Results 61 to 70 of about 9,338 (286)

Introduction to the multi-skilled resource constrained multi project and multi type scheduling problem [PDF]

Journal of Project Management
In this paper, we extend the multi-skilled resource-constrained multi-project scheduling problem (MSRCMPSP) by introducing the concept of multiple project types (MSRCMPMTSP). The study considers two categories of projects: investment projects, which
Yasemin Arici, Semih Eren Karakiliç, Declan O'connor, Andreas Thümmel   +3 more
doaj   +1 more source

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

A Hybrid Genetic Wind Driven Heuristic Optimization Algorithm for Demand Side Management in Smart Grid

Energies, 2017
In recent years, demand side management (DSM) techniques have been designed for residential, industrial and commercial sectors. These techniques are very effective in flattening the load profile of customers in grid area networks.
Nadeem Javaid, Sakeena Javaid, Wadood Abdul, Imran Ahmed, Ahmad Almogren, Atif Alamri, Iftikhar Azim Niaz   +6 more
doaj   +1 more source

Developing Multistage Heuristic Algorithm To Minimize Idle Time And Makespan In Job Shop Scheduling [PDF]

Engineering and Technology Journal, 2010
The behavior and performance of job shops have been the focus andattention in both operations research and operations management literature. Job shop scheduling has received this large amount of attention, because it has the potential to dramatically ...
Mahmoud Abbas Mahmoud
doaj   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

Advanced Robotics Research, EarlyView.
Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +3 more
wiley   +1 more source

Smart REASSURED Sensors via Machine‐Augmented Printable On‐Paper Arrays

Advanced Sensor Research, EarlyView.
This perspective highlights the emerging role of pattern‐recognition, printable on‐paper sensor arrays for intelligent PoC diagnostics. It discusses how paper's inherent limitations can be overcome through surface modification and scalable printing, and how machine‐learning analysis of cross‐reactive arrays enables multiplexed, low‐cost, and REASSURED ...
Naimeh Naseri, Saba Ranjbar
wiley   +1 more source

Factors Driving Battery and Solar Purchase Decision of Residents: a Behavioural Choice Experiment Using a Hybrid Discrete Choice and Latent Variable Model

Advanced Sustainable Systems, EarlyView.
This article explores what drives households to adopt solar PV and battery systems in South East Queensland. Using hybrid discrete choice experiments, it reveals distinct adopter profiles and highlights cost, system size, and energy independence as key motivators.
Mohammad Alipour, Elnaz Irannezhad, Rodney A. Stewart, Oz Sahin   +3 more
wiley   +1 more source

Ant colony optimization in project management

Computer Assisted Methods in Engineering and Science, 2022
This paper presents an Ant Colony Optimization (ACO) approach to the resource-constrained project scheduling problem (RCPSP). RCPSP as a generalization of the classical job shop scheduling problem belongs to the class of NP-hard optimization problems ...
Bożena Skołud, Bożena Marcińczyk
doaj  

Data‐Driven Multi‐Objective Optimization of Large‐Diameter Si Floating‐Zone Crystal Growth

Advanced Theory and Simulations, EarlyView.
This study presents a surrogate‐based Multi‐Objective Optimization framework for Floating Zone silicon crystal growth. An ensemble of Neural Networks is trained on simulation data and combined with Genetic Algorithms to explore trade‐offs in process parameters.
Lucas Vieira, Milena Petković, Robert Menzel, Natasha Dropka   +3 more
wiley   +1 more source

Heuristic decision of planned shop visit products based on similar reasoning method: From the perspective of organizational quality-specific immune

Open Physics, 2020
The purpose of this study is to reduce the maintenance time, cost, and scheduling distance and to determine the maintenance priority of planned shop visit products.
Liu Qiang, Lian Zhifeng, Guo Yu, Tang Shulin, Yang Feixue   +4 more
doaj   +1 more source