Results 71 to 80 of about 22,962 (193)

A Two‐Stage Optimization Model for Multiple‐Crane Service Schedules Problem

Advances in Civil Engineering, Volume 2026, Issue 1, 2026.
Scheduling tower crane movements is essential in a large construction site where multiple cranes are deployed. Efficient planning can avoid potential crane collisions, reduce construction duration, and save energy consumption. The multiple‐crane service schedules problem (MCSSP) is a classic combinatorial problem.
Wen-Qi Wang, Yang He, Hao-Chen Shen, Meng Liu, Xiang-Qian Li, Chun Huang, Hassan Nasir   +6 more
wiley   +1 more source

Behavior of the main parameters of the Genetic Algorithm for Flow Shop Scheduling Problems

Revista Cubana de Ciencias Informáticas, 2014
There are different suggested values to adapt the basic parameters of a Genetic Algorithm, however, these values may not be the optimal for all kinds of applications.
Yunior César Fonseca Reyna, Yailen Martínez Jiménez, Ángel Enrique Figueredo León, Luis Alberto Pernía Nieves   +3 more
doaj  

Minimum‐Peak‐Cost Flows Over Time

Networks, Volume 86, Issue 4, Page 389-401, December 2025.
ABSTRACT Peak cost is a novel objective for flows over time that describes the amount of workforce necessary to run a system. We focus on minimizing peak costs in the context of maximum temporally repeated flows and formulate the corresponding MPC‐MTRF problem.
Mariia Anapolska, Emma Ahrens, Christina Büsing, Felix Engelhardt, Timo Gersing, Corinna Mathwieser, Sabrina Schmitz, Sophia Wrede   +7 more
wiley   +1 more source

Portable PGAS‐Based GPU‐Accelerated Branch‐And‐Bound Algorithms at Scale

Concurrency and Computation: Practice and Experience, Volume 37, Issue 25-26, 30 November 2025.
ABSTRACT The Branch‐and‐Bound (B&B) technique plays a key role in solving many combinatorial optimization problems, enabling efficient problem‐solving and decision‐making in a wide range of applications. It incrementally constructs a tree by building candidates to the solutions and abandoning a candidate as soon as it determines that it cannot lead to ...
Guillaume Helbecque, Ezhilmathi Krishnasamy, Tiago Carneiro, Nouredine Melab, Pascal Bouvry   +4 more
wiley   +1 more source

Abandoned project restoration model (APRM) for residential construction projects [PDF]

, 2017
Incompletion of construction projects is a common phenomenon in Malaysia. Project abandonment has given an adverse consequences to the economy, society and environment. In the best interest of the end users and other parties involved in the contract, the
Doraisamy, Sanitha V.
core  

A Hybrid Task Scheduling Technique in Fog Computing Using Fuzzy Logic and Deep Reinforcement Learning

IEEE Access
This work presents an innovative method for scheduling tasks in a fog computing environments by combining the fuzzy logic with deep reinforcement learning.
Prashanth Choppara, S. Sudheer Mangalampalli   +1 more
doaj   +1 more source

A Comprehensive Survey on LLM‐Based Network Management and Operations

International Journal of Network Management, Volume 35, Issue 6, November/December 2025.
ABSTRACT The growing demands for network capacity and the increasing complexities of modern network environments pose significant challenges for effective network management and operations. In response, network operators and administrators are moving beyond traditional manual and rule‐based methods, adopting advanced artificial intelligence (AI)‐driven
Jibum Hong, Nguyen Van Tu, James Won‐Ki Hong   +2 more
wiley   +1 more source

Traveling salesman problem with drone and bicycle: multimodal last‐mile e‐mobility

International Transactions in Operational Research, Volume 32, Issue 6, Page 3232-3258, November 2025.
Abstract Recently, the multimodal last‐mile e‐mobility concept has been at the center of attention for cleaner, greener, and more accessible urban deliveries. As part of sustainable transportation systems, multimodal e‐mobility is proper for a variety of logistics operations as well as medical applications.
Erfan Babaee Tirkolaee, Emre Cakmak, Saliha Karadayi‐Usta   +2 more
wiley   +1 more source

Efficient Task Scheduling and Load Balancing in Fog Computing for Crucial Healthcare Through Deep Reinforcement Learning

IEEE Access
In healthcare, real-time decision making is crucial for ensuring timely and accurate patient care. However, traditional computing infrastructures, with their wide ranging capabilities, suffer from inherent latency, which compromises the efficiency of ...
Prashanth Choppara, Bommareddy Lokesh
doaj   +1 more source

PENDEKATAN ALGORITMA CROSS ENTROPY-GENETIC ALGORITHM UNTUK MENURUNKAN MAKESPAN PADA PENJADWALAN FLOW SHOP

Journal of Engineering and Management in Industrial System, 2014
In the flow shop scheduling each job will go through every machine in the same order. The goal of this research is to complete a series of jobs in order to obtain the optimal makespan  for stick skewers rounding machine.
Dian Setiya Widodo, Purnomo Budi Santoso, Eko Siswanto   +2 more
doaj   +1 more source