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Although synthetic test problems are widely used for the performance assessment of evolutionary multi-objective optimization algorithms, they are likely to include unrealistic properties which may lead to overestimation/underestimation. To…

Neural and Evolutionary Computing · Computer Science 2020-09-29 Ryoji Tanabe , Hisao Ishibuchi

Model merging combines expert models for multitask performance but faces challenges from parameter interference. This has sparked recent interest in controllable model merging, giving users the ability to explicitly balance performance…

Machine Learning · Computer Science 2025-11-17 Jialin Wu , Jian Yang , Handing Wang , Jiajun Wen , Zhiyong Yu

We study a multi-objective scheduling problem on two dedicated processors. The aim is to minimize simultaneously the makespan, the total tardiness and the total completion time. This NP-hard problem requires the use of well-adapted methods.…

Data Structures and Algorithms · Computer Science 2021-01-05 Adel Kacem , Abdelaziz Dammak

Many real world applications can be framed as multi-objective optimization problems, where we wish to simultaneously optimize for multiple criteria. Bayesian optimization techniques for the multi-objective setting are pertinent when the…

Machine Learning · Computer Science 2019-06-24 Biswajit Paria , Kirthevasan Kandasamy , Barnabás Póczos

Many real-world optimization problems such as engineering design can be eventually modeled as the corresponding multiobjective optimization problems (MOPs) which must be solved to obtain approximate Pareto optimal fronts. Multiobjective…

Neural and Evolutionary Computing · Computer Science 2021-11-12 Wang Chen , Jian Chen , Weitian Wu , Xinmin Yang , Hui Li

Autonomous systems are composed of several subsystems such as mechanical, propulsion, perception, planning and control. These are traditionally designed separately which makes performance optimization of the integrated system a significant…

Robotics · Computer Science 2022-03-01 Hongrui Zheng , Johannes Betz , Rahul Mangharam

Many real-world decision-making problems involve optimizing multiple objectives simultaneously, rendering the selection of the most preferred solution a non-trivial problem: All Pareto optimal solutions are viable candidates, and it is…

Artificial Intelligence · Computer Science 2025-11-17 Niclas Boehmer , Maximilian T. Wittmann

This paper introduces the first objective space algorithm which can exactly find all supported and non-supported non-dominated solutions to a mixed-integer multi-objective linear program with an arbitrary number of objective functions. This…

Optimization and Control · Mathematics 2019-09-10 William Pettersson , Melih Ozlen

Path planning is one of the most vital elements of mobile robotics. With a priori knowledge of the environment, global path planning provides a collision-free route through the workspace. The global path plan can be calculated with a…

Artificial Intelligence · Computer Science 2015-05-25 Alexander Lavin

In this paper, we present a novel approach to efficiently generate collision-free optimal trajectories for multiple non-holonomic mobile robots in obstacle-rich environments. Our approach first employs a graph-based multi-agent path planner…

Robotics · Computer Science 2021-01-29 Juncheng Li , Maopeng Ran , Lihua Xie

Mixed-integer convex programming (MICP) has seen significant algorithmic and hardware improvements with several orders of magnitude solve time speedups compared to 25 years ago. Despite these advances, MICP has been rarely applied to…

Robotics · Computer Science 2022-04-12 A. Cauligi , P. Culbertson , B. Stellato , D. Bertsimas , M. Schwager , M. Pavone

We consider the two-parallel machines scheduling problem, with the aim of minimizing the maximum lateness and the makespan. Formally, the problem is defined as follows. We have to schedule a set J of n jobs on two identical machines. Each…

Data Structures and Algorithms · Computer Science 2018-03-01 Gais Alhadi , Imed Kacem , Pierre Laroche , Izzeldin M. Osman

This paper introduces a new method of partitioning the solution space of a multi-objective optimisation problem for parallel processing, called Efficient Projection Partitioning. This method projects solutions down into a single dimension,…

Optimization and Control · Mathematics 2017-11-23 William Pettersson , Melih Ozlen

In many environmental monitoring scenarios, the sampling robot needs to simultaneously explore the environment and exploit features of interest with limited time. We present an anytime multi-objective informative planning method called…

Robotics · Computer Science 2021-11-04 Weizhe Chen , Lantao Liu

In this paper, we propose a low-rank coordinate descent approach to structured semidefinite programming with diagonal constraints. The approach, which we call the Mixing method, is extremely simple to implement, has no free parameters, and…

Optimization and Control · Mathematics 2026-05-12 Po-Wei Wang , Wei-Cheng Chang , J. Zico Kolter

Submodular maximization is a general optimization problem with a wide range of applications in machine learning (e.g., active learning, clustering, and feature selection). In large-scale optimization, the parallel running time of an…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam

Constrained multiobjective optimization has gained much interest in the past few years. However, constrained multiobjective optimization problems (CMOPs) are still unsatisfactorily understood. Consequently, the choice of adequate CMOPs for…

Neural and Evolutionary Computing · Computer Science 2023-02-07 Aljoša Vodopija , Tea Tušar , Bogdan Filipič

This paper addresses the problem of coordination of a fleet of mobile robots - the problem of finding an optimal set of collision-free trajectories for individual robots in the fleet. Many approaches have been introduced during the last…

Robotics · Computer Science 2019-01-23 Jakub Hvězda , Miroslav Kulich , Libor Přeučil

We propose an approach to find low-makespan solutions to multi-robot multi-task planning problems in environments where robots block each other from completing tasks simultaneously. We introduce a formulation of the problem that allows for…

Robotics · Computer Science 2023-06-06 Valentin N. Hartmann , Marc Toussaint

Soft robot serial chain manipulators with the capability for growth, stiffness control, and discrete joints have the potential to approach the dexterity of traditional robot arms, while improving safety, lowering cost, and providing an…