We describe a general approach to optimization which we term \Squeaky Wheel " Op-timization (swo). In swo, a greedy algorithm is used to construct a solution which is then analyzed to nd the trouble spots, i.e., those elements, that, if improved, are likely to improve the objective function score. The results of the analysis are used to generate new priorities that determine the order in which the greedy algorithm constructs the next solution. This Construct/Analyze/Prioritize cycle continues until some limit is reached, or an acceptable solution is found. SWO can be viewed as operating on two search spaces: solutions and prioritizations. Successive solutions are only indirectly related, via the re-prioritization that results from anal...
Optimization is omnipresent in our world. Its numerous applications spread from industrial cases, su...
Traditionally, algorithms that generate schedules are either based on domain analyses or on task ana...
The deadline monotonic priority ordering is not optimal for schedulability when offsets are allowed ...
We describe a general approach to optimization which we term "Squeaky Wheel" Optimization ...
Oversubscribed scheduling problems require removing or partially satisfying tasks when enough resour...
In optimizing the signal timings of a network, determining the sequence in which the intersections w...
Along with increasing scientific progress, humans are constantly confronted with several new real-wo...
Authors are in alphabetical order. Please send all correspondence to Jingpeng Li Abstract. This pape...
AbstractDespite the long history of classical planning, there has been very little comparative analy...
AbstractOur ability to solve large, important combinatorial optimization problems has improved drama...
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimizat...
International audienceThe study of optimization algorithms started at the end of World War II and ha...
This volume provides resourceful thinking and insightful management solutions to the many challenges...
A greedy randomized adaptive search procedure (GRASP) is an iterative multistart metaheuristic for d...
Many business activities require planning and optimization, this is also true for engineering design...
Optimization is omnipresent in our world. Its numerous applications spread from industrial cases, su...
Traditionally, algorithms that generate schedules are either based on domain analyses or on task ana...
The deadline monotonic priority ordering is not optimal for schedulability when offsets are allowed ...
We describe a general approach to optimization which we term "Squeaky Wheel" Optimization ...
Oversubscribed scheduling problems require removing or partially satisfying tasks when enough resour...
In optimizing the signal timings of a network, determining the sequence in which the intersections w...
Along with increasing scientific progress, humans are constantly confronted with several new real-wo...
Authors are in alphabetical order. Please send all correspondence to Jingpeng Li Abstract. This pape...
AbstractDespite the long history of classical planning, there has been very little comparative analy...
AbstractOur ability to solve large, important combinatorial optimization problems has improved drama...
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimizat...
International audienceThe study of optimization algorithms started at the end of World War II and ha...
This volume provides resourceful thinking and insightful management solutions to the many challenges...
A greedy randomized adaptive search procedure (GRASP) is an iterative multistart metaheuristic for d...
Many business activities require planning and optimization, this is also true for engineering design...
Optimization is omnipresent in our world. Its numerous applications spread from industrial cases, su...
Traditionally, algorithms that generate schedules are either based on domain analyses or on task ana...
The deadline monotonic priority ordering is not optimal for schedulability when offsets are allowed ...