Topic
Look-ahead
About: Look-ahead is a research topic. Over the lifetime, 205 publications have been published within this topic receiving 5466 citations.
Papers published on a yearly basis
Papers
TL;DR: A fast and simple priority dispatch method is described and shown to produce acceptable schedules most of the time and a look ahead algorithm is introduced that outperforms the dispatcher by about 12% with only a small increase in run time.
Abstract: This paper describes three approaches to assigning tasks to earth observing satellites EOS. A fast and simple priority dispatch method is described and shown to produce acceptable schedules most of the time. A look ahead algorithm is then introduced that outperforms the dispatcher by about 12% with only a small increase in run time. These algorithms set the stage for the introduction of a genetic algorithm that uses job permutations as the population. The genetic approach presented here is novel in that it uses two additional binary variables, one to allow the dispatcher to occasionally skip a job in the queue and another to allow the dispatcher to occasionally allocate the worst position to the job. These variables are included in the recombination step in a natural way. The resulting schedules improve on the look ahead by as much as 15% at times and 3% on average. We define and use the "window-constrained packing" problem to model the bare bones of the EOS scheduling problem.
312 citations
TL;DR: In this article, a fuel-optimal control algorithm for a heavy diesel truck that utilizes information about the road topography ahead of the vehicle when the route is known is presented.
258 citations
TL;DR: A notion of inconsistency between instantiations and variables is introduced, and is shown to be a useful tool for characterizing such well-known concepts as backtrack, backjump, and domain annihilation.
199 citations
TL;DR: Sierra is a program that learns procedures incrementally from examples, where an example is a sequence of actions, where a lesson is a set of examples that is guaranteed to introduce only one subprocedure.
194 citations
TL;DR: The solution method, which is based upon Atkinson's greedy look-ahead heuristic, enhances traditional vehicle routing approaches, and provides surprisingly good performance results with respect to a set of standard test problems from the literature.
Abstract: In this paper we consider the problem of physically distributing finished goods from a central facility to geographically dispersed customers, which pose daily demands for items produced in the facility and act as sales points for consumers. The management of the facility is responsible for satisfying all demand, and promises deliveries to the customers within fixed time intervals that represent the earliest and latest times during the day that a delivery can take place. We formulate a comprehensive mathematical model to capture all aspects of the problem, and incorporate in the model all critical practical concerns such as vehicle capacity, delivery time intervals and all relevant costs. The model, which is a case of the vehicle routing problem with time windows, is solved using a new heuristic technique. Our solution method, which is based upon Atkinson's greedy look-ahead heuristic, enhances traditional vehicle routing approaches, and provides surprisingly good performance results with respect to a set of standard test problems from the literature. The approach is used to determine the vehicle fleet size and the daily route of each vehicle in an industrial example from the food industry. This actual problem, with approximately two thousand customers, is presented and solved by our heuristic, using an interface to a Geographical Information System to determine inter-customer and depot–customer distances. The results indicate that the method is well suited for determining the required number of vehicles and the delivery schedules on a daily basis, in real life applications.
144 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 13 |
| 2024 | 19 |
| 2023 | 9 |
| 2022 | 13 |
| 2021 | 7 |
| 2020 | 13 |