Concepción Maroto

A comprehensive review and evaluation of permutation flowshop heuristics

In this work we present a review and comparative evaluation of heuristics and metaheuristics for the well-known permutation flowshop problem with the makespan criterion. A number of reviews and evaluations have already been proposed. However, the evaluations do not include the latest heuristics available and there is still no comparison of metaheuristics. Furthermore, since no common benchmarks and computing platforms are used, the results cannot be generalised. We propose a comparison of 25 methods, ranging from the classical Johnsons algorithm or dispatching rules to the most recent metaheuristics, including tabu search, simulated annealing, genetic algorithms, iterated local search and hybrid techniques. For the evaluation we use the standard test of Taillard [Eur. J. Operation. Res. 64 (1993) 278] composed of 120 instances of different sizes. In the evaluations we use the experimental design approach to obtain valid conclusions on the effectiveness and efficiency of the different methods tested.

A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility

After 50 years of research in the field of flowshop scheduling problems the scientific community still observes a noticeable gap between the theory and the practice of scheduling. In this paper we aim to provide a metaheuristic, in the form of a genetic algorithm, to a complex generalized flowshop scheduling problem that results from the addition of unrelated parallel machines at each stage, sequence dependent setup times and machine eligibility. Such a problem is common in the production of textiles and ceramic tiles. The proposed algorithm incorporates new characteristics and four new crossover operators. We show an extensive calibration of the different parameters and operators by means of experimental designs. To evaluate the proposed algorithm we present several adaptations of other well-known and recent metaheuristics to the problem and conduct several experiments with a set of 1320 random instances as well as with real data taken from companies of the ceramic tile manufacturing sector. The results indicate that the proposed algorithm is more effective than all other adaptations.

A Robust Genetic Algorithm for Resource Allocation in Project Scheduling

Genetic algorithms have been applied to many different optimization problems and they are one of the most promising metaheuristics. However, there are few published studies concerning the design of efficient genetic algorithms for resource allocation in project scheduling. In this work we present a robust genetic algorithm for the single-mode resource constrained project scheduling problem. We propose a new representation for the solutions, based on the standard activity list representation and develop new crossover techniques with good performance in a wide sample of projects. Through an extensive computational experiment, using standard sets of project instances, we evaluate our genetic algorithm and demonstrate that our approach outperforms the best algorithms appearing in the literature.

Solving the Multi-Mode Resource-Constrained Project Scheduling Problem with genetic algorithms

In this paper we consider the Multi-Mode Resource-Constrained Project Scheduling Problem with makespan minimisation as the objective. We have developed new genetic algorithms, extending the representation and operators previously designed for the single-mode version of the problem. Moreover, we have defined a new fitness function for the individuals who are infeasible. We have tested different variants of the algorithm and chosen the best to be compared to different heuristics previously published, using standard sets of instances included in PSPLIB. Results illustrate the good performance of our algorithm.

SOLVING THE FLOWSHOP SCHEDULING PROBLEM WITH SEQUENCE DEPENDENT SETUP TIMES USING ADVANCED METAHEURISTICS

Abstract This paper deals with the permutation flowshop scheduling problem in which there are sequence dependent setup times on each machine, commonly known as the SDST flowshop. The optimisation criteria considered is the minimisation of the makespan or Cmax. Genetic algorithms have been successfully applied to regular flowshops before, and the objective of this paper is to assess their effectiveness in a more realistic and complex environment. We present two advanced genetic algorithms as well as several adaptations of existing advanced metaheuristics that have shown superior performance when applied to regular flowshops. We show a calibration of the genetic algorithms parameters and operators by means of a Design of Experiments (DOE) approach. For evaluating the proposed algorithms, we have coded several, if not all, known SDST flowshop specific algorithms. All methods are tested against an augmented benchmark based on the instances of Taillard. The results show a clear superiority of the algorithms proposed, especially for the genetic algorithms, regardless of instance type and size.

A MULTICRITERIA HEURISTIC METHOD TO IMPROVE RESOURCE ALLOCATION IN MULTIPROJECT SCHEDULING

Abstract Many works published in the area of project management make reference to the scheduling of single projects and time objectives like minimising project duration. Nevertheless, frequently companies manage various projects which share a pool of constrained resources, taking into account other objectives in addition to time. In order to add flexibility in using project scheduling tools, we have developed a multicriteria heuristic that improves lexicographicly two criteria: one time type – mean project delay or multiproject duration increase – and one no time type – project splitting, in-process inventory, resource levelling or idle resources – that can be chosen by the user. The multicriteria heuristic algorithm consists of several algorithms based on the improvement of multiproject feasible schedules. Through an extensive computational study, we have shown that this method improves the feasible multiproject schedule obtained from heuristic methods based on the priority rules coded Maximum Total Work Content (MAXTWK) and Minimum Latest Finish Time (MINLFT) as well as project management software – Microsoft Project, CA-SuperProject, Time Line and Project Scheduler.

