{"id":"W2618694566","doi":"10.1016/j.ejor.2017.05.035","title":"Resource constrained routing and scheduling: Review and research prospects","year":2017,"lang":"en","type":"article","venue":"European Journal of Operational Research","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":108,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Scheduling (production processes); Operations research; Heuristic; Routing (electronic design automation); Service (business); Resource (disambiguation); Management science; Operations management; Business; Computer network; Engineering; Marketing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02773657,0.00009898157,0.0002145015,0.0002293487,0.001077489,0.0007082578,0.0004130699,0.00002649185,0.00005083887],"category_scores_gemma":[0.009449678,0.00008755811,0.0000271295,0.0001687678,0.0004631431,0.0003568178,0.0002536254,0.001145685,0.00001377146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005482899,"about_ca_system_score_gemma":0.0001254085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001280195,"about_ca_topic_score_gemma":3.830054e-7,"domain_scores_codex":[0.9965415,0.001629703,0.0004567126,0.0001708242,0.00087177,0.0003294649],"domain_scores_gemma":[0.9976332,0.0005460178,0.00009221724,0.0002729115,0.001227181,0.0002285395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005901781,0.0005089091,0.04561033,0.01085432,0.001418437,0.004704336,0.01242139,0.1245203,0.1259334,0.1439046,0.07634941,0.4531845],"study_design_scores_gemma":[0.01266738,0.003195221,0.2511869,0.02552688,0.0002338872,0.006796378,0.002926879,0.4985255,0.009862091,0.002180516,0.1844227,0.002475683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.571757,0.07258073,0.02628038,0.04158584,0.0004218591,0.002090552,0.00002420026,0.0001641665,0.2850953],"genre_scores_gemma":[0.9450619,0.004102955,0.04988219,0.00006822026,0.0003568895,0.000002019226,0.000001451311,0.00004559707,0.000478797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4507088,"threshold_uncertainty_score":0.9988942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1414483450789268,"score_gpt":0.4200839522890825,"score_spread":0.2786356072101557,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}