Designing a Multiobjective Human Resource Scheduling Model Using the Tabu Search Algorithm

Abstract

Nowadays, the major and substantial challenge and constraint of organizations, specifically in developing countries, are not the lack of raw materials, energy, or even technology but cases that are directly or indirectly associated with human resource management. The most significant problems that organizations face include dissatisfaction, lack of motivation, inefficiency of human resources, high amount of job turnovers, and low productivity. Today’s organizations and institutions should realize true perfection and health create the conditions for survival, order, excellence, and growth. In this research, considering the high importance of these issues, the problems of scheduling and allocation of manpower in a real place are solved. To this end, the metaheuristic Tabu search algorithm is used with the aim of minimizing the duration of activity and the presence of all manpower. For this purpose, to achieve the objectives of the research, three different scenarios related to the required manpower and the minimum-maximum presence of manpower according to whether they are on leave or not are used.

A Multi-Objective Optimization for Locating Maintenance Stations and Operator Dispatching of Corrective Maintenance

“…For instance, Feng et al implemented NSGA II to improve staffing in emergency departments [40], while Wei et al combined Ant Colony Optimization (ACO) with PSO to address human resource allocation challenges [41]. Additionally, well-established metaheuristic strategies like Tabu Search (TS) [42,43] and Simulated Annealing (SA) [44,45] have been effectively applied to the HRAP. These techniques have proven instrumental in optimizing the allocation process, ensuring efficiency and effectiveness in human resource management.…”

Modeling and Solving the Flow‐Shop Scheduling Problem with Sequence‐Dependent Setup Times by Firefly Algorithm (Case Study: Automotive Industry)

“…e purpose of scheduling is cases such as the minimum completion time for a set of orders, minimum delay, the maximum number of activities or orders completed in a given time, minimum intermediate inventory, and interaction in the use of resources. According to the intended objectives and with regard to the existing constraints such as production capacity, resource capacity, resource inventory, budget constraints, and time constraints, the problem of scheduling or allocating resources to activities over time is done [3,4].…”