Business Commons^™

Predictive Analytics Of Organizational Decisions And The Role Of Rationality, Arash Barfar

USF Tampa Graduate Theses and Dissertations

How can we predict key decisions made by organizations in the presence of big data and on-demand information? In this dissertation we exploit a large repository of B2B real-time transactional data with service quality indicators and present evidence that organizational decision analytics apply both rational and boundedly-rational (i.e. behavioral) economic models. The dissertation’s findings demonstrate that both utility and heuristic models, respectively, play significant roles in predicting organizational decisions on churn, a key decision in this context. In the presence of a large data set the assumed rationality of organizations appears to provide accurate predictions in uncontrolled experiences and selected …

Period Decompositions For The Capacitated Lot Size Problem With Setup Times, Silvio Alexandre De Araujo, Bert De Reyck, Zeger Degraeve, Ioannis Fragkos, Raf Jans

Research Collection Lee Kong Chian School Of Business

We study the multi-item capacitated lot sizing problem with setup times. Based on two strong reformulations of the problem, we present a transformed reformulation and valid inequalities that speed up column generation and Lagrange relaxation. We demonstrate computationally how both ideas enhance the performance of our algorithm and show theoretically how they are related to dual space reduction techniques. We compare several solution methods and propose a new efficient hybrid scheme that combines column generation and Lagrange relaxation in a novel way. Computational experiments show that the proposed solution method for finding lower bounds is competitive with textbook approaches and …

Judging Dread: A Quantitative Investigation Of Affect, Psychometric Dread And Risk Consequence, Melvyn Griffiths

Theses: Doctorates and Masters

Risk is generally understood as a product of the likelihood and consequence of an event. However, the way in which estimations of consequences are formed is unclear due to the complexities of human perception. In particular, the influence of Affect, defined as positive or negative qualities subjectively assigned to stimuli, may skew risk consequence judgements. Thus a clearer understanding of the role of Affect in risk consequence estimations has significant implications for risk management, risk communication and policy formulation.

In the Psychometric tradition of risk perception, Affect has become almost synonymous with the concept of Dread, despite Dread being measured …

A Hybrid Scatter Search/Electromagnetism Meta-Heuristic For Project Scheduling, Dieter Debels, Bert De Reyck, Roel Leus, Mario Vanhoucke

Research Collection Lee Kong Chian School Of Business

In the last few decades, several effective algorithms for solving the resource-constrained project scheduling problem have been proposed. However, the challenging nature of this problem, summarised in its strongly NP-hard status, restricts the effectiveness of exact optimisation to relatively small instances. In this paper, we present a new meta-heuristic for this problem, able to provide near-optimal heuristic solutions for relatively large instances. The procedure combines elements from scatter search, a generic population-based evolutionary search method, and from a recently introduced heuristic method for the optimisation of unconstrained continuous functions based on an analogy with electromagnetism theory. We present computational …

Automated Manpower Rostering: Techniques And Experience, C. M. Khoong, Hoong Chuin Lau, L. W. Chew

Research Collection School Of Computing and Information Systems

We present ROMAN, a comprehensive, generic manpower rostering toolkit that successfully handles a wide spectrum of work policies found in service organizations. We review the use of various techniques and methodologies in the toolkit that contribute to its robustness and efficiency, and relate experience gained in addressing manpower rostering problems in industry.