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Since both the multi-start and the eSS2 approaches use random numbers, the convergence curves will be different for each run.

We propose several mixed integer programming formulations and two heuristic approaches based on multi start simulated annealing and ant colony system to solve these problems.

The algorithms are gradient multi start neighbourhood exhaustive search procedures.

The paper includes a stop criterion for the algorithm based on the stability of the statistics of the multi start results.

Modular Finite-Difference Ground-Water Flow ModelMS, multi start random search (optimization method in LGO).

The heuristic approach, combining a multi-start mechanism and a rounding strategy, is specially developed to solve large-scale problems in reasonable time.

For larger instances the algorithm outperforms both a multi-start heuristic and a discrete-based optimal approach while performing well against a recent powerful VNS approach.

Empirical results, based on several existing data set (TSP-Lib) with various values of p, show that the proposed VNS implementations outperform both a multi-start heuristic and the discrete-based optimal approach that use the same local search.

They use a global docking method based on multi-start energy optimization, and predict low-energy regions as binding sites.

A new hybrid methodology by combining fuzzy random simulation (FRS) technique and multi-start simulated annealing (MSA) algorithm is designed to solve the proposed model.

We overcome these limitations here by embedding a fast and accurate hypercube approximation algorithm adapted for partial backup dispatch policies in single- and multi-start greedy heuristics.

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