https://orion.journals.ac.za/pub <p><strong>Aims &amp; scope</strong><br>ORiON is the official journal of the Operations Research Society of South Africa (ORSSA) and is published biannually. Papers in the following categories are typically published in ORiON:<br><em>&nbsp;- Development of New Theory</em>, which may be useful to operations research practitioners, or which may lead to the introduction of new methodologies or techniques.<br><em>&nbsp;- OR Success Stories</em>, which describe demonstrably successful applications of operations research within the Southern African context (at the developing/developed economy interface) or similar environments elsewhere.<br><em>&nbsp;- OR Case Studies</em>, which might not be "success stories", but which emphasize novel approaches or describe pitfalls in the application of operations research.<br><em>&nbsp;- OR Methodological Reviews</em>, which survey new and potentially useful methodological developments, aimed at operations research practitioners especially in Southern Africa.</p> <p>The above list is by no means exhaustive.</p> Operations Research Society of South Africa (ORSSA) en-US ORiON 0259-191X <p>The following license applies:</p><p><strong> Attribution CC BY</strong></p><p>This <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">license</a> lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit you for the original creation.</p> https://orion.journals.ac.za/pub/article/view/793 Jaco Visagie Copyright (c) 2024 ORiON 2024-12-30 2024-12-30 40 2 10.5784/40-2-793 https://orion.journals.ac.za/pub/article/view/778 <p>Portfolio decisions involve selecting a subset of alternatives that together maximize some measure of value, subject to resource constraints. Exact methods are available to solve portfolio decision problems, but these require time, expertise and effort that may not always be available. In response, recent research has proposed a number of computationally simple, psychologically plausible rule-based heuristics for portfolio decision making. Simulation studies have shown that these portfolio heuristics perform well relative to exact approaches, but portfolio selection heuristics have yet to be applied in a real-world setting. Our study addresses this gap by using portfolio heuristics to support the selection of research grant proposals at a research institute in South Africa. We compare results obtained with portfolio heuristics to those obtained using two more traditional form of decision support, the standard linear-additive portfolio model, and robust portfolio modelling. We found that portfolios constructed using portfolio heuristics yielded over 90% of the value of optimal portfolios, selected slightly different portfolios potentially useful in a sensitivity analysis role, and were experienced as providing transparent and easy to understand decision support. Heuristic portfolios were slighly but consistently outperformed by those generated by robust portfolio modelling. Collectively, our study contributes to the growing body of evidence supporting the use of psychological heuristics in the realm of portfolio decision-making.</p> Dieudonne Kabongo Kantu Ian N. Durbach Copyright (c) 2024 ORiON 2024-12-21 2024-12-21 40 2 109 133 10.5784/40-2-778 https://orion.journals.ac.za/pub/article/view/792 <p>Several computer programs that can implement the Out-of-Kilter algorithm have been written. To date programs have been written in Fortran, Algol, Pascal, Basic, C++ and Matlab. According to the knowledge of the author, a program to do this in R has not yet been written. The R program written in this article can solve both the maximum flow and minimum cost-maximum flow problems. Since the Out-of-Kilter algorithm has a network flow as input, it can also be used to solve the flow in any problem whose information can be presented in the form of a network flow. This includes among others the transportation problem, the assignment problem, the shortest route problem and the caterer problem.</p> Wessel Hendrik Moolman Copyright (c) 2024 ORiON 2024-12-22 2024-12-22 40 2 135 146 10.5784/40-2-792