A modified hybrid whale optimization algorithm for the scheduling problem in multimedia data objects

Mohamed Abdel-Basset, Doaa El-Shahat, Ibrahim El-henawy

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


The scheduling of the Multimedia Data Objects (MDO) is a difficult and extraordinary issue that faces us in the World Wide Web (WWW) to minimize the response time for clients to finish rapidly their tasks. MDO scheduling problem can be modeled as a Two-Machine Flow Shop Scheduling Problem (T-MFSSP) that minimizes the makespan. Notwithstanding another objective is to decrease the average lateness time of the clients' jobs. This paper proposes a Modified Hybrid Whale Algorithm (MHWA) to solve a standout among the most imperative applications of flow shop scheduling in the field of MDO. MHWA is hybridized with a local search strategy for solving the scheduling problem of MDO. To cope up with the combinatorial nature of the MDO scheduling, LRV maps the continuous search space into a sequence of jobs. To get better solutions, some operations are applied to the solutions such as swap mutation and reversed block insertion operations. Nawaz-Enscore-Ham (NEH) is added to MHWA to upgrade the performance of the algorithm. The solution of Johnson heuristic is added to the initial population of MHWA. It can be inferred that MHWA gives competitive outcomes appeared differently in relation to Johnson and Earliest Due Date (EDD) algorithms. MHWA can obtain the optimal makespan and can minimize the average lateness of the jobs.

Original languageEnglish
Article numbere5137
Pages (from-to)1-11
Number of pages11
JournalConcurrency and Computation: Practice and Experience
Issue number4
Publication statusPublished - 25 Feb 2020
Externally publishedYes


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