The teaching–learning-based optimization (TLBO) algorithm is one of the most noted meta-
heuristic algorithms known for its simplicity, fast convergence, and accuracy. Several TLBO …

This paper introduces an innovative resource-constrained time–cost-quality trade-off
optimization model (RCTCQ-TOOM) designed specifically for retrofitting planning projects in …

Duration, cost, and resources are defined as project constraints. Consequently, in each
project, one of these constraints is received attention compared with another. Thus, the …

Balancing discrete time, cost, and resource allocation poses a significant challenge in
construction projects due to their inherent conflicts. The competitive nature of the …

Feature selection is a pivotal preprocessing step in deploying machine learning solutions,
aimed at removing redundant features from datasets while preserving predictive accuracy …

Purpose Most of the existing time-cost-quality-environmental impact trade-off (TCQET)
analysis models have focused on solving a simple project representation without taking …

In recent years, both intelligent robots and drones have been widely used in agriculture. This
paper studies a cooperative task allocation problem of weeding robots and spraying drones …

Dalam proyek konstruksi terdapat triple constrain yang wajib terpenuhi, yaitu waktu, biaya,
dan mutu. Waktu yang optimal, biaya yang minim, dan mutu yang sesuai spesifikasi menjadi …

In response to the RGV speed tracking problem, a multi-strategy enhanced particle swarm
optimization (PSO) algorithm was proposed to optimize the Fuzzy-PID controller. Firstly, the …

This research paper develops a novel hybrid approach, called hybrid particle swarm
optimization–teaching–learning-based optimization (hPSO-TLBO), by combining two …