Local search (optimization) ≈ Local search (optimization)
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A Micro-GA Embedded PSO Feature Selection Approach to Intelligent Facial Emotion Recognition Open
This paper proposes a facial expression recognition system using evolutionary particle swarm optimization (PSO)-based feature optimization. The system first employs modified local binary patterns, which conduct horizontal and vertical neig…
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Effective heuristics and metaheuristics to minimize total flowtime for the distributed permutation flowshop problem Open
Distributed permutation flowshop scheduling problem (DPFSP) has become a very active research area in recent years. However, minimizing total flowtime in DPFSP, a very relevant and meaningful objective for today's dynamic manufacturing env…
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Ant Colony Optimization With Local Search for Dynamic Traveling Salesman Problems Open
For a dynamic traveling salesman problem (DTSP), the weights (or traveling times) between two cities (or nodes) may be subject to changes. Ant colony optimization (ACO) algorithms have proved to be powerful methods to tackle such problems …
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Electric Vehicle Routing Problem with Battery Swapping Considering Energy Consumption and Carbon Emissions Open
In this paper, we study an electric vehicle routing problem while considering the constraints on battery life and battery swapping stations. We first introduce a comprehensive model consisting of speed, load and distance to measure the ene…
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Global and Local Surrogate-Assisted Differential Evolution for Expensive Constrained Optimization Problems With Inequality Constraints Open
For expensive constrained optimization problems (ECOPs), the computation of objective function and constraints is very time-consuming. This paper proposes a novel global and local surrogate-assisted differential evolution (DE) for solving …
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Multi-trip time-dependent vehicle routing problem with time windows Open
10.1016/j.ejor.2020.09.022
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A multi-swarm particle swarm optimization algorithm based on dynamical topology and purposeful detecting Open
This paper proposes a multi-swarm particle swarm optimization (MSPSO) that consists of three novel strategies to balance the exploration and exploitation abilities. The new proposed MSPSO in this work is based on multiple swarms framework …
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A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems Open
Controlling active/reactive power in distribution systems has a great impact on its performance. The placement of distributed generators (DGs) and shunt capacitors (SCs) are the most popular mechanisms to improve the distribution system pe…
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Autoencoding Evolutionary Search With Learning Across Heterogeneous Problems Open
To enhance the search performance of evolutionary algorithms, reusing knowledge captured from past optimization experiences along the search process has been proposed in the literature, and demonstrated much promise. In the literature, the…
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A Modified Sine-Cosine Algorithm Based on Neighborhood Search and Greedy Levy Mutation Open
For the deficiency of the basic sine-cosine algorithm in dealing with global optimization problems such as the low solution precision and the slow convergence speed, a new improved sine-cosine algorithm is proposed in this paper. The impro…
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An Effective Hybrid Genetic Algorithm and Variable Neighborhood Search for Integrated Process Planning and Scheduling in a Packaging Machine Workshop Open
Process planning and scheduling are modeled sequentially in the traditional manufacturing system. However, because of their complementarity, the increasing need to integrate them has emerged to enhance the manufacturing productivity signif…
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The DIRECT algorithm: 25 years Later Open
Introduced in 1993, the DIRECT global optimization algorithm provided a fresh approach to minimizing a black-box function subject to lower and upper bounds on the variables. In contrast to the plethora of nature-inspired heuristics, DIRECT…
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GWO-LPWSN: Grey Wolf Optimization Algorithm for Node Localization Problem in Wireless Sensor Networks Open
Seyedali Mirjalili et al. (2014) introduced a completely unique metaheuristic technique particularly grey wolf optimization (GWO). This algorithm mimics the social behavior of grey wolves whereas it follows the leadership hierarchy and att…
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A Multi-Objective Ant Colony System Algorithm for Airline Crew Rostering Problem With Fairness and Satisfaction Open
The airline crew rostering problem (CRP) is significant for balancing the workload of crew and for improving the satisfaction rate of crew's preferences, which is related to the fairness and satisfaction of crew. However, most existing wor…
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A Novel Cooperative Multi-Stage Hyper-Heuristic for Combination Optimization Problems Open
