A branch and bound algorithm for solving separable convex integer programming problems

DOI10.1016/0305-0548(94)90072-8zbMath0815.90116OpenAlexW1989268498MaRDI QIDQ1342308

A. Victor Cabot, Won J. Lee, Munirpallam A. Venkataramanan

Publication date: 27 June 1995

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

Full work available at URL: https://doi.org/10.1016/0305-0548(94)90072-8

zbMATH Keywords

partitioningnonlinear integer programmingbranch-and-boundfathomingreoptimizing schemesseparable convex objective function

Mathematics Subject Classification ID

Convex programming (90C25) Integer programming (90C10)

Related Items

A discrete dynamic convexized method for nonlinear integer programming ⋮ A critical review of discrete filled function methods in solving nonlinear discrete optimization problems ⋮ Discrete dynamic convexized method for nonlinearly constrained nonlinear integer programming

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Nonlinear integer programming algorithms: A survey
• Non-linear integer programming
• A General Algorithm for the Optimal Distribution of Effort
• Establishing Consistent and Realistic Reorder Intervals in Production-Distribution Systems
• Branch and Bound Experiments in Convex Nonlinear Integer Programming
• A branch and bound algorithm for solving a class of nonlinear integer programming problems
• Determining Optimal Reorder Intervals in Capacitated Production-Distribution Systems
• The use of dynamic programming methodology for the solution of a class of nonlinear programming problems
• A Survey of Methods for Pure Nonlinear Integer Programming
• An Algorithm for Nonlinear Knapsack Problems
• Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming
• A hybrid approach to discrete mathematical programming
• Technical Note—Converting the 0-1 Polynomial Programming Problem to a 0-1 Linear Program
• The Optimum Distribution of Effort
• Integer Programming Formulation of Constrained Reliability Problems
• Further Reduction of Zero-One Polynomial Programming Problems to Zero-One linear Programming Problems