The max-bisection problem is an NP-hard combinatorial optimization problem. In this paper, a new Lagrangian net algorithm is proposed to solve max-bisection problems. First, we relax the bisection constraints to the objective function by introducing the penalty function method. Second, a bisection s
A modified VNS metaheuristic for max-bisection problems
β Scribed by Ai-fan Ling; Cheng-xian Xu; Le Tang
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 163 KB
- Volume
- 220
- Category
- Article
- ISSN
- 0377-0427
No coin nor oath required. For personal study only.
β¦ Synopsis
Variable neighborhood search (VNS) metaheuristic as presented in Festa et al. [Randomized heuristics for the MAX-CUT problem, Optim. Methods Software 17 (2002) 1033-1058] can obtain high quality solution for max-cut problems. Therefore, it is worthwhile that VNS metaheuristic is extended to solve max-bisection problems. Unfortunately, comparing with max-cut problems, max-bisection problems have more complicated feasible region via the linear constraint e T x = 0. It is hard to directly apply the typical VNS metaheuristic to deal with max-bisection problems. In this paper, we skillfully combine the constraint e T x = 0 with the objective function, obtain a new optimization problem which is equivalent to the max-bisection problem, and then adopt a distinct greedy local search technique to the resulted problem. A modified VNS metaheuristic based on the greedy local search technique is applied to solve max-bisection problems. Numerical results indicate that the proposed method is efficient and can obtain high equality solution for max-bisection problems.
π SIMILAR VOLUMES