ﻻ يوجد ملخص باللغة العربية
The travelling salesman problem (TSP) of space trajectory design is complicated by its complex structure design space. The graph based tree search and stochastic seeding combinatorial approaches are commonly employed to tackle the time-dependent TSP due to their combinatorial nature. In this paper, a new continuous optimization strategy for the mixed integer combinatorial problem is proposed. The space trajectory combinatorial problem is tackled using continuous gradient based method. A continuous mapping technique is developed to map the integer type ID of targets on the sequence to a set of continuous design variables. Expected flyby targets are introduced as references and used as priori to select the candidate target to fly by. Bayesian based analysis is employed to model accumulated posterior of the sequence and a new objective function with quadratic form constraints is constructed. The new introduced auxiliary design variables of expected targets together with the original design variables are set to be optimized. A gradient based optimizer is used to search optimal sequence parameter. Performances of the proposed algorithm are demonstrated through a multiple debris rendezvous problem and a static TSP benchmark.
We propose a dual dynamic integer programming (DDIP) framework for solving multi-scale mixed-integer model predictive control (MPC) problems. Such problems arise in applications that involve long horizons and/or fine temporal discretizations as well
Designing networks with specified collective properties is useful in a variety of application areas, enabling the study of how given properties affect the behavior of network models, the downscaling of empirical networks to workable sizes, and the an
We present a gradient-based algorithm for unconstrained minimization derived from iterated linear change of basis. The new method is equivalent to linear conjugate gradient in the case of a quadratic objective function. In the case of exact line sear
We study the problem of learning a linear model to set the reserve price in an auction, given contextual information, in order to maximize expected revenue from the seller side. First, we show that it is not possible to solve this problem in polynomi
The Double Travelling Salesman Problem with Multiple Stacks, DTSPMS, deals with the collect and delivery of n commodities in two distinct cities, where the pickup and the delivery tours are related by LIFO constraints. During the pickup tour, commodi