooperating unmanned aerial vehicles to multiple tasks is posed by a shared model. A discrete particle swarm optimization algorithm for solving such a problem is proposed. A matrix representation of the algorithm's position vector spaces is employed. A new update strategy for the position and speed of particle is applied in this algorithm ...
This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced into DPSO in which a priority set is constructed to control the local search and converge to the global optimum efficiently. Then the particles would be updated ...
Quadratic Assignment Problems (QAPs) are the hardest of combinatorial optimization problems, with some problems of sizes of the order of 30 still remaining unsolved optimally. ... Keywords: Quadratic Assignment Problem; Discrete Particle Swarm Optimization; Taguchi’s robust design. 1. Introduction The Quadratic Assignment Problem (QAP ...
Particle Swarm Optimization, Discrete Optimization, Cate-gorical Optimization 1. INTRODUCTION Discrete optimization problems, such as feature selection or inference in Bayesian networks, represent an important and challenging set of problems. These di er from continu-ous problems in that each variable can take on only a nite number of states [6].
The problem induces efficient assignment of objects into a knapsack with maximum profit without exceeding the capacity of the knapsack. ... Nagari, A.L., et al.: Implementation of discrete particle swarm optimization algorithm in the capacitated vehicle routing problem. Jurnal Sistem dan Manajemen Industri 4, 117-128 (2020). https://doi.org ...
In many optimisation problems, all or some of decision variables are discrete. Solving such problems are more challenging than those problems with pure continuous variables. Among various optimisation techniques, particle swarm optimisation (PSO) has demonstrated more promising performance in tackling discrete optimisation problems. In PSO, basic variants are merely applicable to continuous ...
The classical Particle Swarm Optimization is a powerful method to find the minimum of a numerical function, on a continuous definition domain. As some binary versions have already successfully been used, it seems quite natural to try to define a framework for a discrete PSO. In order to better understand both the power and the limits of this ...
A discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem and the concept of "permutation" is employed to the update strategy. This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced ...
Terminal assignment problem (TEAP) is to determine minimum cost links to form a network by connecting a given set of terminals to a given collection of concentrators. This paper presents a novel discrete particle swarm optimization (PSO) based on estimation of distribution (EDA), named DPSO-EDA, for TEAP.
In this study, in order to solve the assignment problem from supermarket resources to urban residential communities under the situation of the epidemic control, the discrete multi-objective particle swarm algorithm can be improved by introducing some new strategies, and the probability matrix can be used to simulate the many-to-many assignment ...
As an improved version of PSO, Discrete Particle Swarm Optimization (DPSO) was developed for solving discrete optimization problems such as the minimum labeling Steiner tree problem, grid job ...
A discrete particle swarm optimization (DPSO) algorithm is presented to solve the constrained static weapon-target assignment (SWTA) problem subject to firing range constraint, weapon- target match constraint and so on. The weapon-target assignment (WTA) problem is an important content in military operational research. In this paper, a discrete particle swarm optimization (DPSO) algorithm is ...
The optimization model of the storage location assignment problem (SLAP) for retail e-commerce is firstly established based on the principles of efficiency priority, shelf stability and similar products adjacency. Then, a new discrete particle swarm optimization (DPSO) algorithm is proposed to solve the NP-hard SLAP.
Abstract and Figures. In many optimisation problems, all or some of decision variables are discrete. Solving such problems are more challenging than those problems with pure continuous variables ...
The Particle Swarm Optimization (PSO) is a population-based optimization method first proposed by Kennedy and Eberhart [22]. A swarm, in this context, is a population of several solutions of a given problem, and each solution is seen as an organism in a social environment, also called particle.
This paper presents a discrete particle swarm optimization (DPSO) to solve weapon-target assignment (WTA) problem. The proposed algorithm sponges the advantages of PSO and GA. Originally the greedy searching strategy is introduced into DPSO in which a priority set is constructed to control the local search and converge to the global optimum efficiently. Then the particles would be updated ...
The problem of the fixed-spectrum frequency assignment, where the objective is to minimize the cost due to the interference arising in a solution, is studied and solved in this paper using a discrete particle swarm optimization which is refined by a deterministic local search heuristic. Computational results, obtained for eight well-known benchmarks problem, confirm the effectiveness of ...
Goksal et al. describe how a discrete PSO was implemented for solving combinatorial optimization problems in supply chains, such as the Travelling Sales Problem (TSP), scheduling problems and VRP; even a discrete PSO for the VRP with simultaneous pickup and delivery (VRPSPD) was developed. Moreover, a permutation encoding was implemented to ...
The swarm population is constructed as follows: starting from the first job of an identity permutation (1, 2, …, n), the NN heuristic is applied to build a complete NN permutation; then the first phase of the NEH heuristic is ignored and the second phase of the NEH heuristic is applied to the NN permutation to generate a final permutation of the particle so as to be included in the swarm ...
@article{Ahmed2024SurrogateassistedCH, title={Surrogate-assisted constrained hybrid particle swarm optimization algorithm for propane pre-cooled mixed refrigerant LNG process optimization}, author={Rasel Ahmed and Shuhaimi Mahadzir and Jannatul Ferdush and Fahad Matovu and Adrian Mota Babilioni and Rendra Hakim Hafyan}, journal={Energy}, year ...
The optimization model of the storage location assignment problem (SLAP) for retail e-commerce is firstly established based on the principles of efficiency priority, shelf stability and similar products adjacency. Then, a new discrete particle swarm optimization (DPSO) algorithm is proposed to solve the NP-hard SLAP.
The Discrete Particle Swarm Optimization, DPSO, will change the PSO algorithm so it can be applied to discrete optimization problems. This alteration will focus on the velocity update equation. The DPSO was tested in an instance of the Traveling Salesman Problem, att48, 48 points problems proposed by Padberg and Rinaldi, which showed some ...
Task assignment of cooperating multi Unmanned Aerial Vehicles (UAVs) is a hot problem recently. Considering the main factors include the attack order of UAV, kill probability, survival probability and attack path, the target assignment model in different stages for multi-UAVs is established. Discrete particle swarm optimization (DPSO) algorithm is introduced to solve the complex task ...
The problem of unit commitment of pumped storage power stations (UCPS) is rarely discussed in existing works of multi-energy hybrid systems scheduling. It goes against accurately evaluating the operation performance and reliability of the pumped storage unit (PSU). This study proposes a co-optimization scheduling method for a Wind-Photovoltaic-Pumped storage system based on a twofold particle ...
PSO is a nature inspired meta-heuristic global optimization approach based on swarm intelligence [33].In PSO, the set of candidate solutions to optimization problem is represented as swarm of particles, which may flow via search space determining trajectories which are driven by their performance and their neighbor's best performance.