{"id":"W2957530701","doi":"","title":"Heuristics for the dynamic facility location problem with modular capacities","year":2019,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Vehicle Routing Optimization Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Group for Research in Decision Analysis; Université Laval","funders":"","keywords":"Heuristics; Benchmark (surveying); Mathematical optimization; Modular design; Heuristic; Time horizon; Genetic algorithm; Computer science; Facility location problem; Variable (mathematics); Integer programming; Point (geometry); Mathematics","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":[0.001735141,0.0007760345,0.0006851138,0.0009975672,0.0003316544,0.0007307701,0.001525666,0.0009242997,0.002662062],"category_scores_gemma":[0.003399766,0.0004752901,0.0006555598,0.001204633,0.000694785,0.0008355683,0.0009147798,0.000750961,0.0002179919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293658,"about_ca_system_score_gemma":0.000967939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004196298,"about_ca_topic_score_gemma":0.004599757,"domain_scores_codex":[0.9992191,0.0004062738,0.00002400647,0.0001225154,0.0001027538,0.0001252647],"domain_scores_gemma":[0.998086,0.001413538,0.0002136994,0.0001088636,0.00009898691,0.00007895636],"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":[0.00004082483,0.00004124953,0.0002820464,0.0000495991,0.00001557334,0.00003954901,0.00001973379,0.9765354,0.000497298,0.00595099,0.0005577015,0.01597014],"study_design_scores_gemma":[0.00002399778,0.00004391814,0.0001193508,0.00001154417,0.000007140086,0.00002270496,0.00001857109,0.9948949,0.0004218794,0.003850636,0.0005800662,0.000005291377],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09468014,0.0004618645,0.8984454,0.0002541591,0.00004550078,0.0002030796,0.0002186434,0.0004157571,0.005275523],"genre_scores_gemma":[0.6310843,0.000244968,0.3661599,0.00008726012,0.00003814502,0.0002183163,0.0003035928,0.00007436038,0.001789317],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004196298,"threshold_uncertainty_score":0.009386182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008236871715568514,"score_gpt":0.2170081944015468,"score_spread":0.2087713226859783,"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."}}