A multiplier adjustment method for the generalized assignment problem
Management Science
The generalized assignment problem: valid inequalities and facets
Mathematical Programming: Series A and B
A genetic algorithm for the generalised assignment problem
Computers and Operations Research
Computers and Operations Research
A class of greedy algorithms for the generalized assignment problem
Discrete Applied Mathematics
A dynamic tabu search for large-scale generalised assignment problems
Computers and Operations Research
Journal of Global Optimization
Genetic Optimization Using A Penalty Function
Proceedings of the 5th International Conference on Genetic Algorithms
Solving the Generalized Assignment Problem: An Optimizing and Heuristic Approach
INFORMS Journal on Computing
An Ejection Chain Approach for the Generalized Assignment Problem
INFORMS Journal on Computing
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series)
A discrete differential evolution algorithm for the permutation flowshop scheduling problem
Computers and Industrial Engineering
Computers and Operations Research
Advances in Differential Evolution
Advances in Differential Evolution
Applying adaptive algorithms to epistatic domains
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
A family of inequalities for the generalized assignment polytope
Operations Research Letters
Differential evolution for a constrained combinatorial optimisation problem
International Journal of Metaheuristics
Grey incidence optimization model based on hybrid differential evolution algorithm
AICI'12 Proceedings of the 4th international conference on Artificial Intelligence and Computational Intelligence
An improved differential evolution algorithm based on adaptive parameter
Journal of Control Science and Engineering - Special issue on Advances in Methods for Networked and Cyber-Physical System
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In this paper, differential evolution (DE) algorithms are presented to solve the generalized assignment problem (GAP), which is basically concerned with finding the minimum cost assignment of jobs to agents such that each job is assigned to exactly one agent, subject to capacity constraint of agents. The first algorithm is unique in terms of solving a discrete optimization problem on a continuous domain. The second one is a discrete/combinatorial variant of the traditional differential evolution algorithm working on a discrete domain. The objective is to present a continuous optimization algorithm dealing with discrete spaces hence to solve a discrete optimization problem. Both algorithms are hybridized with a "blind" variable neighborhood search (VNS) algorithm to further enhance the solution quality, especially to end up with feasible solutions. They are tested on a benchmark suite from OR Library. Computational results are promising for a continuous algorithm such that without employing any problem-specific heuristics and speed-up methods, the DE variant hybridized with a "blind" VNS local search was able to generate competitive results to its discrete counterpart.