Aims, Themes & Scope: As per tradition, looking at the previous editions of the MIC conferences, thisconference focuses on the progress of the area of Metaheuristics and their applications and provides anopportunity to the international research community to discuss recent research results, to develop newideas and collaborations, and to meet old friends and make new ones in relaxed atmosphere. MIC 2026strives to propose a high-quality program that will be completed by a number of invited talks, tutorials,workshops and special sessions.

Solicited contributions can cover a variety of topics including but not limited to:

• Metaheuristic techniques such as tabu search, simulated annealing, iterated local search, variableneighborhood search, memory-based optimization, dynamic local search, evolutionary algorithms,memetic algorithms, ant colony optimization, particle swarm optimization, scatter search, pathrelinking, etc.
• Techniques that enhance the usability and increase the potential of metaheuristic algorithms suchas reactive search mechanisms for self-tuning, offline metaheuristic algorithm configurationtechniques, algorithm portfolios, parallelization of metaheuristic algorithms, etc.
• Empirical and theoretical research in metaheuristics including large-scale experimental analyses,algorithm comparisons, new experimental methodologies, engineering methodologies formetaheuristic algorithms, search space analysis, theoretical insights into properties ofmetaheuristic algorithms, etc.
• High-impact applications of metaheuristics in fields such as bioinformatics, electrical andmechanical engineering, telecommunications, sustainability, business, scheduling and timetabling.Particularly welcome are innovative applications of metaheuristic algorithms that have a potentialof pushing research frontiers.
• Contributions on the combination of metaheuristic techniques with those from other areas, suchas integer programming, constraint programming, machine learning, etc.
• Contributions on the use of metaheuristic techniques in machine learning and deep learning forfinetuning and neural architecture search, etc.
• Challenging applications areas such as continuous, mixed discrete-continuous, multi-objective,stochastic, or dynamic problems.

Submission details: MIC 2026 accepts submissions in three different formats:

1. Regular paper: novel and original research contributions of a maximum of 15 pages (LNCS format)
2. Short paper: extended abstract of novel research works of 6 pages (LNCS format)
3. Oral presentation: high-quality manuscripts that have recently, within the last year, beensubmitted or accepted for journal publication.

All submitted papers will undergo a review process. All papers must be prepared using Lecture Notes inComputer Science (LNCS) template, and must be submitted in PDF using the easychair system.