An improved simulated annealing simulation optimization method for discrete parameter stochastic systems

DOI10.1016/S0305-0548(03)00240-5zbMath1073.90026MaRDI QIDQ1885946

Catherine M. Harmonosky, Scott L. Rosen

Publication date: 12 November 2004

Published in: Computers \& Operations Research (Search for Journal in Brave)

Mathematics Subject Classification ID

Stochastic programming (90C15) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (12)

A robust parameter design for multi-response problems ⋮ A framework for evaluating remote diagnostics investment decisions for semiconductor equipment suppliers ⋮ An extended mind evolutionary computation model for optimizations ⋮ An auxiliary function method for global minimization in integer programming ⋮ Parameter-free filled function method for nonlinear integer program ⋮ Multi-objective simulation-based evolutionary algorithm for an aircraft spare parts allocation problem ⋮ Unnamed Item ⋮ Black box scatter search for general classes of binary optimization problems ⋮ A critical review of discrete filled function methods in solving nonlinear discrete optimization problems ⋮ A multiobjective metaheuristic for a mean-risk multistage capacity investment problem ⋮ A multiobjective metaheuristic for a mean-risk static stochastic knapsack problem ⋮ A survey on metaheuristics for stochastic combinatorial optimization

Cites Work

• Unnamed Item
• Optimization by Simulated Annealing
• Simulated annealing for discrete optimization with estimation
• A Simulated Annealing Algorithm with Constant Temperature for Discrete Stochastic Optimization
• Optimization by Simulated Annealing: An Experimental Evaluation; Part I, Graph Partitioning
• Cooling Schedules for Optimal Annealing
• The time complexity of maximum matching by simulated annealing
• Simulation-based optimization using simulated annealing with ranking and selection

This page was built for publication: An improved simulated annealing simulation optimization method for discrete parameter stochastic systems