Results 21 to 30 of about 66,599 (198)
On the use of biased-randomized algorithms for solving non-smooth optimization problems [PDF]
, 2020 Soft constraints are quite common in real-life applications. For example, in freight transportation, the fleet size can be enlarged by outsourcing part of the distribution service and some deliveries to customers can be postponed as well; in inventory ...
Ferrer Biosca, Albert +4 more
core +3 more sources
Ant Colony Optimization with Warm-Up
Algorithms, 2021 The Ant Colony Optimization (ACO) is a probabilistic technique inspired by the behavior of ants for solving computational problems that may be reduced to finding the best path through a graph.
Mattia Neroni
doaj +1 more source
IEEE Access, 2023 An improved hybrid grey wolf optimization algorithm (IHGWO) is proposed to solve the problem of population diversity, imbalance of exploration and development capabilities, and premature convergence.
Chuanjing Zhang +3 more
doaj +1 more source
On the Neutrality of Flowshop Scheduling Fitness Landscapes [PDF]
, 2011 Solving efficiently complex problems using metaheuristics, and in particular local searches, requires incorporating knowledge about the problem to solve. In this paper, the permutation flowshop problem is studied.
C.O. Wilke +15 more
core +6 more sources
Firefly Algorithm, Stochastic Test Functions and Design Optimisation [PDF]
, 2010 Modern optimisation algorithms are often metaheuristic, and they are very promising in solving NP-hard optimization problems. In this paper, we show how to use the recently developed Firefly Algorithm to solve nonlinear design problems.
Yang, Xin-She
core +1 more source
Accelerated Particle Swarm Optimization and Support Vector Machine for Business Optimization and Applications [PDF]
, 2011 Business optimization is becoming increasingly important because all business activities aim to maximize the profit and performance of products and services, under limited resources and appropriate constraints.
A. Chatterjee +23 more
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Multi-Objective Big Data Optimization with jMetal and Spark [PDF]
, 2017 Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi ...
A Cabanas-Abascal +11 more
core +1 more source
A variable neighborhood search simheuristic for project portfolio selection under uncertainty [PDF]
, 2018 With limited nancial resources, decision-makers in rms and governments face the task of selecting the best portfolio of projects to invest in. As the pool of project proposals increases and more realistic constraints are considered, the problem becomes
Döering, Jana +4 more
core +1 more source
Lemurs Optimizer: A New Metaheuristic Algorithm for Global Optimization
Applied Sciences, 2022 The Lemur Optimizer (LO) is a novel nature-inspired algorithm we propose in this paper. This algorithm’s primary inspirations are based on two pillars of lemur behavior: leap up and dance hub.
Ammar Kamal Abasi +9 more
doaj +1 more source
The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms [PDF]
, 2020 open access articleWe present Stochastic Optimisation Software (SOS), a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms.
Caraffini, Fabio, Iacca, Giovani
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