Browsing by Author "Oppen, Johan"

Now showing 1 - 2 of 2

Access status: Open Access ,
An attribute based similarity function for VRP Decision Support
(2012) Løkketangen, Arne; Oppen, Johan; Oyola, Jorge; Woodruff, David L.
When solving problems in the real world using optimization tools, the model solved by the tools is often only an approximation of the underlying, real, problem. In these circumstances, a decision maker (DM) should consider a diverse set of good solutions, not just an optimal solution as produced using the model. On the other hand, the same DM will only be interested in seeing a few of the alternative solutions, and not the plethora of solutions often produced by modern search techniques. There is thus a need to distinguish between good solutions using the attributes of solutions. We develop a distance function of the type proposed in the Psychology literature by Tversky (1977) for the class of VRP problems. We base our difference on the underlying structure of solutions. A DM is often interested in focusing on a set of solutions fulfilling certain conditions that are of specific importance that day, or in general, like avoiding a certain road due to construction that day. This distance measure can also be used to generate solutions containing these specific classes of attributes, as the normal search process might not supply enough of these interesting solutions. We illustrate the use of the functions in a Multiobjective Decision Support System (DSS) setting, where the DM might want to see the presence (or absence) of certain attributes, and show the importance of identifying solutions not on the Pareto front. Our distance measure can use any attributes of the solutions, not just those defined in the optimization model.
Access status: Open Access ,
Decision support for allocating farmed fish to customer orders using a bi-objective optimization model
(Wydawnictwa AGH, 2022) Knudseth, Sunniva Haukvik; Molland, Even; Hoff, Arild; Hvattum, Lars Magnus; Oppen, Johan
Aquaculture is an important industry in certain coastal areas. Focusing on the farming of salmon and trout, an operational planning problem arises with the goal of allocating a supply of fish to the demand that is expressed through customer orders. This paper provides a conceptual model of such a planning problem and defines a corresponding bi-objective mathematical programming model. The problem is novel with respect to the structure of fish transport and the rules for satisfying customer orders with respect to fish size, quality, certification, and health status. Computational experiments have been conducted to gain further insight into the use of the provided model to provide support for planners who are involved in operational decision-making. The results indicated that the bi-objective optimization model can be useful in situations where a supply is insufficient to cover all of the demand within a given planning horizon.