A Hybrid Heuristic Method to Solve an Assignment Problem of Human Resource

Tkatek, Said; Abdoun, Otman; Abouchabaka, Jâafar; Rafalia, Najat

doi:10.15866/irecos.v10i9.7246

Cited by 7 publications

(10 citation statements)

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“…Such a problem consists of "moving employees from one site to another based on one or more criteria". Similar issues were discussed in Tkatek et al (2015), where the authors combined the flowgraph approach (to model and construct the space solution) and the genetic approach (to investigate the optimal plan in the space solution). Recently, Jain et al (2020) developed a priority-based unbalanced time minimization assignment problem for projects executed in two stages (some primary jobs are supposed to be completed within the first stage and the remaining jobs may be commenced after primary job completion).…”

Section: Selected Extensions Of the Deteministic Assignment Problemmentioning

confidence: 94%

The Assignment Problem in Human Resource Project Management under Uncertainty

Gaspars-Wieloch

2021

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The assignment problem (AP) is a discrete and combinatorial problem where agents are assigned to perform tasks for efficiency maximization or cost (time) minimization. AP is a part of human resource project management (HRPM). The AP optimization model, with deterministic parameters describing agent–task performance, can be easily solved, but it is characteristic of standard, well-known projects realized in a quiet environment. When considering new (innovation or innovative) projects or projects performed in very turbulent times, the parameter estimation becomes more complex (in extreme cases, even the use of the probability calculus is not recommended). Therefore, we suggest an algorithm combining binary programming with scenario planning and applying the optimism coefficient, which describes the manager’s nature (attitude towards risk). The procedure is designed for one-shot decisions (i.e., for situations where the selected alternative is performed only once) and pure strategies (the execution of a weighted combination of several decision variants is not possible).

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Section: Selected Extensions Of the Deteministic Assignment Problemmentioning

confidence: 94%

The Assignment Problem in Human Resource Project Management under Uncertainty

Gaspars-Wieloch

2021

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“…According to the literature, resource assignment consists of matching human resources to tasks, machines, projects, teams, sites, schedules, etc. [11], its considered of one of NP-hard problem [3], [4]. The resource assignment issue is present in any organization that depends on resources to generate tangible throughput or provide services [11].…”

Section: About the Np-hard Problems: Resource Assignment And Vr Problemsmentioning

confidence: 99%

“…In the real world, the resource ("human", "machine", etc.) management problem arises in various contexts, and the literature is of interest for RAP, which is an NP-hard problem [3], [4] and proposes various practical applications [1]. In general, the classical assignment problem consists in finding a one-to-one correspondence between a set of tasks and a set of agents, whose objective is to minimize the total cost of the agents' work.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence for Improving the Optimization of NP-Hard Problems: A Review

2020

IJATCSE

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Artificial intelligence (AI) techniques play an important role in the development and optimization of complex problems in various fields. This study presents a systematic analysis of previously publications on the use of AI techniques to optimize the NP-hard problems in the area of human resource assignment to multi-constrained activities in order to increase the productivity and performance of a company, and in the area of vehicle routing in order to cost minimization. These two problems belonged to the NP-hard family. Among these AI techniques used for a better optimization of this type of problems, we discuss the genetic algorithms (GA), hybrid GA, parallel GA, GA with Big Data and improved AI techniques with special features are also discussed and presented through the different contributions of the researchers.

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“…Another important concept of AG is the notion of population. Unlike traditional research methods, genetic algorithms rely on a population of candidate solutions [22]. The size of the population, which is usually a user-specified parameter, is one of the important factors affecting the scalability and performance of genetic algorithms.…”

Section: Geneticmentioning

confidence: 99%

Artificial Intelligence Approach for Multi-Objective Design Optimization of Composite Structures: Parallel Genetic Immigration

Majdoubi¹

2020

IJATCSE

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An isotropic mechanical structure cannot withstand shocks, accidents, and mechanical loading. In this perspective, composite structures have been introduced to improve the performance of mechanical structures. We are interested in the study of laminates with the aim to find an optimal structure resistant to vibrations and buckling. To remedy the problem of vibrations and buckling, we use artificial intelligence methods to optimize the design of composite structures. As it is a typical method of artificial intelligence adapted to this studied problem, we use genetic algorithms based on a new genetic operator. In the present article, an optimization procedure based on the new genetic operator called genetic immigration operator is developed to determine the maximum buckling load and fundamental frequency of the laminated plate with plies oriented at -45•/45• ,0•, and 90•. The aim of this paper is the use of two different methods for their effectiveness. These optimization works consist of first maximizing the buckling load factor with UGA (Uniform Genetic Algorithm) and a new evolutionary search strategies called Immigration Genetic: SIG (Standard Immigration Genetic Algorithm) and AIG (Improved Genetic Immigration Algorithm) and second of solving a multi-objective problem with minimizing the cost and weight of the hybrid laminate made of the fibers of two composite materials. The resolution of this problem by the proposed genetic immigration approach is reinforced by the optimization of the CPU computation time which is due to the exploitation of the parallel architecture based on the multi-processor parallel computation.

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A Hybrid Heuristic Method to Solve an Assignment Problem of Human Resource

Cited by 7 publications

References 0 publications

The Assignment Problem in Human Resource Project Management under Uncertainty

The Assignment Problem in Human Resource Project Management under Uncertainty

Artificial Intelligence for Improving the Optimization of NP-Hard Problems: A Review

Artificial Intelligence Approach for Multi-Objective Design Optimization of Composite Structures: Parallel Genetic Immigration

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