Journal ArticleDOI
Lagrangian relaxation guided problem space search heuristics for generalized assignment problems
Vishv Jeet,Erhan Kutanoglu +1 more
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TLDR
A heuristic based on Lagrangian relaxation and problem space search to solve the generalized assignment problem (GAP) is developed and test that works well on most of the benchmark instances known and provides high-quality solutions quickly.About:
This article is published in European Journal of Operational Research.The article was published on 2007-11-01. It has received 45 citations till now. The article focuses on the topics: Lagrangian relaxation & Generalized assignment problem.read more
Citations
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Hybrid metaheuristics in combinatorial optimization: A survey
TL;DR: A survey of some of the most important lines of hybridization of metaheuristics with other techniques for optimization, which includes, for example, the combination of exact algorithms and meta heuristics.
Journal ArticleDOI
A Survey of the Generalized Assignment Problem and Its Applications
TL;DR: This survey focuses on the real-life applications of the Generalized Assignment Problem (GAP) in scheduling, timetabling, telecommunication, facility location, transportation, production planning, etc.
Journal ArticleDOI
A scalable parallel genetic algorithm for the Generalized Assignment Problem
Yan Liu,Shaowen Wang +1 more
TL;DR: A scalable coarse-grained PGA-PGAP is developed to enable efficient deme interactions and significantly improve the overlapping of computation and communication for NP-hard optimization problem: Generalized Assignment Problem (GAP).
Journal ArticleDOI
Collaborative service-component integration in cloud manufacturing
TL;DR: Numerical experiments are conducted to demonstrate the benefits of the developed framework for efficient and optimal configuration of collaborative networked organisations, addressing the Industry 4.0 demand for agility through modularisation and service-orientation.
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Decomposition based hybrid metaheuristics
TL;DR: A general review of design patterns for hybrid metaheuristics that combine principles of classical metaheuristic techniques with advanced methods from fields like mathematical programming, dynamic programming, and constraint programming.
References
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Journal ArticleDOI
The Lagrangian Relaxation Method for Solving Integer Programming Problems
TL;DR: This paper is a review of Lagrangian relaxation based on what has been learned in the last decade and has led to dramatically improved algorithms for a number of important problems in the areas of routing, location, scheduling, assignment and set covering.
Journal ArticleDOI
A generalized assignment heuristic for vehicle routing
TL;DR: This paper presents a heuristic for this problem in which an assignment of customers to vehicles is obtained by solving a generalized assignment problem with an objective function that approximates delivery cost and shows that it has outperformed the best existing heuristics on a sample of standard test problems.
Journal ArticleDOI
A guide to vehicle routing heuristics
TL;DR: Several of the most important classical and modern heuristics for the vehicle routing problem are summarized and compared using four criteria: accuracy, speed, simplicity and flexibility.
Journal ArticleDOI
New search spaces for sequencing problems with application to job shop scheduling
TL;DR: In this paper, search heuristics are developed for generic sequencing problems with emphasis on job shop scheduling, and two methods are proposed, both of which are based on novel definitions of solution spaces and of neighborhoods in these spaces.
Journal ArticleDOI
A genetic algorithm for the generalised assignment problem
P. C. Chu,John E. Beasley +1 more
TL;DR: Computational results show that the genetic algorithm heuristic is able to find optimal and near optimal solutions that are on average less than 0.01 % from optimality.
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A branch and bound algorithm for the generalized assignment problem
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