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We consider the problem of multi-objective optimization (MOO) of expensive black-box functions with the goal of discovering high-quality and diverse Pareto fronts where we are allowed to evaluate a batch of inputs. This problem arises in…

Machine Learning · Computer Science 2024-06-14 Alaleh Ahmadianshalchi , Syrine Belakaria , Janardhan Rao Doppa

This paper presents a multiobjective Home Care Scheduling Problem (from now on multiobjective HCSP) related to a home care company for elderly and dependent people located in the North of Spain. In particular, a biobjective problem is…

Optimization and Control · Mathematics 2024-06-06 Isabel Méndez-Fernández , Silvia Lorenzo-Freire , Ángel Manuel González-Rueda

For the purpose of addressing the multi-objective optimal reactive power dispatch (MORPD) problem, a two-step approach is proposed in this paper. First of all, to ensure the economy and security of the power system, the MORPD model aiming…

Optimization and Control · Mathematics 2020-03-06 Meng Zhang , Yang Li

This paper considers the scheduling of stochastic jobs on parallel identical machines to minimize the expected total weighted completion time. While this is a classical problem with a significant body of research on approximation algorithms…

Data Structures and Algorithms · Computer Science 2026-01-27 Benjamin Moseley , Kirk Pruhs , Marc Uetz , Rudy Zhou

Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, we extend this flower algorithm to solve multi-objective optimization problems in engineering. By using the…

Neural and Evolutionary Computing · Computer Science 2014-04-04 Xin-She Yang , M. Karamanoglu , Xingshi He

We study the problem of scheduling $n$ independent moldable tasks on $m$ processors that arises in large-scale parallel computations. When tasks are monotonic, the best known result is a $(\frac{3}{2}+\epsilon)$-approximation algorithm for…

Data Structures and Algorithms · Computer Science 2023-03-30 Xiaohu Wu , Patrick Loiseau

In this article we provide a comprehensive review of the different evolutionary algorithm techniques used to address multimodal optimization problems, classifying them according to the nature of their approach. On the one hand there are…

Neural and Evolutionary Computing · Computer Science 2015-08-24 Noe Casas

Machine learning techniques have been developed to learn from complete data. When missing values exist in a dataset, the incomplete data should be preprocessed separately by removing data points with missing values or imputation. In this…

Machine Learning · Computer Science 2020-12-25 Hadi A. Khorshidi , Michael Kirley , Uwe Aickelin

In parallel machine scheduling, we are given a set of jobs, together with a number of machines and our goal is to decide for each job, when and on which machine(s) it should be scheduled in order to minimize some objective function.…

Data Structures and Algorithms · Computer Science 2023-02-09 Klaus Jansen , Kai Kahler

Scheduling with testing is a recent online problem within the framework of explorable uncertainty motivated by environments where some preliminary action can influence the duration of a task. Jobs have an unknown processing time that can be…

Data Structures and Algorithms · Computer Science 2021-08-20 Susanne Albers , Alexander Eckl

Mixed-integer optimisation problems can be computationally challenging. Here, we introduce and analyse two efficient algorithms with a specific sequential design that are aimed at dealing with sampled problems within this class. At each…

Optimization and Control · Mathematics 2023-03-07 Mohammadreza Chamanbaz , Roland Bouffanais

Multi-mode resource and precedence-constrained project scheduling is a well-known challenging real-world optimisation problem. An important variant of the problem requires scheduling of activities for multiple projects considering…

Data Structures and Algorithms · Computer Science 2016-09-09 Shahriar Asta , Daniel Karapetyan , Ahmed Kheiri , Ender Özcan , Andrew J. Parkes

This paper considers scheduling on identical machines. The scheduling objective considered in this paper generalizes most scheduling minimization problems. In the problem, there are $n$ jobs and each job $j$ is associated with a…

Data Structures and Algorithms · Computer Science 2019-04-23 Benjamin Moseley

Optimizing multiple, non-preferential objectives for mixed-variable, expensive black-box problems is important in many areas of engineering and science. The expensive, noisy, black-box nature of these problems makes them ideal candidates…

Machine Learning · Computer Science 2022-11-15 Haris Moazam Sheikh , Philip S. Marcus

Many academic disciplines - including information systems, computer science, and operations management - face scheduling problems as important decision making tasks. Since many scheduling problems are NP-hard in the strong sense, there is a…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-05-26 Gerhard Rauchecker , Guido Schryen

A new multi-objective method for the thesis defence scheduling problem is introduced. The problem involves appointing committees to defences and assigning them to a time slot and room. A multi-objective approach is necessary to provide a…

Optimization and Control · Mathematics 2024-11-26 João Almeida , Alexandre Francisco , Daniel Santos , José Rui Figueira

In this paper, we devise a scheduling algorithm for ordering transmission of synchrophasor data from the substation to the control center in as short a time frame as possible, within the realtime hierarchical communications infrastructure…

Information Theory · Computer Science 2015-11-03 K. G. Nagananda , P. P. Khargonekar

In engineering optimization problems, multiple objectives with a large number of variables under highly nonlinear constraints are usually required to be simultaneously optimized. Significant computing effort are required to find the Pareto…

Neural and Evolutionary Computing · Computer Science 2020-08-06 Junfei Zhang , Yimiao Huang , Guowei Ma , Brett Nener

We consider energy-efficient scheduling on multiprocessors, where the speed of each processor can be individually scaled, and a processor consumes power $s^{\alpha}$ when running at speed $s$, for $\alpha>1$. A scheduling algorithm needs to…

Data Structures and Algorithms · Computer Science 2014-10-14 Hongyang Sun , Yuxiong He , Wen-Jing Hsu , Rui Fan

The paper presents a new balanced selection operator applied to the proposed Balanced Non-dominated Tournament Genetic Algorithm (B-NTGA) that actively uses archive to solve multi- and many-objective NP-hard combinatorial optimization…

Neural and Evolutionary Computing · Computer Science 2024-10-15 Michał Antkiewicz , Paweł B. Myszkowski
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