This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominated sorting genetic algorithm (NSGA-II) and clustering in the objective space. It is first argued that for good scalability, clustering or some other form of niching in the objective space is necessary and the size of e...

This paper considers a transportation problem for moving empty or laden containers for a logistic company. A model for this truck and trailer vehicle routing problem (TTVRP) is first constructed in the paper. The solution to the TTVRP consists of finding a complete routing schedule for serving the jobs with minimum routing distance and number of trucks, subject to a number of constraints such a...

Financial portfolio optimization is a challenging problem. First, the problem is multiobjective (i.e.: minimize risk and maximize profit) and the objective functions are often multimodal and non smooth (e.g.: value at risk). Second, managers have often to face real-world constraints, which are typically non-linear. Hence, conventional optimization techniques, such as quadratic programming, cann...

Abstract In the real world, we often encounter cases where the information / data items can’t be determined with certainty. Hence the value of the datum in the data is assessed using an interval. Meanwhile multiobjective linear programming model is more adequate to describe the problem in the real world. Thus, the multiobjective linear programming problem will be developed into a multiobjective...

Maximin strategy has its origin in game theory, but it can be adopted for effective multiobjective optimization. This paper proposes a particle swarm multiobjective optimiser, maximinPSO, which uses a fitness function derived from the maximin strategy to determine Pareto-domination. The maximin fitness function has some very desirable properties with regard to multiobjective optimization. One a...

This paper develops the theoretical and methodological relationship between multiobjective decision trees (MODT) and the multiobjective risk impact analysis method (MRIAM)—two tools that are useful in decision-making at each step of the system life cycle. Decision trees have been extensively used in decision problems with great success. Multiobjective decision trees include multiple noncommensu...

Large software companies have to plan their project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering limited resources. Project portfolio managers need methods and tools to find a good solution for complex project portfolios and multiobjective target criteria efficiently. However, software project portfolios are chall...

Multiplex Polymerase Chain Reaction (PCR) assay is to amplify multiple target DNAs simultaneously using different primer pairs for each target DNA. Recently, it is widely used for various biology applications such as genotyping. For sucessful experiments, both the primer pairs for each target DNA and grouping of targets to be actually amplified in one tube should be optimized. This involves mul...

Nature-inspired computational techniques are nowadays being developed for and employed in various application domains. Evolutionary algorithms, known as general and robust optimizers, have recently been extended to deal with multiobjective optimization where search for the best among candidate solutions is performed not according to one, but multiple, usually conflicting objectives. In this pap...

In this paper multiobjective optimization problem simultaneously optimized using hybrid PS-ACO algorithm has been attempted. The methodology used in this paper is based upon the information sharing and movement of swarms or particles in a search space, and further applying ACO on the result obtained by the PSO. Multiobjective optimization problems are present at physical design level at partiti...