8 research outputs found
An efficient memetic, permutation-based evolutionary algorithm for real-world train timetabling
Train timetabling is a difficult and very tightly constrained combinatorial
problem that deals with the construction of train schedules. We focus on the
particular problem of local reconstruction of the schedule following a small
perturbation, seeking minimisation of the total accumulated delay by adapting
times of departure and arrival for each train and allocation of resources
(tracks, routing nodes, etc.). We describe a permutation-based evolutionary
algorithm that relies on a semi-greedy heuristic to gradually reconstruct the
schedule by inserting trains one after the other following the permutation.
This algorithm can be hybridised with ILOG commercial MIP programming tool
CPLEX in a coarse-grained manner: the evolutionary part is used to quickly
obtain a good but suboptimal solution and this intermediate solution is refined
using CPLEX. Experimental results are presented on a large real-world case
involving more than one million variables and 2 million constraints. Results
are surprisingly good as the evolutionary algorithm, alone or hybridised,
produces excellent solutions much faster than CPLEX alone
On the Benefits of Inoculation, an Example in Train Scheduling
The local reconstruction of a railway schedule following a small perturbation
of the traffic, seeking minimization of the total accumulated delay, is a very
difficult and tightly constrained combinatorial problem. Notoriously enough,
the railway company's public image degrades proportionally to the amount of
daily delays, and the same goes for its profit! This paper describes an
inoculation procedure which greatly enhances an evolutionary algorithm for
train re-scheduling. The procedure consists in building the initial population
around a pre-computed solution based on problem-related information available
beforehand. The optimization is performed by adapting times of departure and
arrival, as well as allocation of tracks, for each train at each station. This
is achieved by a permutation-based evolutionary algorithm that relies on a
semi-greedy heuristic scheduler to gradually reconstruct the schedule by
inserting trains one after another. Experimental results are presented on
various instances of a large real-world case involving around 500 trains and
more than 1 million constraints. In terms of competition with commercial math
ematical programming tool ILOG CPLEX, it appears that within a large class of
instances, excluding trivial instances as well as too difficult ones, and with
very few exceptions, a clever initialization turns an encouraging failure into
a clear-cut success auguring of substantial financial savings
Multi-dwelling refurbishment optimization: problem decomposition, solution and trade-off analysis
A methodology has been developed for the multiobjective
optimization of the refurbishment of
domestic building stock on a regional scale. The
approach is based on the decomposition of the
problem into two stages: first to find the energy-cost
trade-off for individual houses, and then to apply it
tomultiple houses.
The approach has been applied to 759 dwellings
using buildings data from a survey of the UK
housing stock. The energy use of each building and
their refurbished variants were simulated using
EnergyPlus using automatically-generated input files.
The variation in the contributing refurbishment
options from least to highest cost along the Pareto
front shows loft and cavity wall insulation to be
optimal intially, and solid wall insulation and double
glazing appearing later
Multi-dwelling Refurbishment Optimization: Problem Decomposition, Solution, and Trade-off Analysis
A methodology has been developed for the multiobjective optimization of the refurbishment of domestic building stock on a regional scale. The approach is based on the decomposition of the problem into two stages: first to find the energy-cost trade-off for individual houses, and then to apply it tomultiple houses. The approach has been applied to 759 dwellings using buildings data from a survey of the UK housing stock. The energy use of each building and their refurbished variants were simulated using EnergyPlus using automatically-generated input files. The variation in the contributing refurbishment options from least to highest cost along the Pareto front shows loft and cavity wall insulation to be optimal intially, and solid wall insulation and double glazing appearing later
A review of timetabling and resource allocation models for light-rail transportation systems
This paper surveys the relevant operations research literature on timetabling and resource allocationproblems with a special attention paid to the transportation systems. The purpose of this review is to define the critical objectives, determine the key components and identify the key issues for developing a comprehensive mathematical model for timetabling of light rail transit vehicles in sequence with the assignment of drivers as an available resource. In doing so, the implications of the emerging timetabling research is discussed, components of the mathematical models proposed are reviewed, and the extend they reflect real business practices are analyzed. Finally, fundamental issues and primary elements of a simple model in association with general timetabling and resource allocation problems are presented