Allocation of short-term jobs to unemployed citizens amid the global economic downturn using genetic algorithm

Authors:
Rong-Chang Chen;Menz-Ru Huang;Ruey-Gwo Chung;Chih-Jung Hsu
Affiliations:
Department of Logistics Engineering and Management, National Taichung Institute of Technology, 129 Sanmin Road, Sec. 3, Taichung, Taiwan, ROC;Employment Services Center, Taichung-Changhua-Nantou Region, Bureau of Employment and Vocational Training, Council of Labor Affairs, Executive Yuan, Taiwan, ROC and Department of Industrial Educat ...;Department of International Business Management, Hsiuping Institute of Technology, Taiwan, ROC;Department of Logistics Engineering and Management, National Taichung Institute of Technology, 129 Sanmin Road, Sec. 3, Taichung, Taiwan, ROC
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

In an effort to hold back the domestic effects caused by the global economic downturn, many countries present a variety of economic stimulus programs to create and save employment opportunities. Among them, offering short-term jobs to unemployed citizens is one of the most popular plans. Allocation of short-term jobs to jobless citizens has become an important issue since an improper allocation could bring about the dissatisfaction and complaints from citizens. In this paper, we propose a novel mechanism which is based on genetic algorithm (GA) to allocate the short-term jobs. The allocation is decided by a system which considers the unemployed citizens' preferences. Employing GA to solve the allocation problem shows that the complicated problem can be well solved and the job allocation can be properly made. Moreover, this easy-to-use system can facilitate the allocation in different scenarios.