This study proposes an improved version of teaching learning-based optimization (TLBO)
with a modified dynamic-opposition learning (MDOL) strategy, called modified dynamic …

This paper presents an improving teaching-learning-based optimization algorithm (called
DRCMTLBO) combined with the dynamic ring neighborhood topology. Firstly, based on the …

Balancing cost and time present a critical yet conflicting challenge in scheduling of
construction projects. In today; s highly competitive construction market, achieving a subtle …

The Mayfly Optimization Algorithm (MOA), as a new biomimetic metaheuristic algorithm with
superior algorithm framework and optimization methods, plays a remarkable role in solving …

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

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 …

Traditional essay scoring methods not only consume tremendous manpower and financial
resources, but also the scoring results are easily affected by subjective factors. To improve …

This paper presents a novel time-cost-environmental impact trade-off optimization Model
(TCETOM) designed specifically for retrofitting projects in densely populated areas, with a …

This study introduces a modified quasi-opposition learning Jaya optimization (MQOL-Jaya)
algorithm to address time–cost-trade-off (TCTP) optimization problems. The proposed …