A decision support system for a real vehicle routing problem

Abstract The vehicle routing problem has been widely studied in the literature, mainly because of the real world logistics and transportation problems related to it. In the present paper, a new two-stage exact approach for solving a real problem is shown, along with decision making software. In the first stage, all the feasible routes are generated by means of an implicit enumeration algorithm; afterwards, an integer programming model is designed to select in the second stage the optimum routes from the set of feasible routes. The integer model uses a number of 0–1 variables ranging from 2000 to 15,000 and gives optimum solutions in an average time of 60 seconds (for instances up to 60 clients). An interactive decision support system was also developed. The system was tested with a set of real instances and, in a worst-case scenario (up to 60 clients), the routes obtained ranged from a 7% to 12% reduction in the distance travelled and from a 9% to 11% reduction in operational costs.

The Evolution of Software Quality in Project Scheduling

Since the end of the 50’s when CPM -Critical Path Method- and PERT -Program Evaluation and Review Technique- were developed, the evolution of the use in practice of these and other methods of project scheduling has been closely linked to the evolution of the software and hardware which has made it possible from the start. We can divide its four decades of history into three principle periods. The first until the 70’s, during which large machines, mainframes, were necessary. Therefore, project scheduling in that period was quite costly, reserving it in practice for large projects and big companies. The PC’s are the protagonists of the second period, taking place in approximately the decade of the 80’s. In 1981 the IBM PC came out and in 1983 Harvard Project Manager software appeared. Later, tens of packages for the PC flooded the market, making it possible for any company to have access to software at a low cost and with few hardware requirements (Maroto and Tormos, 1994; Burke, 1997). Finally, the third period corresponds to the decade of the 90’s, in which software and hardware have made high quality and low price compatible. The improved quality of some programs has been achieved in successive versions by correcting flaws and deficiencies detected in previous ones, parallel to the improvements in the capabilities of the hardware and software in general. The programs are becoming more and more interactive and user-friendly, offering greater ease in connecting with other tools and more and better capabilities in resource-constrained project scheduling.

Operations strategy configurations in project process firms

Purpose – Seeks to focus on operations priority patterns and operations strategy. Configurations by testing them in a specific environment which contributes to demonstrating their applicability and generalizability.Design/methodology/approach – Using data from 130 Spanish companies with project process organization, their operations strategy is analyzed as a whole, without the following of a trade‐off pattern being observed.Findings – Cost, conformer and innovation strategy types, compared with other operations strategy configurations regarding variables used to develop project management configurations, for the most part exhibit a coherent behaviour, giving support to operations strategy validation at a higher theoretical level.Research limitations/implications – The two most important limitations are the relatively small sample size used in the study and the results obtained with the organization structure variable. Similar studies in other specific production process contexts should also be undertaken....

A multiple criteria supplier segmentation using outranking and value function methods

Abstract Suppliers play a key role in supply chain management which involves evaluation for supplier selection problem, as well as other complex issues that companies should take into account. The purpose of this research is to develop and test an integrated system, which allows qualifying providers and also supplier segmentation by monitoring their performance based on a multiple criteria tool for systematic decision making. This proposal consists in a general procedure to assess suppliers based mainly on exploiting all reliable databases of the company. Firstly, for each group of products, their evaluation criteria are defined collaboratively in order to determine their critical and strategic performance, which are then integrated with other criteria that are specific of the suppliers and represent relevant aspects for the company, also classified by critical and strategic dimensions. Two multiple criteria methods, compensatory and non-compensatory, are used and compared so as to point out their strengths, weaknesses and flexibility for the supplier evaluation in different contexts, which are usually relevant in the supply chain management. A value function approach is the appropriate method to qualify providers to be included in the panel of approved suppliers of the company as this process depends only on own features of the supplier. On the other hand, outranking methods such as PROMETHEE have shown greater potential and robustness to develop portfolios with suppliers that should be partners of the company, as well as to identify other types of relationships, such as long term contracts, market policies or to highlight those to be removed from their portfolio. These results and conclusions are based on an empirical research in a multinational company for food, pharmaceuticals and chemicals. This system has shown a great impact as it represents the first supplier segmentation proposal applied to industry, in which decision making not only takes into account opinions and judgements, but also integrates historical data and expert knowledge. This approach provides a robust support system to inform operative, tactical and strategic decisions, which is very relevant when applying an advanced management in practice.