Mustafa Misir

Journal article Journal of cheminformatics · March 2026 Selecting an effective docking algorithm is highly context-dependent, and no single method performs reliably across structural, chemical, and protocol regimes. MolAS is a lightweight algorithm-selection model that predicts per-algorithm performance from pr ... Full text Cite

Deep reinforcement learning for solving the stochastic e-waste collection problem

Journal article European Journal of Operational Research · November 16, 2025 With the growing influence of the internet and information technology, Electrical and Electronic Equipment (EEE) has become a gateway to technological innovations. However, discarded devices, also called e-waste, pose a significant threat to the environmen ... Full text Cite

Deep learning for predicting 16S rRNA gene copy number.

Journal article Scientific reports · June 2024 Culture-independent 16S rRNA gene metabarcoding is a commonly used method for microbiome profiling. To achieve more quantitative cell fraction estimates, it is important to account for the 16S rRNA gene copy number (hereafter 16S GCN) of different communit ... Full text Cite

Algorithm selection for protein-ligand docking: strategies and analysis on ACE.

Journal article Scientific reports · May 2023 The present study investigates the use of algorithm selection for automatically choosing an algorithm for any given protein-ligand docking task. In drug discovery and design process, conceptualizing protein-ligand binding is a major problem. Targeting this ... Full text Cite

A Bi-Objective Constrained Robust Gate Assignment Problem: Formulation, Instances and Algorithm.

Journal article IEEE transactions on cybernetics · September 2021 The gate assignment problem (GAP) aims at assigning gates to aircraft considering operational efficiency of airport and satisfaction of passengers. Unlike the existing works, we model the GAP as a bi-objective constrained optimization problem. The total wa ... Full text Cite

A case study of algorithm selection for the traveling thief problem

Journal article Journal of Heuristics · June 1, 2018 Many real-world problems are composed of several interacting components. In order to facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in 2013 as the combination of two well-understood combinatorial optimization proble ... Full text Cite

ALORS: An algorithm recommender system

Journal article Artificial Intelligence · March 1, 2017 Algorithm selection (AS), selecting the algorithm best suited for a particular problem instance, is acknowledged to be a key issue to make the best out of algorithm portfolios. This paper presents a collaborative filtering approach to AS. Collaborative fil ... Full text Cite

An analysis of generalised heuristics for vehicle routing and personnel rostering problems

Journal article Journal of the Operational Research Society · May 20, 2015 The present study investigates the performance of heuristics while solving problems with routing and rostering characteristics. The target problems include scheduling and routing home care, security and maintenance personnel. In analysing the behaviour of ... Full text Cite

An investigation on the generality level of selection hyper-heuristics under different empirical conditions

Journal article Applied Soft Computing Journal · January 1, 2013 The present study concentrates on the generality of selection hyper-heuristics across various problem domains with a focus on different heuristic sets in addition to distinct experimental limits. While most hyper-heuristic research employs the term general ... Full text Cite

A new hyper-heuristic as a general problem solver: An implementation in HyFlex

Journal article Journal of Scheduling · January 1, 2013 This study provides a new hyper-heuristic design using a learning-based heuristic selection mechanism together with an adaptive move acceptance criterion The selection process was supported by an online heuristic subset selection strategy In addition, a pa ... Full text Cite

One hyper-heuristic approach to two timetabling problems in health care

Journal article Journal of Heuristics · June 1, 2012 We present one general high-level hyper-heuristic approach for addressing two timetabling problems in the health care domain: the patient admission scheduling problem and the nurse rostering problem. The complex combinatorial problem of patient admission s ... Full text Cite

Monte Carlo hyper-heuristics for examination timetabling

Journal article Annals of Operations Research · January 1, 2012 Automating the neighbourhood selection process in an iterative approach that uses multiple heuristics is not a trivial task. Hyper-heuristics are search methodologies that not only aim to provide a general framework for solving problem instances at differe ... Full text Cite

A Reinforcement Learning - Great-Deluge Hyper-Heuristic for Examination Timetabling

Journal article International Journal of Applied Metaheuristic Computing · January 1, 2010 Hyper-heuristics can be identified as methodologies that search the space generated by a finite set of low level heuristics for solving search problems. An iterative hyper-heuristic framework can be thought of as requiring a single candidate solution an ... Full text Cite