Received December 15, 2021, accepted February 20, 2022, date of publication March 2, 2022, date of current version March 10, 2022. Digital Object Identifier 10.1109/ACCESS.2022.3156008 Problem Solving in Crowd Management Using Heuristic Approach ALI M. AL-SHAERY 1 , (Member, IEEE), MOHAMED O. KHOZIUM 2 , (Member, IEEE), NORAH S. FAROOQI 3 , (Member, IEEE), SHROUG S. ALSHEHRI 3 , (Member, IEEE), AND MOHAMMAD ADNAN M.B. AL-KAWA 4 1 Department of Civil Engineering, Vice Presidency for Innovation and Entrepreneurship (VPIE), Vice Presidency for Development and Community Service (VPDCS), Umm Al-Qura University, Makkah 21955, Saudi Arabia 2 Computer Science Research Center, Future University in Egypt, Cairo 11835, Egypt 3 College of Computer and Information Systems, Umm Al-Qura University, Makkah 21955, Saudi Arabia 4 Wentworth College of Computer with Artificial Intelligence, University of York, Heslington, York YO10 5DD, U.K. Corresponding author: Mohamed O. Khozium (osama@khozium.com) This work was supported in part by the Deputyship for Research & Innovation, Ministry of Education, Saudi Arabia, under Project RDO-P543. ABSTRACT There are many problems that procedural algorithms can solve efficiently. However, these algorithms are sometimes too slow to abide by the time available for performing the solution; other times, it is impossible to get a solution using procedural algorithms. A heuristic method is a practical approach that can reach an approximation of an efficient solution where the optimum is not guaranteed. Heuristic techniques are applied in many real-world problems, including crowd management; using heuristic-based models helped to comprehend crowd behavior better and increase simulation reliability. This paper reviews many heuristic-related articles to gather the aspects of the topic in one place and clear the fuzziness to make it easy to comprehend. The paper covers some of the previous works with similar approaches and presents state-of-the-art heuristic solutions for real-world problems. These techniques are discussed under three classifications: simple heuristics, meta-heuristics, and hyper-heuristics. Most importantly, the paper explores the heuristic role in crowd field problems concluding that heuristics are primarily applied in modeling when it comes to the Crowd field. It investigates different heuristics for crowd management. The main intent of this review is to establish a comprehensive understanding of heuristics-related operations in the crowd management field. Moreover, it aims to support other researchers’ future work and fill research gaps by highlighting the absence of crowd problems from heuristics literature and the limitations of each heuristics approach. INDEX TERMS Crowd malmanagement, hyper-heuristics, meta-heuristics, problem-solving, search algorithms. I. INTRODUCTION Problem-solving methods aim to provide solutions to specific problems. Typically, algorithms provide procedural steps that guarantee to reach a satisfactory solution in trade of some cost of time or other weights. The optimal solution is the one that sufficiently satisfies the solution with the lowest cost. Where algorithms provide clear steps to reach a solution, heuristics educates the decision-making process to solve the problem instead of offering the solution directly. This distinction inherits more detailed differences in solution optimization, The associate editor coordinating the review of this manuscript and approving it for publication was Shuihua Wang . linearity, and architecture. Though it cannot guarantee a solu- tion, heuristics can sometimes be the more practical and effective problem-solving approach to a satisfactory solution than procedural algorithms. It is like a recursion algorithm that checks its conditions over time and calls the suitable cor- responding functions. These conditions represent the online function that evaluates the parametric inputs and beliefs to decide the following actions over time. This makes heuristics the most suitable solution for artificial intelligence (AI) bots and multi-agent systems (MAS). First, starting with the difference between heuristics and algorithms in terms of optimization, the optimal solution is the one that sufficiently satisfies the problem conditions with 25422 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 10, 2022