An Iterated Local Search Algorithm for Agile Earth Observation Satellite Scheduling Problem

Abstract

The scheduling problem of an Agile Earth Observation Satellite is to schedule a subset of observation tasks among a set of candidates during their visible time windows in order to gain a maximum collected profit. Each pair of two consecutive tasks should satisfy the "time-dependent" transition time constraint, which contributes to the difficulty of solving the problem. To tackle this problem, a concept of "minimal transition time" which only depends on the observation start time of the previous task, is introduced. On this basis, we develop a fast and effective Iterated Local Search algorithm. A local search insert procedure is specifically designed to deal with time-dependent transition times and time windows. The experimental results on a variety of instances show that our algorithm performs very well in terms of solution quality and computation time and outperforms the state of the art.

Agile Earth observation satellite scheduling over 20 years: formulations, methods and future directions

“…There operators are iteratively selected to efficiently assign the tasks to different AEOSs. Peng et al [83] introduce a concept of minimal transition time, which only depends on the observation start time of the previous task. Based on this idea, a fast and effective iterated local search (ILS) algorithm is then developed.…”

Time/sequence-dependent scheduling: the design and evaluation of a general purpose tabu-based adaptive large neighbourhood search algorithm

“…A dispatching rule considering weighted shortest processing time, setup times and nearest neighbour was proposed. Liu et al (2017) and Peng et al (2018) studied the agile satellite observation scheduling problem with time-dependent setup times. Liu et al (2017) proposed a mixed integer program-ming (MIP) method and an ALNS algorithm, where they also integrated ALNS with an insertion algorithm considering time-dependency by introducing forward/backward time slacks.…”

“…Liu et al (2017) proposed a mixed integer program-ming (MIP) method and an ALNS algorithm, where they also integrated ALNS with an insertion algorithm considering time-dependency by introducing forward/backward time slacks. Peng et al (2018) proposed an iterated local search (ILS) algorithm. They further calculated the minimal transition time, the neighbours and earliest/latest start time of each job to accelerate the insertion.…”

“…Verbeeck et al (2017) proposed the time-dependent OP with time windows (TDOPTW). In their ACO metaheuristic, they used the max shift to fast determine the feasibility of an insertion, which is similar to the ideas of Peng et al (2018).…”

“…We compare the proposed ALNS/TPF with our previous algorithm called ALNS/TPI (He et al 2018), the standard ALNS (Liu et al 2017), the ILS algorithm (Peng et al 2018), and an MIP model from He et al (2018). We have obtained the source codes for the standard ALNS and the ILS algorithm from the corresponding authors.…”