International Journal of Algorithms Design and Analysis Review

International Journal of Algorithms Design and Analysis Review is a peer-reviewed hybrid open-access journal launched in 2015 that focuses on original research and practice-driven application with relevance to algorithms designs and analysis. All articles included are peer-reviewed by scholars with colossal experience in the same fields. Dynamic programming, amortized analysis, and linear programming are major focus areas.

• Algorithm design paradigms: divide and conquer, dynamic programming and memoisation, greedy strategies and matroid structure, backtracking and branch and bound, recursive formulation and problem decomposition, and comparative analysis of paradigm choice.
• Complexity and computability: asymptotic analysis and lower bounds, NP-completeness and hardness reductions, complexity classes and their relationships, fine-grained complexity, average-case and smoothed analysis, and impossibility results.
• Data structures: search trees and balanced structures, hashing schemes and collision handling, priority queues and heaps, disjoint set union and path compression, succinct and compressed structures, persistent and concurrent data structures, and amortised analysis with potential functions.
• Graph algorithms: shortest path, flow, and matching algorithms, connectivity and spanning structures, graph partitioning and clustering, dynamic and incremental graph algorithms, graph exploration and traversal, and algorithms on structured graph classes including interval and planar graphs.
• String and sequence algorithms: pattern matching and multi-pattern search, suffix arrays, trees, and construction algorithms, approximate matching and edit distance, compressed text indexing, permutation pattern matching, and sequence algorithms for computational biology.
• Computational geometry: convex hulls and triangulations, geometric search and range queries, quadtrees and spatial subdivision, arrangement and intersection computation, algebraic curve and surface algorithms, and geometric approximation.
• Randomised and approximation algorithms: randomised construction and analysis techniques, derandomisation, approximation ratio analysis and hardness of approximation, primal–dual and LP rounding methods, set cover and packing approximations, and probabilistic guarantees.
• Parameterized and exact algorithms: fixed-parameter tractability, kernelisation and preprocessing, treewidth and structural parameters, exact exponential algorithms, branch-and-search techniques, and parameterized hardness.
• Online, streaming, and sublinear algorithms: competitive analysis of online algorithms, streaming and sketching under space constraints, sublinear-time property testing, dynamic algorithms under updates, and lower bounds in restricted models.
• Combinatorial optimisation and mathematical programming: integer and linear programming formulations, simplex and interior point methods, cutting plane and column generation, multi-objective and stochastic programming, fuzzy and possibilistic programming, and network flow and scheduling optimisation.
• Metaheuristics and search-based optimisation: evolutionary and swarm-based methods, local search and iterated variants, tabu search and simulated annealing, hybrid and memetic designs, parameter control and adaptation, and rigorous benchmarking against established baselines.
• Parallel and distributed algorithms: work and depth analysis, parallel algorithm design for shared and distributed memory, distributed graph and consensus algorithms, communication complexity, and external memory and cache-oblivious algorithms.
• Algorithm engineering and experimental analysis: implementation techniques and constant-factor optimisation, experimental methodology and benchmarking practice, algorithm libraries and reusable implementations, reproducibility of algorithmic experiments, and gap analysis between theoretical and practical performance.
• Applied algorithms: algorithms for scheduling and logistics, routing and vehicle routing problems, resource allocation and assignment, algorithms in bioinformatics and network science, and algorithmic methods in machine learning pipelines.