| Summary: | 碩士 === 國立虎尾科技大學 === 工業管理系工業工程與管理碩士班 === 104 === This thesis explored a new Museum Routing Problem with capacity and fixed visiting time constrains. In this problem, there are two types of exhibition rooms for visitors. First type is the must-visit exhibition rooms, and it means that all visitor groups have to visit. Second type is the select-visit exhibition rooms, and it means that each visitor group may visit or not visit. Additionally, each room has fixed periods of open time and capacity restriction.
This considered Museum Routing Problem with capacity and fixed visiting time constrains amis to schedule the routes for all group such that objectives, including the makespan (maximal completion time of the groups) and the total waiting time of groups are minimized.This considered problem in this thesis is an extended problem of Open Shop Scheduling Problem (OSSP), therefore the new Museum Routing Problem with capacity and fixed visiting time constraints is also an NP-hard problem.
In this thesis, we apply three artificial intelligence algorithms, including Immune Algorithm (IA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to solve the New Museum Routing Problem with the objective of minimizing makespan of visitor groups and the total waiting times of visitor groups. Two examples of Taiwan Pavilion Theatre (Ilan) and Tainan Astronomical Education Area (Tainan) are solved and analyzed based upon different problem parameters.
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