A hyper-heuristic algorithm is a general solution framework that adaptively selects the optimizer to address complex problems. A classical hyper-heuristic framework consists of two levels, including the high-level heuristic and a set of lo…
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Recent Methodology-Based Gradient-Based Optimizer for Economic Load Dispatch Problem Open
Economic load dispatch (ELD) in power system problems involves scheduling the power generating units to minimize cost and satisfy system constraints. Although previous works propose solutions to reduce CO2 emission and production cost, an …
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An adaptive hybrid genetic algorithm for pavement management Open
The pavement maintenance and rehabilitation (M&R) strategy selection problem is an exceedingly hard problem to solve optimally. In this paper, a novel Adaptive Hybrid Genetic Algorithm (AHGA) is proposed which incorporates Local Search (LS…
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New binary bat algorithm for solving 0–1 knapsack problem Open
This paper presents a novel binary bat algorithm (NBBA) to solve 0–1 knapsack problems. The proposed algorithm combines two important phases: binary bat algorithm (BBA) and local search scheme (LSS). The bat algorithm enables the bats to e…
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A Niching Memetic Algorithm for Multi-Solution Traveling Salesman Problem Open
Multi-solution problems extensively exist in practice. Particularly, the traveling salesman problem (TSP) may possess multiple shortest tours, from which travelers can choose one according to their specific requirements. However, very few …
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Two Efficient Local Search Algorithms for Maximum Weight Clique Problem Open
The Maximum Weight Clique problem (MWCP) is an important generalization of the Maximum Clique problem with wide applications. This paper introduces two heuristics and develops two local search algorithms for MWCP. Firstly, we propose a heu…
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SHADE with Iterative Local Search for Large-Scale Global Optimization Open
Global optimization is a very important topic in research due to its wide applications in many real-world problems in science and engineering. Among optimization problems, dimensionality is one of the most crucial issues that increases the…
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Ant Colony Optimization Based Memetic Algorithm to Solve Bi-Objective Multiple Traveling Salesmen Problem for Multi-Robot Systems Open
This paper considers the problem of having a team of mobile robots to visit a set of target locations. This problem is known as multi-robot patrolling problems. In this paper, the problem is formulated as a multiple traveling salesman prob…
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LSHADE-SPA memetic framework for solving large-scale optimization problems Open
During the last decade, large-scale global optimization has been one of the active research fields. Optimization algorithms are affected by the curse of dimensionality associated with this kind of complex problems. To solve this problem, a…
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The Electric Vehicle Routing Problem with Capacitated Charging Stations Open
Electric vehicle routing problems (E-VRPs) deal with routing a fleet of electric vehicles (EVs) to serve a set of customers while minimizing an operational criterion, for example, cost or time. The feasibility of the routes is constrained …
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A Novel Sparrow Search Algorithm for the Traveling Salesman Problem Open
The sparrow search algorithm (SSA) tends to fall into local optima and to have insufficient stagnation when applied to the traveling salesman problem (TSP). To address this issue, we propose a novel greedy genetic sparrow search algorithm …
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A Learning Sparrow Search Algorithm Open
This paper solves the drawbacks of traditional intelligent optimization algorithms relying on 0 and has good results on CEC 2017 and benchmark functions, which effectively improve the problem of algorithms falling into local optimality. Th…
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The multiple team formation problem using sociometry Open
This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/
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Opposition-Based Memetic Search for the Maximum Diversity Problem Open
International audience
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An Improved Binary Cuckoo Search Algorithm for Solving Unit Commitment Problems: Methodological Description Open
The unit commitment problem is a large-scale, nonlinear, and mixed-integer optimization problem in an electric power system. Numerous researchers concentrate on minimizing its total generation cost. Cuckoo search is an efficient metaheuris…
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A hybrid genetic algorithm and tabu search for minimizing makespan in flow shop scheduling problem Open
This paper combines the tabu search process with a genetic algorithm by employing a new partial opposed-based as the population initialization technique to minimize makespan. Flow shop is a prominent variety in scheduling with various appl…