Systematic numerical investigation of the role of hierarchy in heterogeneous bio-inspired materials

It is well known that hierarchical structure is an important feature in biological materials to optimise various properties, including mechanical ones. It is however still unclear how these hierarchical architectures can improve material characteristics, for example strength. Also, the transposition of these structures from natural to artificial bioinspired materials remains to be perfected. In this paper, we introduce a numerical method to evaluate the strength of fibre-based heterogeneous biological materials and systematically investigate the role of hierarchy. Results show that hierarchy indeed plays an important role and that it is possible to “tune” the strength of bio-inspired materials in a wide range of values, in some cases improving the strength of non-hierarchical structures considerably

ITERATED INSIDE OUT: a new exact algorithm for the transportation problem

We propose a novel exact algorithm for the transportation problem, one of the paradigmatic network optimization problems. The algorithm, denoted Iterated Inside Out, requires in input a basic feasible solution and is composed by two main phases that are iteratively repeated until an optimal basic feasible solution is reached. In the first "inside" phase, the algorithm progressively improves upon a given basic solution by increasing the value of several non-basic variables with negative reduced cost. This phase typically outputs a non-basic feasible solution interior to the constraints set polytope. The second "out" phase moves in the opposite direction by iteratively setting to zero several variables until a new improved basic feasible solution is reached. Extensive computational tests show that the proposed approach strongly outperforms all versions of network and linear programming algorithms available in the commercial solvers Cplex and Gurobi and other exact algorithms available in the literature

Merging Nodes in Search Trees: an Exact Exponential Algorithm for the Single Machine Total Tardiness Scheduling Problem

This paper proposes an exact exponential algorithm for the problem of minimizing the total tardiness of jobs on a single machine. It exploits the structure of a basic branch-and-reduce framework based on the well known Lawler\u27s decomposition property. The proposed algorithm, called branch-and-merge, is an improvement of the branch-and-reduce technique with the embedding of a node merging operation. Its time complexity is O*(2.247^n) keeping the space complexity polynomial. The branch-and-merge technique is likely to be generalized to other sequencing problems with similar decomposition properties