{"id":"W1210901285","doi":"10.1016/j.ifacol.2015.06.305","title":"On-line Supply Chain Scheduling Problem with Capacity Limited Vehicles","year":2015,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Scheduling and Optimization Algorithms","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Job shop scheduling; Computer science; Scheduling (production processes); Mathematical optimization; Supply chain; Competitive analysis; Robustness (evolution); Operations research; Mathematics; Computer network; Upper and lower bounds; Business; Routing (electronic design automation)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00126614,0.002251513,0.002482651,0.0009479257,0.0013989,0.00217274,0.00209519,0.00268075,0.006733132],"category_scores_gemma":[0.00220394,0.0009426653,0.0007735087,0.001970115,0.0009265008,0.002268741,0.001512515,0.001072799,0.0006146423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001944006,"about_ca_system_score_gemma":0.001494703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008062555,"about_ca_topic_score_gemma":0.005891985,"domain_scores_codex":[0.9983918,0.0006199169,0.00006016041,0.0002579864,0.0002841382,0.0003860257],"domain_scores_gemma":[0.9983231,0.0008752361,0.000331256,0.00009340887,0.0001749991,0.0002020761],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002754662,0.0002004637,0.0006200988,0.0001961708,0.00007269139,0.0005102385,0.0000862344,0.9684054,0.001694859,0.007110197,0.00191309,0.01891515],"study_design_scores_gemma":[0.00006540443,0.000163574,0.000209175,0.00001431491,0.00002080632,0.0001056299,0.00008023054,0.9877189,0.0006972053,0.00913245,0.00177702,0.00001538237],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3040654,0.0012997,0.6610792,0.001362458,0.0003238138,0.0007706162,0.0009901284,0.0005148506,0.02959395],"genre_scores_gemma":[0.9215772,0.0009345525,0.06403391,0.0001949766,0.0001871807,0.0003483485,0.0007320898,0.000112872,0.01187894],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008062555,"threshold_uncertainty_score":0.02252454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02993425478790617,"score_gpt":0.2288458763730954,"score_spread":0.1989116215851892,"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."}}