A Fast and Exact Algorithm for the Exemplar Breakpoint Distance

2016 ◽  
Vol 23 (5) ◽  
pp. 337-346 ◽  
Author(s):  
Mingfu Shao ◽  
Bernard M.E. Moret
Keyword(s):  
Exact Algorithm ◽  
Breakpoint Distance

Exact algorithm for generating optimal homogenous strip T-shape layouts

2013 ◽  
Vol 32 (9) ◽  
pp. 2634-2637
Author(s):  
Jun JI ◽  
Yi-ping LU ◽  
Jian-zhong ZHA ◽  
Yao-dong CUI
Keyword(s):  
Exact Algorithm

scholarly journals An exact algorithm for subgraph homeomorphism

2009 ◽  
Vol 7 (4) ◽  
pp. 464-468 ◽  
Author(s):  
Andrzej Lingas ◽  
Martin Wahlen
Keyword(s):  
Exact Algorithm

scholarly journals A Comparison of Genetic Representations and Initialisation Methods for the Multi-objective Shortest Path Problem on Multigraphs

2021 ◽  
Vol 2 (3) ◽  
Author(s):  
Lilla Beke ◽  
Michal Weiszer ◽  
Jun Chen
Keyword(s):  
Shortest Path ◽  
Time Budget ◽  
Exact Algorithm ◽  
Simple Graph ◽  
Shortest Path Problem ◽  
Future Application ◽  
Multi Objective ◽  
Trade Offs ◽  
Conflicting Objectives ◽  
Problem Instances

AbstractThis paper compares different solution approaches for the multi-objective shortest path problem (MSPP) on multigraphs. Multigraphs as a modelling tool are able to capture different available trade-offs between objectives for a given section of a route. For this reason, they are increasingly popular in modelling transportation problems with multiple conflicting objectives (e.g., travel time and fuel consumption), such as time-dependent vehicle routing, multi-modal transportation planning, energy-efficient driving, and airport operations. The multigraph MSPP is more complex than the NP-hard simple graph MSPP. Therefore, approximate solution methods are often needed to find a good approximation of the true Pareto front in a given time budget. Evolutionary algorithms have been successfully applied for the simple graph MSPP. However, there has been limited investigation of their applications to the multigraph MSPP. Here, we extend the most popular genetic representations to the multigraph case and compare the achieved solution qualities. Two heuristic initialisation methods are also considered to improve the convergence properties of the algorithms. The comparison is based on a diverse set of problem instances, including both bi-objective and triple objective problems. We found that the metaheuristic approach with heuristic initialisation provides good solutions in shorter running times compared to an exact algorithm. The representations were all found to be competitive. The results are encouraging for future application to the time-constrained multigraph MSPP.

An improved heuristic and an exact algorithm for the 2D strip and bin packing problem

2010 ◽  
Vol 10 (1/2/3) ◽  
pp. 217 ◽  
Author(s):  
Abdelghani Bekrar ◽  
Imed Kacem ◽  
Chengbin Chu ◽  
Cherif Sadfi
Keyword(s):  
Bin Packing ◽  
Exact Algorithm ◽  
Packing Problem ◽  
Bin Packing Problem

An exact algorithm for scheduling identical coupled tasks

2004 ◽  
Vol 59 (2) ◽  
pp. 193-203 ◽  
Author(s):  
Dino Ahr ◽  
J�zsef B�k�si ◽  
G�bor Galambos ◽  
Marcus Oswald ◽  
Gerhard Reinelt
Keyword(s):  
Exact Algorithm ◽  
Coupled Tasks

A new exact algorithm for the vehicle routing problem based onq-paths andk-shortest paths relaxations

1995 ◽  
Vol 61 (1) ◽  
pp. 21-43 ◽  
Author(s):  
Eleni Hadjiconstantinou ◽  
Nicos Christofides ◽  
Aristide Mingozzi
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Shortest Paths ◽  
Exact Algorithm ◽  
Routing Problem
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