改良式突變型態之粒子群演算法於客服人員排班的應用

The Improved Mutation-based Particle Swarm Optimization for Call Center Staff Rostering

黎長明(Chang-Ming Lee)

指導教授 ： 邱昭彰

元智大學/資訊學院/資訊管理學系/碩士(2007年)

摘要

現實生活中所發生的問題，多半以離散的方式呈現，諸如學校內考場教室的安排、大眾運輸排班系統或是最常見的工廠內工作生產排程等等，皆屬於此類問題，本研究改良離散型粒子群演算法，並將之運用於建置全年無休服務人員的排班過程。首先將人員排班問題定義為一個限制滿足問題，依據問題模式，建立人員排班過程所須考量的限制條件，最後求得一個成功建置的最佳化排班表。

關鍵字

粒子群演算法 ； 離散型 ； 人員排班 ； 限制滿足 ； 最佳化

並列摘要

Most of problems that happen in the real world, appear in a discrete way mostly, such as timetable scheduling, vehicle routing problem or flow shop scheduling etc. This research improves discrete particle swarm optimization and applies it to staff scheduling and rostering problem. We firstly, set up staff scheduling and rostering problem with constraint satisfied problem, and then establish whole constraint condition that have to consider in rostering process according to problem mode, finally get one successful optimization form.

並列關鍵字

Particle Swarm Optimization ； Discrete Type ； Staff Rostering ； Constraint Satisfied ； Optimization

參考文獻

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