[HTML][HTML] Artificial intelligence in supply chain management: A systematic literature review
R Toorajipour, V Sohrabpour, A Nazarpour… - Journal of Business …, 2021 - Elsevier
This paper seeks to identify the contributions of artificial intelligence (AI) to supply chain
management (SCM) through a systematic review of the existing literature. To address the …
management (SCM) through a systematic review of the existing literature. To address the …
GRASP with path-relinking: Recent advances and applications
MGC Resendel, CC Ribeiro - Metaheuristics: progress as real problem …, 2005 - Springer
Path-relinking is a major enhancement to the basic greedy randomized adaptive search
procedure (GRASP), leading to significant improvements in solution time and quality. Path …
procedure (GRASP), leading to significant improvements in solution time and quality. Path …
Greedy randomized adaptive search procedures: Advances, hybridizations, and applications
MGC Resende, CC Ribeiro - Handbook of metaheuristics, 2010 - Springer
GRASP is a multi-start metaheuristic for combinatorial optimization problems, in which each
iteration consists basically of two phases: construction and local search. The construction …
iteration consists basically of two phases: construction and local search. The construction …
[BOG][B] Handbook of approximation algorithms and metaheuristics
TF Gonzalez - 2007 - taylorfrancis.com
Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …
[BOG][B] Scatter search
This chapter discusses the principles and foundations behind scatter search and its
application to the problem of training neural networks. Scatter search is an evolutionary …
application to the problem of training neural networks. Scatter search is an evolutionary …
[BOG][B] Optimization by GRASP
MGC Resende, CC Ribeiro - 2016 - Springer
Greedy randomized adaptive search procedures, or GRASP, were introduced by T. Feo and
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …
Machine Learning and Genetic Algorithms: A case study on image reconstruction
In this research, we investigate the application of machine learning techniques to
optimization problems and propose a novel integration between metaheuristics and …
optimization problems and propose a novel integration between metaheuristics and …
An annotated bibliography of GRASP–Part I: Algorithms
P Festa, MGC Resende - International Transactions in …, 2009 - Wiley Online Library
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for
combinatorial optimization. It is a multi‐start or iterative process, in which each GRASP …
combinatorial optimization. It is a multi‐start or iterative process, in which each GRASP …
TTT plots: a perl program to create time-to-target plots
RM Aiex, MGC Resende, CC Ribeiro - Optimization Letters, 2007 - Springer
This paper describes a perl language program to create time-to-target solution value plots
for measured CPU times that are assumed to fit a shifted exponential distribution. This is …
for measured CPU times that are assumed to fit a shifted exponential distribution. This is …
Parallel GRASP with path-relinking for job shop scheduling
RM Aiex, S Binato, MGC Resende - Parallel Computing, 2003 - Elsevier
In the job shop scheduling problem (JSP), a finite set of jobs is processed on a finite set of
machines under certain constraints, such that the maximum completion time of the jobs is …
machines under certain constraints, such that the maximum completion time of the jobs is …