This work deals with the so-called weighted independent domination problem, which is an NP-hard combinatorial optimization problem in graphs. In contrast to previous work, this paper considers the problem from a non-theoretical perspective. The first contribution consists in the development of three integer linear programming models. Second, two greedy heuristics are proposed. Finally, the last...

This paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mixed integer linear program. The problem can be optimally solved by the model. The paper also develops a novel metaheuristic base...

When assessing experimentally the performance of metaheuristic algorithms on a set of hard instances of an NP-complete problem, the required time to carry out the experimentation can be very large. A means to reduce the needed effort is to incorporate variance reduction techniques in the computational experiments. For the incorporartion of these techniques, the traditional approaches propose me...

the simultaneous optimization of multiple responses is an important problem in the design of industrial processes in order to achieve improved quality. in this paper, we present a new metaheuristic approach including simulated annealing and particle swarm optimization to optimize all responses simultaneously. for the purpose of illustration and comparison, the proposed approach is applied to tw...

Problems for which many objective functions are to be simultaneously optimised are widely encountered in science and industry. These multiobjective problems have also been the subject of intensive investigation and development recently for metaheuristic search algorithms such as ant colony optimisation, particle swarm optimisation and extremal optimisation. In this chapter, a unifying framework...

This paper proposes a visualization tool for analyzing the behavior of metaheuristic algorithms. It works by reproducing graphically the solutions generated in execution time. The tool was evaluated analyzing the Hybrid Grouping Genetic Algorithm for Bin Packing (HGGA_BP). It was used to solve a benchmark with 17 instances of the one dimensional Bin Packing problem (1D-BPP). The use of the visu...

This paper presents an exact algorithm, a constructive heuristic algorithm, and a metaheuristic for the Hamiltonian p-Median Problem (HpMP). The exact algorithm is a branch-and-cut algorithm based on an enhanced p -median based formulation, which is proved to dominate an existing p -median based formulation. The constructive heuristic is a giant tour heuristic, based on a dynamic programming fo...

The Annual Crop Planning (ACP) problem was a recently introduced problem in the literature. This study further expounds on this problem by presenting a new mathematical formulation, which is based on market economic factors. To determine solutions, a new local search metaheuristic algorithm is investigated which is called the enhanced Best Performance Algorithm (eBPA). eBPA's results are compar...

Transportation Network Design Problem (TNDP) aims to select the best project sets among a number of new projects. Recently, metaheuristic methods are applied to solve TNDP in the sense of finding better solutions sooner. PSO as a metaheuristic method is based on stochastic optimization and is a parallel revolutionary computation technique. The PSO system initializes with a number of random solu...

This paper addresses the multistage hybrid flow shop (HFS) scheduling problems. The HFS is the special case of flowshop problem. Multiple parallel machines are considered in each stage in the HFS. The HFS scheduling problem is known to be strongly NPhard. Hence, many researchers proposed metaheuristic algorithms for solving the HFS scheduling problems. This paper develops a bat algorithm (BA) t...