A C++ Design for Self-Registering Objective Functions in Optimization Frameworks

This article presents a robust, modern C++ design pattern for managing objective functions within optimization frameworks. This design introduces a self-registration mechanism that automatically registers new objective functions at compile-time. The design promotes modularity, minimizes boilerplate code, and simplifies the integration of new objective functions. The implementation uses the Curiously Recurring Template Pattern (CRTP) and requires new objective types to provide a default constructor. The approach aligns with contemporary guidance on object-oriented design and C++ resource management.

Authors

Institutions

Publication Details

Journal
The Pinnacle A Journal by Scholar-Practitioners
Published
2026-03-09
DOI
https://doi.org/10.61643/c19500
Primary Topic
Advanced Software Engineering Methodologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A C++ Design for Self-Registering Objective Functions in Optimization Frameworks

Mikal Keenan
The Pinnacle A Journal by Scholar-Practitioners
Advanced Software Engineering Methodologies
article

A C++ Design for Self-Registering Objective Functions in Optimization Frameworks

Mikal Keenan
article en

Abstract

This article presents a robust, modern C++ design pattern for managing objective functions within optimization frameworks. This design introduces a self-registration mechanism that automatically registers new objective functions at compile-time. The design promotes modularity, minimizes boilerplate code, and simplifies the integration of new objective functions. The implementation uses the Curiously Recurring Template Pattern (CRTP) and requires new objective types to provide a default constructor. The approach aligns with contemporary guidance on object-oriented design and C++ resource management.

The Pinnacle A Journal by Scholar-PractitionersVol. 4(1)
Colorado Technical University
Decent work and economic growth
Openalex Percentile: Top 33%
Advanced Software Engineering Methodologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.