Loading...
Please wait, while we are loading the content...
Similar Documents
Solving a New Bi-objective Model for a Cell Formation Problem Considering Labor Allocation by Multi-objective Particle Swarm Optimization
| Content Provider | Semantic Scholar |
|---|---|
| Author | Tavakkoli-Moghaddam, Reza Ghodratnama, Ali |
| Copyright Year | 2011 |
| Abstract | Mathematical programming and artificial intelligence (AI) methods are known as the most effective and applicable procedures to form manufacturing cells in designing a cellular manufacturing system (CMS). In this paper, a bi -objective programming model is presented to consider the cell formation problem that is solved by multi-objectiv particle swarm optimization (MOPSO) algorithm. The model contains two conflicting objectives, namely optimal labor allocation and maximization of cell utilization. In order to verify its effectiveness of the MOPSO algorithm, the results are compared with those obtained from a well-known evolutionary procedure, called NSGA-II. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.sid.ir/en/VEWSSID/J_pdf/856201103A04.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Algorithm Allocation Artificial intelligence CNS disorder Conflict (Psychology) Entropy maximization Mathematical optimization Multi-objective optimization Numerous Particle swarm optimization Programming model |
| Content Type | Text |
| Resource Type | Article |
