博哥万T资源库（连续6年更新）-2024更新一区-/【职业技能专区】/人工智能合集/40G人工智能算法课/043_Discrete Optimization

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2 - 1 - Course Motivation - Indiana Jones, challenges, applications (20_49).srt
2 - 1 - Course Motivation - Indiana Jones, challenges, applications (20_49).txt
2 - 2 - Course Introduction - philosophy, design, grading rubric (11_30).srt
2 - 2 - Course Introduction - philosophy, design, grading rubric (11_30).txt
2 - 3 - Knapsack 1 - intuition (2_29).srt
2 - 3 - Knapsack 1 - intuition (2_29).txt
2 - 4 - Knapsack 2 - greedy algorithms (7_10).srt
2 - 4 - Knapsack 2 - greedy algorithms (7_10).txt
2 - 5 - Knapsack 3 - modeling (8_56).srt
2 - 5 - Knapsack 3 - modeling (8_56).txt
2 - 6 - Knapsack 4 - dynamic programming (17_58).srt
2 - 6 - Knapsack 4 - dynamic programming (17_58).txt
2 - 7 - Knapsack 5 - relaxation, branch and bound (14_49).srt
2 - 7 - Knapsack 5 - relaxation, branch and bound (14_49).txt
2 - 8 - Knapsack 6 - search strategies, depth first, best first, least discrepancy (14_41).srt
2 - 8 - Knapsack 6 - search strategies, depth first, best first, least discrepancy (14_41).txt
2 - 9 - Exploring the Material - open course design, optimization landscape, picking your adventure (10_06).srt
2 - 9 - Exploring the Material - open course design, optimization landscape, picking your adventure (10_06).txt
3 - 1 - CP 1 - intuition, computational paradigm, map coloring, n-queens (27_16).srt
3 - 1 - CP 1 - intuition, computational paradigm, map coloring, n-queens (27_16).txt
3 - 10 - CP 10 - value-variable labeling, domain splitting, symmetry breaking in search (28_45).srt
3 - 10 - CP 10 - value-variable labeling, domain splitting, symmetry breaking in search (28_45).txt
3 - 2 - CP 2 - propagation, arithmetic constraints, send+more=money (26_20).srt
3 - 2 - CP 2 - propagation, arithmetic constraints, send+more=money (26_20).txt
3 - 3 - CP 3 - reification, element constraint, magic series, stable marriage (16_49).srt
3 - 3 - CP 3 - reification, element constraint, magic series, stable marriage (16_49).txt
3 - 4 - CP 4 - global constraint intuition, table constraint, sudoku (19_23).srt
3 - 4 - CP 4 - global constraint intuition, table constraint, sudoku (19_23).txt
3 - 5 - CP 5 - symmetry breaking, BIBD, scene allocation (18_30).srt
3 - 5 - CP 5 - symmetry breaking, BIBD, scene allocation (18_30).txt
3 - 6 - CP 6 - redundant constraints, magic series, market split (11_35).srt
3 - 6 - CP 6 - redundant constraints, magic series, market split (11_35).txt
3 - 7 - CP 7 - car sequencing, dual modeling (18_20).srt
3 - 7 - CP 7 - car sequencing, dual modeling (18_20).txt
3 - 8 - CP 8 - global constraints in detail, knapsack, alldifferent (33_44).srt
3 - 8 - CP 8 - global constraints in detail, knapsack, alldifferent (33_44).txt
3 - 9 - CP 9 - search, first-fail, euler knight, ESDD (24_49).srt
3 - 9 - CP 9 - search, first-fail, euler knight, ESDD (24_49).txt
4 - 1 - LS 1 - intuition, n-queens (13_57).srt
4 - 1 - LS 1 - intuition, n-queens (13_57).txt
4 - 2 - LS 2 - swap neighborhood, car sequencing, magic square (15_14).srt
4 - 2 - LS 2 - swap neighborhood, car sequencing, magic square (15_14).txt
4 - 3 - LS 3 - optimization, warehouse location, traveling salesman, 2-opt, k-opt (23_09).srt
4 - 3 - LS 3 - optimization, warehouse location, traveling salesman, 2-opt, k-opt (23_09).txt
4 - 4 - LS 4 - optimality vs feasibility, graph coloring (22_18).srt
4 - 4 - LS 4 - optimality vs feasibility, graph coloring (22_18).txt
4 - 5 - LS 5 - complex neighborhoods, sports scheduling (22_42).srt
4 - 5 - LS 5 - complex neighborhoods, sports scheduling (22_42).txt
4 - 6 - LS 6 - escaping local minima, connectivity (15_39).srt
4 - 6 - LS 6 - escaping local minima, connectivity (15_39).txt
4 - 7 - LS 7 - formalization, heuristics, meta-heuristics introduction (22_46).srt
4 - 7 - LS 7 - formalization, heuristics, meta-heuristics introduction (22_46).txt
4 - 8 - LS 8 - iterated location search, metropolis heuristic, simulated annealing, tabu search intuition (18_54).srt
