Network programming
Computers and Operations Research - Special issue: implementing multiobjective optimization methods: behavioral and computational issues
Efficient solutions for the bicriteria network flow problem
Computers and Operations Research - Special issue: implementing multiobjective optimization methods: behavioral and computational issues
Interactive multiple objective programming procedures via adaptive random search and feed-forward artificial neural networks
An approach for the network flow problem with multiple objectives
Computers and Operations Research
Pivot Strategies for Primal-Simplex Network Codes
Journal of the ACM (JACM)
Interactive multiple objective programming using Tchebycheff programs and artificial neural networks
Computers and Operations Research - Special issue on artificial intelligence and decision support with multiple criteria
Model-Based Decision Support Methodology with Environmental Applications
Model-Based Decision Support Methodology with Environmental Applications
Network Models in Optimization and Their Applications in Practice
Network Models in Optimization and Their Applications in Practice
Algorithms for Network Programming
Algorithms for Network Programming
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Three warm-start routines are developed to find initial basic feasible solutions for augmented weighted Tchebycheff network programs, subproblems derived from multiple-objective network-programming problems. In an interactive solution procedure, a series of augmented weighted Tchebycheff network programs need to be solved sequentially to find representative nondominated solutions. To speed up the solution process using the network structure of the problem, these warm-start routines start the solution process of one augmented weighted Tchebycheff network program from the optimal solution of the previous one. All three warm-start routines use the same strategy but different ways of reducing the number of basic flow variables, or equivalently increasing the number of basic nonflow variables to construct a basic solution. These warm-start routines can be used by any interactive procedures to facilitate the solution process of multiple-objective network-programming problems. A detailed example is presented. A computational experiment is conducted to compare the performance of these warm-start routines. A cold-start routine and NETSIDE, specialized software for solving network problems with side constraints, are also used as references in the experiment. These warm-start routines can save substantial computation time.