Two general-purpose metaheuristic algorithms for solving multiobjective stochastic combinatorial optimization problems are introduced: SP-ACO (based on the ...
The aim of this paper is to present two general-purpose metaheuristic solu- tion algorithms SP-ACO and SPSA, determining approximations to the Pareto- optimal ...
Two Metaheuristics for Multiobjective Stochastic Combinatorial Optimization. https://doi.org/10.1007/11571155_12 · Full text. Journal: Stochastic Algorithms ...
The two main parameters of the algorithm are ITER (the number of iterations to apply the algorithm) and CS (the cooling schedule), since they have the most.
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In this paper, we formulate a multi echelon PDN to deliver products to customers with uncertain demand in the least time with uncertain delivery lead time.
Missing: Combinatorial | Show results with:Combinatorial
This book discusses recent research in metaheuristics for combinatorial optimization and includes recent research results from MESS 2018.
Oct 22, 2024 · Metaheuristics such as Ant Colony Optimization, Evolutionary Compu- tation, Simulated Annealing, Tabu Search and Stochastic Partitioning Methods are introduced.
Missing: Multiobjective | Show results with:Multiobjective
Special attention is given to multi-objective SCO as well as to combinations of metaheuristics with mathematical programming. Keywords: metaheuristics • ...
This paper presents a state-of-the-art review on multi-objective metaheuristics for multi-objective discrete optimization problems (MODOPs).
The two phases method: An efficient procedure to solve bi-objective combinatorial optimization problems. Article. Jan 1995. E.L. Ulungu · Jacques ...