Multi-Objective Combinatorial Optimization - Anytime Behavior Model (moco_abm)

This software provides both a binary and a library (see note) for an anytime behavior model of multi-objective combinatorial optimization algorithms that, at each iteration, collect an efficient solution that maximizes the hypervolume contribution. It is assumed that all objective functions are to be maximized.

Note: the current software is intended to be used as a binary for now. The library API is not yet properly defined and no documentation is provided for now.

Binary

Install the latest binary using cargo with:

cargo install moco_abm

or compile from source with:

cargo build --release

Usage

USAGE:
    moco_abm [OPTIONS] -n <num>

FLAGS:
    -h, --help       Prints help information
    -V, --version    Prints version information

OPTIONS:
    -f <file>        file with piecewise approximation definition (stdin is used if not set)
    -n <num>         number of points to retrieve

The input file should contain at least one segment in the following format

u1 u2 v1 v2

where $(u_1, u_2)$ and $(v_1, v_2)$ denote the coordinates of the linear segment endpoints. Multiple segments, and coordinates within the segments, can be separated by any whitespace.

Note: Points in the segments must be provided such that v1 > u1 and v2 < u2. Moreover, when multiple segments are provided, e.g.:

u1 u2 v1 v2
p1 p2 q1 q2

it is required that p1 >= v1 and that p2 <= v2.

Example of a valid segments list file:

0.0 1.0 0.7 0.7
0.7 0.7 1.0 0.0

Output

The output is returned to stdout and consists of a .tsv with the following fields

field	description
index	index of the current point (starts at 1)
hv_contribution	hypervolume contribution of this point
hv_current	hypervolume of all returned points up to now
hv_relative	current_hv relative to maximal hypervolume
point	comma separated coordinates of the point

Library

Add this to your Cargo.toml:

[dependencies]
moco_abm = "0.1"

and this to your crate root:

extern crate moco_abm;