In recent decades, droughts have become more frequent and severe due to global warming, the amount of water in dams reservoirs has decreased many regions. To alleviate shortage problem, we modeled allocation achieve optimal combination electricity. A multi-objective optimization model for was developed. grid method used rasterize calculate reservoir capacity dams. The improve distribution schem...

Auctions and exchanges are important coordination mechanisms for multiagent systems. Most multi-good markets are combinatorial in that the agents have preferences over bundles of goods. We study the possibility of determining prices so as to support (efficient) allocations in combinatorial economies where a seller (or arbitrator) wants to implement an efficient allocation. Conditions on the exi...

We develop a multi-objective model for the resource allocation problem in a dynamic PERT network, where the activity durations are exponentially distributed random variables and the new projects are generated according to a Poisson process. This dynamic PERT network is represented as a network of queues, where the service times represent the durations of the corresponding activities and the arr...

The buffer allocation problem (BAP) has been widely studied by researchers while pursuing diverse research goals. Similarly, the cross-entropy method has been applied to a variety of optimisation problems with single objectives. In this article it is extended to the multiobjective case and proposed as a computationally economic approach to optimise at least two conflicting objectives of the BAP...

In a R&D department, several projects may have to be implemented simultaneously within a certain period of time by a limited number of human resources with diverse skills. This paper proposes an optimisation model for the allocation of multi-skilled human resources to R&D projects, considering individual workers as entities having different knowledge, experience and ability. The model focuses o...

An important issue in multi-objective optimisation is how to ensure that the obtained non-dominated set covers the Pareto front as widely as possible. A number of techniques (e.g. weight vectors, niching, clustering, cellular structures, etc.) have been proposed in the literature for this purpose. In this paper we propose a new approach to address this issue in multi-objective combinatorial opt...