A decomposition-based approach for knee solution approximation in multi-objective optimization
Conference proceedings article
ผู้เขียน/บรรณาธิการ
กลุ่มสาขาการวิจัยเชิงกลยุทธ์
ไม่พบข้อมูลที่เกี่ยวข้อง
รายละเอียดสำหรับงานพิมพ์
รายชื่อผู้แต่ง: Sudeng S., Wattanapongsakorn N.
ผู้เผยแพร่: Hindawi
ปีที่เผยแพร่ (ค.ศ.): 2016
หน้าแรก: 3710
หน้าสุดท้าย: 3717
จำนวนหน้า: 8
ISBN: 9781509006229
นอก: 0146-9428
eISSN: 1745-4557
ภาษา: English-Great Britain (EN-GB)
บทคัดย่อ
Multi-objective Evolutionary Algorithms (MOEAs) always approximate a set of optimal solutions. This set is required to be well spread and uniformly covering wide area of the Pareto-optimal front. In practical context, the Decision Maker (DM) usually chooses solutions in the middle of objective space, where the surface bulges out the most. Such solutions are called 'knee solutions'. They are the most attractive solutions to the DM when he/she does not have an explicit preference. The aim of this paper is to develop a knee-based MOEA which is a method to find Pareto-optimal solutions with biasing parameter to focus on knee regions. The proposed approach is called k-MOEA/D-DE algorithm. It uses a distance-based concept to guide the solution process towards knee regions. The extent of the obtained solutions can be controlled by density controller parameter. The approach is verified by two and three-objective knee-based test problems. In addition, the approach has been applied to many-objective knee-based test problems including four, five and six-objective problems. The results in two and three-objective problems have shown that our approach is competitive to well-known knee-based MOEAs in convergence to optimality. Furthermore, knee solutions are visible and clearly seen in four, five and six-objective problems. ฉ 2016 IEEE.
คำสำคัญ
Knee-based MOEAs, Knee region, Knee solutions
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