Pawel Jan Kalczynski

An improved NEH heuristic to minimize makespan in permutation flow shops

For over 20 years the NEH heuristic of Nawaz, Enscore, and Ham [A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega, The International Journal of Management Science 1983;11:91-5] has been commonly regarded as the best heuristic for solving the NP-hard problem of minimizing the makespan in permutation flow shops. The strength of NEH lies mainly in its priority order according to which jobs are selected to be scheduled during the insertion phase. Framinan et al. [Different initial sequences for the heuristic of Nawaz, Enscore and Ham to minimize makespan, idle time or flowtime in the static permutation flowshop problem. International Journal of Production Research 2003;41:121-48] presented the results of an extensive study to conclude that the NEH priority order is superior to 136 different orders examined. Based upon the concept of Johnsons algorithm, we propose a new priority order combined with a simple tie-breaking method that leads to a heuristic that outperforms NEH for all problem sizes.

On no-wait and no-idle flow shops with makespan criterion

The paper deals with the NP-hard problems of minimizing the makespan in m-machine no-wait and no-idle permutation flow shops. We identify networks whose longest path lengths represent the makespans. These networks reveal the duality between the two problems, and show graphical explanations of the fact that under no-wait and no-idle conditions the makespan can be a decreasing function of some job processing times. Moreover, they also lead to a natural reduction of the no-wait flow shop problem to the traveling salesman problem, some lower bounds on the shortest makespan, and new efficiently solvable special cases.

A heuristic for minimizing the makespan in no-idle permutation flow shops

The paper deals with the problem of finding a job sequence that minimizes the makespan in m-machine flow shops under the no-idle condition. This condition requires that each machine must process jobs without any interruption from the start of processing the first job to the completion of processing the last job. Since the problem is NP-hard, we propose a constructive heuristic for solving it that significantly outperforms heuristics known so far.

Filtering the Web to Feed Data Warehouses

From the Publisher: Information is a key factor in business today, and data warehousing has become a major activity in the development and management of information systems to support the proper flow of information. Unfortunately, the majority of information systems are based on structured information stored in organizational databases, which means that the company is isolated from the business environment by concentrating on their internal data sources only. It is therefore vital that organizations take advantage of external business information, which can be retrieved from Internet services and mechanically organized within the existing information structures. Such a continuously-extending integrated collection of documents and data could facilitate decision-making process in the organization. Filtering the Web to Feed Data Warehouses discusses areas such as: * how to use data warehouse for filtering Web content * how to retrieve relevant information from diverse sources on the Web * how to handle the time aspect * how to mechanically establish links among data warehouse structures and documents filtered from external sources * how to use collected information to increase corporate knowledge and gives a comprehensive example, illustrating the idea of supplying data warehouses with relevant information filtered from the Web.

Predicting On-Line Task Completion with Clickstream Complexity Measures: A Graph-Based Approach

A model that uses navigational complexity to classify on-line shopping sessions and information-search tasks as successful or unsuccessful is described. A graph-based approach to representing clickstream is employed to capture the complexity. A total of 485 individual goal-oriented shopping sessions on five different Web sites were analyzed. Ten complexity metrics were studied in order to select the ones that can predict the outcome (i.e., success or failure) of a goal-oriented navigational session. The practical applications to e-business, including the implementation of the proposed model, are discussed.

A heuristic for minimizing the expected makespan in two-machine flow shops with consistent coefficients of variation

Abstract The paper deals with the classical problem of minimizing the makespan in a two-machine flow shop. When the job processing times are deterministic, the optimal job sequence can be determined by applying Johnson’s rule. When they are independent and exponential random variables, Talwar’s rule yields a job sequence that minimizes the makespan stochastically. Assuming that the job processing times are independently and Weibull distributed random variables, we present a new job sequencing rule that includes both Johnson’s and Talwar’s rules as special cases. The proposed rule is applicable as a heuristic whenever the job processing times are characterized by their means and the same coefficient of variation. Simulation results show that it leads to very encouraging results when the expected makespan is minimized.

Strategic Competitive Location: Improving Existing and Establishing New Facilities

Competitive facility location models consider two main strategies for increasing the market share captured by a chain subject to a budget constraint. One strategy is the improvement of existing facilities. The second strategy is the construction of new facilities. In this paper we analyse these two strategies as well as the joint strategy which is a combination of the two. All three strategies are formulated as a unified model. The best solution to an individual strategy is a feasible solution to the joint one. Therefore, the joint strategy must yield solutions that are at least as good as the solutions to each of the individual strategies. Based on the results of extensive experiments, we conclude that the increase in market share captured by a chain when the joint strategy is employed can be significantly higher than increases obtained by individual strategies. A branch and bound procedure and a tabu search heuristic are constructed for the solution of the unified model. Both algorithms performed very well on a set of test problems with up to 900 demand points. A total of 62% of the test problems were optimally solved by the branch and bound procedure.

A cover-based competitive location model

In this paper we propose a new approach to estimating market share captured by competing facilities. The approach is based on cover location models. Each competing facility has a ‘sphere of influence’ determined by its attractiveness level. More attractive facilities have a larger radius of the sphere of influence. The buying power of a customer within the sphere of influence of several facilities is equally divided among the competing facilities. The buying power of a customer within the sphere of influence of no facility is lost. Assuming the presence of competition in the area, the objective is to add a number of new facilities to a chain of existing facilities in such a way that the increase of market share captured by the chain is maximized. The model is formulated and analysed. Optimal and heuristic solution algorithms are designed. Computational experiments demonstrate the effectiveness of the proposed algorithms.

A discrete model for optimal operation of fossil-fuel generators of electricity

This paper presents a new discrete approach to the price-based dynamic economic dispatch (PBDED) problem of fossil-fuel generators of electricity. The objective is to find a sequence of generator temperatures that maximizes profit over a fixed-length time horizon. The generic optimization model presented in this paper can be applied to automatic operation of fossil-fuel generators or to prepare market bids, and it works with various price forecasts. The model’s practical applications are demonstrated by the results of simulation experiments involving 2009 NYISO electricity market data, branch-and-bound, and tabu-search optimization techniques.

Dynamic identification of anonymous consumers' visit goals using clickstream

This paper presents a model for identifying general goals of anonymous consumers visiting a retail website. When visiting a transactional website, consumers have various goals such as browsing or purchasing a particular product during their current visit. By predicting these goals early in the visit, online merchants could personalise their offer to better fulfil the needs of consumers. Most visitors remain anonymous to the website, however personalisation systems require demographic and transaction history data which is available only for registered and logged-on users. We propose a simple model which enables classifying anonymous visitors according to their goals after only a few clicks. The model is based solely on navigational patterns which can be automatically extracted from clickstream. Theoretical and managerial implications are presented.