A lot of heuristic approaches have been explored in the last two decades in order to tackle large size optimization problems. These areas include parallel meta-heuristics, hybrid meta-heuristic, and cooperative search algorithms. Different taxonomies have been proposed in the literature for parallel and hybrid meta-heuristics. In these taxonomies, one can realize that cooperative search algorit...

This paper presents an overview of recent advances for the Nurse Rostering Problem (NRP) based on methodological papers published between 2012 to 2021. It provides a comprehensive review latest solution methodologies, particularly computational intelligence (CI) approaches, utilized in benchmark and real-world nurse rostering. The methodologies are systematically categorised (Heuristics, Meta-h...

The chapter presents a general view of parallel meta-heuristics for optimization. It recalls the main concepts and strategies in designing parallel meta-heuristics and identifies trends and promising research directions. The focus is on cooperation-based strategies, which display remarkable performances, in particular strategies based on asynchronous exchanges and the creation of new informatio...

In this paper, teaching–learning-based optimization (TLBO) is proposed to solve flexible job shop scheduling problem (FJSP) based on the integrated approach with an objective to minimize makespan. An FJSP is an extension of basic job-shop scheduling problem. There are two sub problems in FJSP. They are routing problem and sequencing problem. If both the sub problems are solved simultaneously, t...

this paper deals with the product mix problem using the concept of theory of constraints (toc). theory of constraints is one of the most efficient approaches which have been applied to solve the product mix problem heuristically. although there are numerous heuristic and meta-heuristics to solve this problem, finding the optimal solution in a reasonable time is still a challenging issue. in thi...

the robust coloring problem (rcp) is a generalization of the well-known graph coloring problem where we seek for a solution that remains valid when extra edges are added. the rcp is used in scheduling of events with possible last-minute changes and study frequency assignments of the electromagnetic spectrum. this problem has been proved as np-hard and in instances larger than 30 vertices, meta-...

vendor selection decisions are complicated by the fact that various conflicting multi-objective factors must be considered in the decision making process. the problem of vendor selection becomes still more compli-cated with the inclusion of incremental discount pricing schedule. such hard combinatorial problems when solved using meta heuristics produce near optimal solutions. this paper propose...

this research, for the first time presents the flexible flow shop model of scheduling method for considering runway assignment and operations planning together. one of the advantages of the developed model is considering the procedures of air routes in terminal airspace and separation between consecutive aircraft which is very similar to the real world condition. there are different objective f...

Due to NP-Hard nature of the Job Shop Scheduling Problems (JSP), exact methods fail to provide the optimal solutions in quite reasonable computational time. Due to this nature of the problem, so many heuristics and meta-heuristics have been proposed in the past to get optimal or near-optimal solutions for easy to tough JSP instances in lesser computational time compared to exact methods. One of...

We present a state-of-the-art survey of parallel meta-heuristic developments and results, discuss general design and implementation principles that apply to most meta-heuristic classes, instantiate these principles for the three meta-heuristic classes currently most extensively used—genetic methods, simulated annealing, and tabu search, and identify a number of trends and promising research dir...