Results 241 to 250 of about 29,068 (302)

BGSE-RRT*: A Goal-Guided and Multi-Sector Sampling-Expansion Path Planning Algorithm for Complex Environments. [PDF]

Sensors (Basel)
Yue W, Li X, Liu Z, Jiang X, Pan L.
europepmc   +1 more source

Joint Optimization of Trajectory-Resource Allocation and Deep Task Partial Offloading for MEC-Enabled Multi-UAV. [PDF]

Sensors (Basel)
Liu C, Wang Y, Mei H, Du S, Guo B.
europepmc   +1 more source

Bi-objective location-allocation model of interventions in high drug consumption areas incorporating X topic modeling. [PDF]

Health Care Manag Sci
Palomino K, Berdugo C, Acuña J, Zayas-Castro JL.   +3 more
europepmc   +1 more source

Review of Mathematical Programming for Coastal Land Use Optimization [PDF]

Tipparat Pongthanapanich
core   +1 more source

Wireless sensor network design with reliable and long network lifetime. [PDF]

Sci Rep
Çelik E, Keskin ME.
europepmc   +1 more source

Early reduction in unplanned healthcare utilization following vagus nerve stimulation for pediatric epilepsy. [PDF]

Childs Nerv Syst
Murugesan RA, Tomlinson SB, Melamed SE, Galligan K, Kennedy BC.   +4 more
europepmc   +1 more source

Fuzzy Multi-objective Bi-level Goal Programming [PDF]

, 2015
In Chap. 8, we presented the definitions, solutions, and algorithms for the fuzzy multi-objective bi-level programming (FMO-BLP) problems. This chapter still addresses the fuzzy multi-objective bi-level problem but applies a goal programming approach. We call it fuzzy multi-objective bi-level goal programming (FMO-BLGP).
Guangquan Zhang, Jie Lu, Ya Gao
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Interactive fuzzy goal programming for multi-objective transportation problems

Omega, 2006
This paper presents an interactive fuzzy goal programming approach to determine the preferred compromise solution for the multi-objective transportation problem. The proposed approach considers the imprecise nature of the input data by implementing the minimum operator and also assumes that each objective function has a fuzzy goal. The approach focuses
Sang M Lee
exaly   +2 more sources

Solving goal programming problems using multi-objective genetic algorithms [PDF]

Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), 2003
Goal programming is a technique often used in engineering design activities primarily to find a compromised solution which will simultaneously satisfy a number of design goals. In solving goal programming problems, classical methods reduce the multiple goal-attainment problem into a single objective of minimizing a weighted sum of deviations from goals.
Deb, K.
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A preemptive goal programming for multi‐objective cooperative games: an application to multi‐objective linear production

International Transactions in Operational Research, 2022
AbstractThe aim of this study is to investigate the fair allocation of multi‐objective cooperative games (MOCGs) using a preemptive goal programming (PGP). First, this research establishes the PGP model, where the priority factors of PGP describe the importance degrees of different objectives in MOCGs, the positive and negative deviations of PGP ...
Jiangxia Nan, Lixiao Wei, Dengfeng Li, Maojun Zhang   +3 more
openaire   +2 more sources