In this paper, instead of the classical approach to the multi-criteria location selection problem, a new approach was presented based on selecting a portfolio of locations. First, the indices affecting the selection of maintenance stations were collected. The K-means model was used for clustering the maintenance stations. The optimal number of clusters was calculated through the Silhou...

We develop a generic tool for approximating the Pareto front of multicriteria optimization problems using stochastic local search algorithms. Our algorithmic scheme handles problems that the multi-criteria context introduces into the local search framework such as the non-uniqueness of the best neighbor and the potentially large size of the Pareto front. We demonstrate the performance of our al...

The aim of the paper is to show an example of interaction between the AI and OR elds of research using the Constraint Programming (CP) framework to glue them together. We solve a shortest path problem using the c-semiring-based framework for programming over soft constraints (SCLP), which is an extension of classical constraint solving and programming. The SCLP approac handle uniformly several ...

compared to conventional chlorination methods which apply chlorine at water treatment plant, booster chlorination has almost solved the problems of high dosages of chlorine residuals near water sources and lack of chlorine residuals in the remote points of a water distribution system (wds). however, control of trihalomethane (thm) formation as a potentially carcinogenic disinfection by-product ...

Scheduling for job shop is very important in both fields of production management and combinatorial op-timization. However, it is quite difficult to achieve an optimal solution to this problem with traditional opti-mization approaches owing to the high computational complexity. The combination of several optimization criteria induces additional complexity and new problems. In this paper, we pro...

In this paper, we propose an energy-efficient mathematical model for the resource-constrained project scheduling problem to optimize makespan and consumption of energy, simultaneously. In the proposed model, resources are speed-scaling machines. The problem is NP-hard in the strong sense. Therefore, a multi-objective fruit fly optimization algorithm (MOFOA) is developed. The MOFOA uses the VIKO...

We elaborate upon new strategies and heuristics for solving multi-criteria optimization problems via Answer Set Programming (ASP). In particular, we conceive a new solving algorithm, based on conflict-driven learning, allowing for non-uniform descents during optimization. We apply these techniques to solve realistic Linux package configuration problems, thereby showing how transparently such pr...