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Content available remote The Extended Shift Minimization Personnel Task Scheduling Problem
EN
In workforce scheduling, shift generation is the process of determining the shift structure, along with the tasks to be carried out in particular shifts. Application areas of shift generation include hospitals, retail stores, contact centers, cleaning, home care, guarding, manufacturing and delivery of goods. We present an extension to the Shift Minimization Personnel Task Scheduling Problem that is a problem in which a set of tasks with fixed start and finish times have to be allocated to a heterogeneous workforce. The objective in the SMPTSP is to minimize the number of employees required to carry out the given set of tasks. In the ESMPTSP, another objective is to maximize the number of feasible (shift, employee) pairs. We provide a mathematical formulation of the extended problem. We present an efficient ruin and recreate heuristic along with computational results for existing SMPTSP data sets and to a new data set. The presented heuristic is suitable for application in large real-world scenarios. The new instances, along with our best solutions, have been made available online.
EN
Optimization of the production process is important for every factory or organization. The better organization can be done by optimization of the workforce planing. The main goal is decreasing the assignment cost of the workers with the help of which, the work will be done. The problem is NP-hard, therefore it can be solved with algorithms coming from artificial intelligence. The problem is to select employers and to assign them to the jobs to be performed. The constraints of this problem are very strong and for the algorithms is difficult to find feasible solutions. We apply Ant Colony Optimization Algorithm to solve the problem. We investigate the algorithm performance according evaporation parameter. The aim is to find the best parameter setting.
EN
This paper models the academic staff structure in a university as a system of stocks and flows in a three-dimensional space, R3. The stocks are the number of academic staff in a particular state at a given time and the flows are the staff moving between any two states over an interval of time. The paper places emphasis on the grade-specific completion rates of Graduate Assistants, who choose to study in the university in which they are employed for higher degrees. The study describes the evolution of structures in the university as a linear recurrence system. Some aspects of linear algebra are employed as a theoretical underpinning to gain insights into the transformation matrix of the recurrence system. A number of resulting propositions are presented along with their proofs. We provide two theorems to serve as a means of predicting a university manpower structure. Following that a numerical illustration of the theorems and propositions is provided with data which are representative of the kind of data in a Nigerian university system.
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