4 - 8 - LS 8 - iterated location search, metropolis heuristic, simulated annealing, tabu search intuition (18_54).txt
4 - 9 - LS 9 - tabu search formalized, aspiration, car sequencing, n-queens (26_37).srt
4 - 9 - LS 9 - tabu search formalized, aspiration, car sequencing, n-queens (26_37).txt
5 - 1 - LP 1 - intuition, convexity, geometric view (24_14).srt
5 - 1 - LP 1 - intuition, convexity, geometric view (24_14).txt
5 - 10 - MIP 4 - convex hull, polyhedral cuts, warehouse location, node packing, graph coloring (19_20).srt
5 - 10 - MIP 4 - convex hull, polyhedral cuts, warehouse location, node packing, graph coloring (19_20).txt
5 - 11 - MIP 5 - cover cuts, branch and cut, seven bridges, traveling salesman (31_21).srt
5 - 11 - MIP 5 - cover cuts, branch and cut, seven bridges, traveling salesman (31_21).txt
5 - 2 - LP 2 - algebraic view, naive algorithm (13_42).srt
5 - 2 - LP 2 - algebraic view, naive algorithm (13_42).txt
5 - 3 - LP 3 - the simplex algorithm (32_22).srt
5 - 3 - LP 3 - the simplex algorithm (32_22).txt
5 - 4 - LP 4 - matrix notation, the tableau (20_52).srt
5 - 4 - LP 4 - matrix notation, the tableau (20_52).txt
5 - 5 - LP 5 - duality derivation (22_00).srt
5 - 5 - LP 5 - duality derivation (22_00).txt
5 - 6 - LP 6 - duality interpretation and uses (17_00).srt
5 - 6 - LP 6 - duality interpretation and uses (17_00).txt
5 - 7 - MIP 1 - intuition, relaxation, branch and bound, knapsack, warehouse location (26_16).srt
5 - 7 - MIP 1 - intuition, relaxation, branch and bound, knapsack, warehouse location (26_16).txt
5 - 8 - MIP 2 - modeling, big-M, warehouse location, graph coloring (28_25).srt
5 - 8 - MIP 2 - modeling, big-M, warehouse location, graph coloring (28_25).txt
5 - 9 - MIP 3 - cutting planes, Gomory cuts (20_47).srt
5 - 9 - MIP 3 - cutting planes, Gomory cuts (20_47).txt
6 - 1 - Large Neighborhood Search - asymmetric TSP with time windows (8_42).srt
6 - 1 - Large Neighborhood Search - asymmetric TSP with time windows (8_42).txt
6 - 2 - Column Generation - branch and price, cutting stock (23_04).srt
6 - 2 - Column Generation - branch and price, cutting stock (23_04).txt
6 - 3 - Scheduling - jobshop, disjunctive global constraint (37_13).srt
6 - 3 - Scheduling - jobshop, disjunctive global constraint (37_13).txt
7 - 1 - Getting Started (13_42).srt
7 - 1 - Getting Started (13_42).txt
7 - 2 - Introduction & Screen Name (13_47).srt
7 - 2 - Introduction & Screen Name (13_47).txt
7 - 3 - Knapsack & External Solver (12_13).srt
7 - 3 - Knapsack & External Solver (12_13).txt
7 - 4 - Graph Coloring (6_23).srt
7 - 4 - Graph Coloring (6_23).txt
7 - 5 - Traveling Salesman (10_38).srt
7 - 5 - Traveling Salesman (10_38).txt
7 - 6 - Facility Location (9_37).srt
7 - 6 - Facility Location (9_37).txt
7 - 7 - Vehicle Routing (14_19).srt
7 - 7 - Vehicle Routing (14_19).txt
7 - 8 - Optimization Tools (6_00).srt
7 - 8 - Optimization Tools (6_00).txt
8 - 1 - Set Cover (9_11).srt
8 - 1 - Set Cover (9_11).txt
Additional Materials.html
assign-getting-started.pdf
coloring.zip
Discrete Optimization 0.0 Course Motivation - Indiana Jones challenges applications (2049).mp4
Discrete Optimization 0.1 Course Introduction - philosophy design grading rubric (1130).mp4
Discrete Optimization 0.2 Knapsack 1 - intuition (229).mp4
Discrete Optimization 0.3 Knapsack 2 - greedy algorithms (710).mp4
Discrete Optimization 0.4 Knapsack 3 - modeling (856).mp4
Discrete Optimization 0.5 Knapsack 4 - dynamic programming (1758).mp4
Discrete Optimization 0.6 Knapsack 5 - relaxation branch and bound (1449).mp4
Discrete Optimization 0.7 Knapsack 6 - search strategies depth first best first least discrepancy (1441).mp4
Discrete Optimization 0.8 Exploring the Material - open course design optimization landscape picking your adventure (1006).mp4
Discrete Optimization 1.0 CP 1 - intuition computational paradigm map coloring n-queens (2716).mp4
Discrete Optimization 1.1 CP 2 - propagation arithmetic constraints send+more=money (2620).mp4
Discrete Optimization 1.2 CP 3 - reification element constraint magic series stable marriage (1649).mp4
