TY - RPRT
TI - User’s Guide of ERC Slitting Package
AU - Lamendola, C.N.
AU - Fang, S.
A3 - AT&T Engineering Research Center
DA - 1982/3//
PY - 1982/3//
M1 - CC3083-02
M3 - Technical Report
PB - AT&T Engineering Research Center
SN - CC3083-02
ER -
TY - RPRT
TI - Fiber Selection Problem in the Lightguide Cable Ribboning Process
AU - Murr, M.R.
AU - Fang, S.
A3 - AT&T Engineering Research Center
DA - 1982/9//
PY - 1982/9//
M1 - CC7778
M3 - Technical Report
PB - AT&T Engineering Research Center
SN - CC7778
ER -
TY - CONF
TI - Optimal Scheduling of the Coil Slitting Problem
AU - Lamendola, C.N.
AU - Fang, S.
C2 - 1982///
C3 - IIE Proceedings of Annual Conference
DA - 1982///
SP - 476 – 480
ER -
TY - JOUR
TI - A Note on Q-Matrices
AU - Fang, S.
T2 - Bulletin of the Institute of Mathematics Academia Sinica
DA - 1982///
PY - 1982///
VL - 10
IS - 3
SP - 239 – 243
ER -
TY - JOUR
TI - Fixed Point Models for the Equilibrium Problems on Transportation Networks
AU - Fang, Shu-Cherng
T2 - Tamkang Journal of Mathematics
DA - 1982///
PY - 1982///
VL - 13
IS - 2
SP - 181-191
ER -
TY - JOUR
TI - Solving Linear Constrained Separable Convex Programs via Generalized Geometric Programming Duality
AU - Fang, Shu-Cherng
T2 - Chinese Journal of Mathematics
DA - 1982/12//
PY - 1982/12//
VL - 10
IS - 2
SP - 103-112
ER -
TY - JOUR
TI - Traffic Equilibria on Multiclass-User Transportation Networks Analyzed via Variational Inequalities
AU - Fang, Shu-Cherng
T2 - Tamkang Journal of Mathematics
DA - 1982///
PY - 1982///
VL - 13
IS - 1
SP - 1-9
ER -
TY - JOUR
TI - Generalized variational inequalities
AU - Fang, S. C.
AU - Peterson, E. L.
T2 - Journal of Optimization Theory and Applications
DA - 1982/11//
PY - 1982/11//
DO - 10.1007/bf00935344
VL - 38
IS - 3
SP - 363-383
J2 - J Optim Theory Appl
LA - en
OP -
SN - 0022-3239 1573-2878
UR - http://dx.doi.org/10.1007/bf00935344
DB - Crossref
ER -
TY - JOUR
TI - A model for locating repair stations in a sequential manufacturing process
AU - Fang, S.C.
T2 - Applied Mathematical Modelling
AB - With the increasing complexity of final products, the sequential manufacturing process becomes very important. It breaks a production line into a linear sequence of simpler individual operations. By performing each individual operation step by step, we can manufacture a final product with the desired high complexity. For a given sequential manufacturing process with n operations S 1 , S 2 , …, S n , we assume there is an operational cost c i and a success probability p i associated with each operation S i . After each operation, it is possible to locate a repair station R i . In the repair station, the first task is to test defective products at a unit test cost t i, j (which may depend on the location of the previous repair station R j ). Then the defectives are fixed at a unit repair cost r i, j (which may also depend on the location of the previous station R j ). The settings of repair stations affect both the total manufacturing cost and final yield. Our major economic incentive is to minimize the unit manufacturing cost per fault — free final product by locating a number of repair stations at proper places. Obviously there are 2 n possible combinations in total. A dynamic programming model with an algorithm of 0( n 3 ) complexity is used to solve this problem.
DA - 1982/10//
PY - 1982/10//
DO - 10.1016/s0307-904x(82)80099-1
VL - 6
IS - 5
SP - 363-368
J2 - Applied Mathematical Modelling
LA - en
OP -
SN - 0307-904X
UR - http://dx.doi.org/10.1016/s0307-904x(82)80099-1
DB - Crossref
ER -