We propose a new genetic algorithm with optimal recombination for the asymmetric instances of travelling salesman problem. The algorithm incorporates several new features that contribute to its effectiveness: (i) Optimal recombination problem is solved within crossover operator. (ii) A new mutation operator performs a random jump within 3-opt or 4-opt neighborhood. (iii) Greedy constructive heu...

This paper describes Zenith, a discovery system that performs constructive induction. The system is able to generate and extend new features for concept learning using agenda-based heuristic search. The search is guided by feature worth (a composite measure of discriminability and cost). Zenith is distinguished from existing constructive induction systems by its interaction with a performance s...

In this paper, we study an assembly job shop scheduling problem with tree-structured precedence constraints and jobs characterized by specific bills of materials. We propose a fast and efficient constructive heuristic that is able to easily deal with real-world sized instances. The production schedule takes into account the actual availability of materials in stock as well as the supply times a...

This paper presents a genetic algorithm for solving the optimal transmission network applied to the expansion planning of Colombia’s system. Main improvements have been introduced in the genetic algorithm: initial population is obtained by constructive heuristic methods of optimization, and elitism and building block concepts are used in the optimization process. An important part of this optim...

The algorithm we present for solving the Car Sequencing Problem as defined in the Roadef Challenge 2005 consists of the following components. First, a constructive heuristic is used to generate an initial sequence. Next, a local search is applied to improve the solution quality. Because a simple local search would stop in a local optimum as soon as no more improvements can be achieved with any ...

Timetabling problems are well known NP-hard constraint satisfaction, and real-world cases often have complicated and challenging structures. For such problems, we present a new hybrid method, “Interleaved Constructive Memetic Algorithm” (ICMA) that interleaves memetic algorithms with constructive methods. ICMA works using an active subset of all the events. Starting with a few events, in multip...

In this paper we study a complex real world workforce scheduling problem. We apply constructive search and variable neighbourhood search (VNS) metaheuristics and enhance these methods by using a variable fitness function. The variable fitness function (VFF) uses an evolutionary approach to evolve weights for each of the (multiple) objectives. The variable fitness function can potentially enhanc...

In this paper, we consider the problem of scheduling n jobs on m machines in an open shop environment so that the sum of completion times or mean flow time becomes minimal. For this strongly NP-hard problem, we develop and discuss different constructive heuristic algorithms. Extensive computational results are presented for problems with up to 50 jobs and 50 machines, respectively. The quality ...

In industry, when flexible manufacturing systems are designed within a group technology approach, numerous decision-taking processes emerge requiring control of the multiple characteristics of the system. In this context, several grouping problems are identified within the scope of combinatorial optimisation. Such is the case of the part families with precedence constraints problem, which is de...