Discrete Optimization 1.3 CP 4 - global constraint intuition table constraint sudoku (1923).mp4
Discrete Optimization 1.4 CP 5 - symmetry breaking BIBD scene allocation (1830).mp4
Discrete Optimization 1.5 CP 6 - redundant constraints magic series market split (1135).mp4
Discrete Optimization 1.6 CP 7 - car sequencing dual modeling (1820).mp4
Discrete Optimization 1.7 CP 8 - global constraints in detail knapsack alldifferent (3344).mp4
Discrete Optimization 1.8 CP 9 - search first-fail euler knight ESDD (2449).mp4
Discrete Optimization 1.9 CP 10 - valuevariable labeling domain splitting symmetry breaking in search (2845).mp4
Discrete Optimization 2.0 LS 1 - intuition n-queens (1357).mp4
Discrete Optimization 2.1 LS 2 - swap neighborhood car sequencing magic square (1514).mp4
Discrete Optimization 2.2 LS 3 - optimization warehouse location traveling salesman 2-opt k-opt (2309).mp4
Discrete Optimization 2.3 LS 4 - optimality vs feasibility graph coloring (2218).mp4
Discrete Optimization 2.4 LS 5 - complex neighborhoods sports scheduling (2242).mp4
Discrete Optimization 2.5 LS 6 - escaping local minima connectivity (1539).mp4
Discrete Optimization 2.6 LS 7 - formalization heuristics meta-heuristics introduction (2246).mp4
Discrete Optimization 2.7 LS 8 - iterated location search metropolis heuristic simulated annealing tabu search intuition (1854).mp4
Discrete Optimization 2.8 LS 9 - tabu search formalized aspiration car sequencing n-queens (2637).mp4
Discrete Optimization 3.0 LP 1 - intuition convexity geometric view (2414).mp4
Discrete Optimization 3.1 LP 2 - algebraic view naive algorithm (1342).mp4
Discrete Optimization 3.10 MIP 5 - cover cuts branch and cut seven bridges traveling salesman (3121).mp4
Discrete Optimization 3.2 LP 3 - the simplex algorithm (3222).mp4
Discrete Optimization 3.3 LP 4 - matrix notation the tableau (2052).mp4
Discrete Optimization 3.4 LP 5 - duality derivation (2200).mp4
Discrete Optimization 3.5 LP 6 - duality interpretation and uses (1700).mp4
Discrete Optimization 3.6 MIP 1 - intuition relaxation branch and bound knapsack warehouse location (2616).mp4
Discrete Optimization 3.7 MIP 2 - modeling big-M warehouse location graph coloring (2825).mp4
Discrete Optimization 3.8 MIP 3 - cutting planes Gomory cuts (2047).mp4
Discrete Optimization 3.9 MIP 4 - convex hull polyhedral cuts warehouse location node packing graph coloring (1920).mp4
Discrete Optimization 4.0 Large Neighborhood Search - asymmetric TSP with time windows (842).mp4
Discrete Optimization 4.1 Column Generation - branch and price cutting stock (2304).mp4
Discrete Optimization 4.2 Scheduling - jobshop disjunctive global constraint (3713).mp4
Discrete Optimization 5.0 Getting Started (1342).mp4
Discrete Optimization 5.1 Introduction & Screen Name (1347).mp4
Discrete Optimization 5.2 Knapsack & External Solver (1213).mp4
Discrete Optimization 5.3 Graph Coloring (623).mp4
Discrete Optimization 5.4 Traveling Salesman (1038).mp4
Discrete Optimization 5.5 Facility Location (937).mp4
Discrete Optimization 5.6 Vehicle Routing (1419).mp4
Discrete Optimization 5.7 Optimization Tools (600).mp4
Discrete Optimization 6.0 Set Cover (911).mp4
facility.zip
knapsack.zip
lecture-column-generation.pdf
lecture-cp-1.pdf
lecture-cp-10.pdf
lecture-cp-2.pdf
lecture-cp-3.pdf
lecture-cp-4.pdf
lecture-cp-5.pdf
lecture-cp-6.pdf
lecture-cp-7.pdf
lecture-cp-8.pdf
lecture-cp-9.pdf
lecture-explore.pdf
lecture-knapsack-BB.pdf
lecture-knapsack-DP.pdf
lecture-knapsack-greedy-1.pdf
lecture-knapsack-greedy-2.pdf
lecture-knapsack-model.pdf
lecture-knapsack-search.pdf
lecture-LNS.pdf
lecture-lp-1.pdf
lecture-lp-2.pdf
lecture-lp-3.pdf
lecture-lp-4.pdf
lecture-lp-5.pdf
lecture-lp-6.pdf
lecture-ls-1.pdf
lecture-ls-2.pdf
lecture-ls-3.pdf
lecture-ls-4.pdf
lecture-ls-5.pdf
lecture-ls-6.pdf
lecture-ls-7.pdf
lecture-ls-8.pdf
lecture-ls-9.pdf
lecture-mip-1.pdf
lecture-mip-2.pdf
lecture-mip-3.pdf
lecture-mip-4.pdf
lecture-mip-5.pdf
lecture-scheduling.pdf
Optimization Tools.html
screenname.zip
setcover.zip
tsp.zip
vrp.zip

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