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2008

167views Artificial Intelligence» more AIPS 2008»

A New Hybrid Genetic Algorithm for the Job Shop Scheduling Problem with Setup Times

13 years 6 months ago

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In this paper we face the Job Shop Scheduling Problem with Sequence Dependent Setup Times by means of a genetic algorithm hybridized with local search. We have built on a previous...

Miguel A. González, Camino R. Vela, Ramiro ...

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Id	Views	Title	Status

1	167	A New Hybrid Genetic Algorithm for the Job Shop Scheduling Problem with Setup Times	claim
2	155	Stochastic Planning with First Order Decision Diagrams	claim
3	155	HiPPo: Hierarchical POMDPs for Planning Information Processing and Sensing Actions on a Robot	claim
4	153	Learning Relational Decision Trees for Guiding Heuristic Planning	claim
5	151	Criticality Metrics for Distributed Plan and Schedule Management	claim
6	148	Bounded-Parameter Partially Observable Markov Decision Processes	claim
7	148	Exact Dynamic Programming for Decentralized POMDPs with Lossless Policy Compression	claim
8	146	Generative Planning for Hybrid Systems Based on Flow Tubes	claim
9	144	Fast Dynamic Scheduling of Disjunctive Temporal Constraint Networks through Incremental Compilation	claim
10	142	Useless Actions Are Useful	claim
11	137	A Temporal Logic-Based Planning and Execution Monitoring System	claim
12	133	Fast and Memory-Efficient Multi-Agent Pathfinding	claim
13	131	Additive-Disjunctive Heuristics for Optimal Planning	claim
14	126	The Complexity of Optimal Planning and a More Efficient Method for Finding Solutions	claim
15	126	Using Constraint Networks on Timelines to Model and Solve Planning and Scheduling Problems	claim
16	124	Generating Robust Schedules Subject to Resource and Duration Uncertainties	claim
17	123	Effective Information Value Calculation for Interruption Management in Multi-Agent Scheduling	claim
18	120	Efficient ADD Operations for Point-Based Algorithms	claim
19	117	Planning 3D Task Demonstrations of a Teleoperated Space Robot Arm	claim
20	116	From One to Many: Planning for Loosely Coupled Multi-Agent Systems	claim
21	116	Structural Patterns Heuristics via Fork Decomposition	claim
22	115	Filtering for a Continuous Multi-Resources cumulative Constraint with Resource Consumption and Production	claim
23	115	Causal Graphs and Structurally Restricted Planning	claim
24	115	CircuitTSAT: A Solver for Large Instances of the Disjunctive Temporal Problem	claim
25	112	Unifying the Causal Graph and Additive Heuristics	claim
26	111	Multiagent Planning Under Uncertainty with Stochastic Communication Delays	claim
27	109	A Compact and Efficient SAT Encoding for Planning	claim
28	108	P3C: A New Algorithm for the Simple Temporal Problem	claim
29	107	A Probabilistic Planner for the Combat Power Management Problem	claim
30	106	Stochastic Enforced Hill-Climbing	claim
31	105	An Online Learning Method for Improving Over-Subscription Planning	claim
32	101	Planning for Modular Printers: Beyond Productivity	claim
33	99	In Search of the Tractability Boundary of Planning Problems	claim
34	96	A New Local Search for the Job Shop Problem with Uncertain Durations	claim
35	95	Learning Heuristic Functions through Approximate Linear Programming	claim
36	93	Optimal Additive Composition of Abstraction-based Admissible Heuristics	claim
37	91	A New Probabilistic Plan Recognition Algorithm Based on String Rewriting	claim
38	91	The Compression Power of Symbolic Pattern Databases	claim
39	90	Using Classical Planners to Solve Nondeterministic Planning Problems	claim
40	90	Multi-Objective Evolutionary Algorithms for Scheduling the James Webb Space Telescope	claim
41	89	Faster than Weighted A*: An Optimistic Approach to Bounded Suboptimal Search	claim
42	88	Angelic Hierarchical Planning: Optimal and Online Algorithms	claim
43	87	A New Approach to Tractable Planning	claim
44	86	Linear Relaxation Techniques for Task Management in Uncertain Settings	claim
45	83	Fast Planning for Dynamic Preferences	claim
46	83	Scheduling Meetings at Trade Events with Complex Preferences	claim
47	78	Realizing Multiple Autonomous Agents through Scheduling of Shared Devices	claim
48	75	What Makes Planners Predictable?	claim

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