Genetic algorithms are kind of metaheuristic method in that they apply evolutionary techniques (best-fit selection, crossover, and mutation) to find optimal solution by iteratively attempting to improve current candidate solution with respect to the fitness criteria. The use of heuristic-based search through the application of reproduction, recombination, and mutation mechanisms keeps genetic a...

In this paper, we discuss the application of search-based software testing techniques for unit level testing of a real-world telecommunication middleware at Ericsson. Input data for the system under test consists of nested data structures, and includes non-trivial variables such as uninitialized pointers. Our current implementation analyzes the existing test cases to discover how to handle poin...

Evolutionary Algorithms (EAs) are well-known terms in many science fields. EAs usually interfere with science problems when common mathematical methods are unable to provide a good solution or finding the exact solution requires an unreasonable amount of time. Nowadays, many EA methods have been proposed and developed. Most of them imitate natural behavior, such as swarm animal movement. In thi...

This paper deals with the construction of binary sequences with low autocorrelation, a very hard problem with many practical applications. The paper analyzes several metaheuristic approaches to tackle this kind of sequences. More specifically, the paper provides an analysis of different local search strategies, used as standalone techniques and embedded within memetic algorithms. One of our pro...

This paper deals with a practical transportation model known as the Vehicle Routing Problem with Backhauls (VRPB), which aims at designing the minimum cost route set for satisfying both delivery and pick-up demands. In methodological terms, we propose a local search metaheuristic which explores rich solution neighborhoods composed of exchanges of variable-length customer sequences. To efficient...

This article proposes a local search metaheuristic solution approach for the Vehicle Routing Problem with Simultaneous Pick-ups and Deliveries (VRPSPD), which models numerous practical transportation operations in the context of reverse logistics. The proposed algorithm is capable of exploring wide solution neighborhoods by statically encoding moves into special data structures. To avoid cyclin...

We present a Tabu Search (TS) method that employs a simple version of ejection chains for coloring graphs. The procedure is tested on a set of benchmark problems. Empirical results indicate that the proposed TS implementation outperforms other metaheuristic methods, including Simulated Annealing, a previous version of Tabu Search and a recent implementation of a Greedy Randomized Adaptive Searc...

Assembly line balancing problem (ALBP) is a decision problem arising when designing or redesigning an assembly line and it consists in finding the optimal assignment of tasks among the workstations corresponding to some objectives. This paper deals with the single-model ALBP with the aim of minimizing the cycle time and maximizing the workload smoothness among the workstations. In order to solv...

This paper investigates scheduling job shop problems with sequence-dependent setup times under minimization of makespan. We develop an effective metaheuristic, simulated annealing with novel operators, to potentially solve the problem. Simulated annealing is a well-recognized algorithm and historically classified as a local-search-based metaheuristic. The performance of simulated annealing crit...

This paper proposes a new two-phase hybrid metaheuristic for vehicle routing problem with time windows (VRPTW). The first phase is to minimize the number of routes by means of variable neighborhood search algorithm, while the second phase is mainly aimed at minimizing the total travel distance using tabu search algorithm. Three neighborhood search operators (All-exchange, All-2-opt, All-crossex...