A Multi-Objective Water Cycle Algorithm for the BI-Objective Multi-Mode Project Resource Renting Problem
Why this work is in the frame
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Bibliographic record
Abstract
A resource renting problem is a project scheduling problem in which the required resources should be rented, and the goal is to find a schedule and resource renting plan such that the total cost of the resources minimises.Traditionally, the model of a resource renting problem contains single-mode activities and a single objective function.This research aims to present a new mathematical model for a bi-objective multi-mode resource renting problem.The objectives are to minimise the project makespan and also the total cost of resources, including the time-independent resource procurement costs and time-dependent resource renting costs, simultaneously.A novel evolutionary algorithm, namely the Multi-Objective Water Cycle Algorithm (MOWCA), is employed to solve this NP-hard problem.In order to evaluate the proposed algorithm, the Non-Dominated Sorting Genetic Algorithm (NSGA-II) is applied, too.A set of instances is selected from the digital library of project scheduling problems to analyse the performances of evolutionary algorithms.The results of the experimentation are quite satisfactory.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it