| Author | Natanaree Sooksaksun |
| Call Number | AIT Diss. no.ISE-12-08 |
| Subject(s) | Warehouses
|
| Note | A dissertation submitted in partial fulfillment of the requirements for the
degree of Doctoral of Engineering in
Industrial and Manufacturing Engineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Dissertation ; no. ISE-12-08 |
| Abstract | Many factors influence the effectiveness of warehouse operations and one of the important
factors is the layout configuration. A good layout configuration of the warehouse may greatly
reduce the travel distance for order picking that is one of the indicators of an effective
warehouse operation. Classical method for warehouse design is commonly done in two steps.
The first step is to determine the layout and dimension of the aisles that may have impacts on
operations, space needs, storage assignment and material handling. The second step is the
storage location assignment that concerns assign items to storage locations in storage zones.
The design process is performed iteratively until a design with appropriate performance
criterion is found. This research proposes a one-step approach for warehouse design that can
determine the aisle layout and dimension while simultaneously assigning shelf spaces for
storing the items based on item classes.
The mathematical model for warehouses that operate under a class-based storage policy is
formulated to determine the optimal number of aisles, the length of aisle and the length of
each pick aisle to allocate to each product class that will minimize the travel distance. The
particle swarm optimization (PSO) algorithm is applied to find solutions for this highly nonlinear model. The numerical examples are given to demonstrate how to use the proposed
algorithm to simplify the warehouse design process. Overall, the PSO algorithm can provide
the optimal warehouse design in one step and the computational time is shorter than classical
method.
In addition, this research proposes a Pareto-based multi-objective optimization for warehouse
design. The two objectives considered are to minimize travel distance and to maximize usable
storage space. The mathematical model is presented for multi-objective warehouse design for
warehouses that operate under a class-based storage policy. Moreover, the multi-objective
particle swarm optimization (MOPSO) algorithm is proposed to solve the mathematical
model. A case study is given to illustrate that the proposed method can identify non-dominant
solutions as well as multiple alternative designs. |
| Year | 2012 |
| Corresponding Series Added Entry | Asian Institute of Technology. Dissertation ; no. ISE-12-08 |
| Type | Dissertation |
| School | School of Engineering and Technology (SET) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Systems Engineering (ISE) |
| Chairperson(s) | Voratas Kachitvichyanukul; |
| Examination Committee(s) | Gong, Dah-Chuan ;Huynh Trung Luong ;Khang, Do Ba; |
| Scholarship Donor(s) | National Science and Technology Development Agency; |
| Degree | Thesis (Ph. D.) - Asian Institute of Technology, 2012 |