Prof. E. Zilla Sinuany-Stern is from the Department of Industrial Engineering and Management (IEM) at Ben-Gurion University of the Negev, Beer-Sheva, Israel (since 1978). She held the Chair of Sir John and Lady Cohen Business and Industrial Management.
She earned a Ph.D. degree in Operations Research (OR) from Case Western Reserve University, in Cleveland, Ohio, USA, and BA MA Degrees in Economics and Statistics from Tel Aviv University.
She was the head of the IEM department in 1992-1994, and she was the Vice President of Academic Affairs of Ariel University during 2000-2008. She was a visiting Professor in several universities in USA, Australia, Europe, South Africa and South America.
She was Vice president 1 of EURO 2000-2004, and President of the OR Society of Israel (ORSIS) 1996-2000, and VP 1992-1996. She was Guest Editor of EJOR and Annals of OR. Since 1993 she is a member of the international advisory board of the Journal of Operational Research Society (JORS). In 2010 she won the ORSIS Prize for excellent paper (with Alper).
Her Areas of research are: Operations Research & Management Science and its application, more specifically: Resource allocation, Efficiency analysis (DEA), Logistics, Decision Analyses, AHP, Multi Objective Optimization, Production Planning, Reliability and Maintenance.
She authored and co-authored over 170 publications, of which over 100 papers are in refereed journals such as: EJOR, JORS, OPER RES, Annals of OR, MANAG SCI, COMP & OR, COMP & IE, IIE TRANS, CJOR, INT J. of PROD RES, INT J. of Logistic SYS MANAG, J. of Transport GEOG, PROD PLAN Control, Location SCI, Accident ANAL PREV, Water RESOUR RES, R&D MANAG, COMP ENVIRON URBAN, J Regional SCI, Simulation.
She consulted for various organizations in industry and the public sector in the USA and Israel mainly in planning and logistics such as: Cleveland Trust Bank, Indiana Commission of Higher Education, Israel's Police Headquarter, Electric Authorities of Israel, and Nuclear Commission of Israel.
Till 2017 she was a member of the Council for Higher Education in Israel, she also chaired the Committee of Quality Assurance there.
Current research: Handbook of OR &MS in Higher Education, Robust ranking in DEA context, Water Allocation between the Agricultural and the Municipal Sectors, Emergency evacuation models after earthquake.
Foundations of OR: from LP to DEA
Operations Research (OR) as a discipline was born during WWII in UK and USA, when scientists from various disciplines gathered to solve complex military operations, such as: resource allocation, location and logistics. Thereafter, OR was successfully applied to civil problems. OR is a combination of several disciplines: Mathematics, Computer Science, Statistics, Economics, Business and Industrial Engineering - and has many titles, such as: Management Science, Decision Science and Analytics.
Although, initially, OR was interdisciplinary, it developed in the direction of mathematical modeling of complex systems, and problems, which often do not have a closed-form mathematical solution.
Linear Programming (LP), with its Simplex algorithm, developed by Dantzig in 1947, is the preeminent methodology associated with OR. LP stems from the simplest economic production problem (i.e., how much should be produced of each product to maximize profit or minimize cost under resources constraints) - in which objective function and constraints are linear and the variables are non-negative. The success of Simplex, and other OR algorithms is due to the rapid, development of Computer Science, another innovative, post WWII science.
Ever since, LP has developed in multiple directions, such as: large scale optimization, approximations for non-LP problems, Integer Programming (IP), mixed IP, transportation, timetabling, networks and Data Envelopment Analysis (DEA). Some of these developments required new, improved, and faster algorithms.
DEA (1978) deals with another economic problem - finding the efficient frontier of decision-making units (DMUs) - based on given inputs and output data ex-ante. DEA employs sets of LP problems - one for each DMU - to determine the efficiency of DMU.
The lecture covers the history of OR, LP and its derivatives - focusing on developments in DEA.