Multi-objective scheduling in an agent based Holonic manufacturing system
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The present paper is aimed at multi-objective scheduling in an agent based holonic manufacturing system to satisfy the goal of several communities namely the product, the resource, and the organization simultaneously. In this attempt, first a multi criteria based priority rule is developed following Simple Additive Weight (SAW) method under Multi Criteria Decision Making (MCDM) environment to rank the products. Accordingly, the products are allowed to select a particular resource for execution by negotiation considering minimum time as criterion. The interests of different communities are accomplished by allocating the ordered rank of products to the ordered rank of resources. Conflict, if arises between products and resources, are resolved by introducing the concept of Early Finish Time (EFT) as criterion for task allocation. A scheduling algorithm is proposed for execution of the rule. In view of machine failure, a cooperation strategy is evolved that also optimizes reallocation of the incomplete task. It is concluded that the proposed scheduling algorithm together with the disturbance handling algorithm are poised to satisfy the agent's local objective as well as organization's global objective concurrently and are commensurable with multi agent paradigm.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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