Krzysztof Bzdyra

Multiple Project Portfolio Scheduling Subject to Mass Customized Service

Declarative framework enabling to determine conditions as well as to develop a decision making software supporting small and medium size enterprises aimed at unique, multi project-like and mass customized oriented production is discussed. The set of unique production orders grouped into portfolio orders is considered. To each production order treated as an activity network common shared resources operation times of which are known in advance are allotted. The problem concerns of scheduling of a newly inserted projects portfolio subject to constraints imposed by a multi-project environment The answer sought is: Whether a given portfolio can be completed within assumed time period in a manufacturing system in hand? The goal is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi project-like and mass customized oriented production scheduling. The attached calculation example illustrates the computational efficiency of the proposed solution.

Knowledge Discovery in Enterprise Databases for Forecasting New Product Success

This paper presents the knowledge discovery process that aims to improve the forecast quality of the success of new product development projects. The critical success factors for new product development are identified on the basis of information acquired from an enterprise system, including the fields of sales and marketing, research and development, production, and project management. The proposed knowledge discovery process consists of stages such as data selection from enterprise databases, data preprocessing, data mining, and the use of the discovered patterns for forecasting new product success. The illustrative example presents the use of fuzzy neural networks for forecasting net profit from new products.

A Hybrid Method for Modeling and Solving Supply Chain Optimization Problems with Soft and Logical Constraints

This paper presents a hybrid method for modeling and solving supply chain optimization problems with soft, hard, and logical constraints. Ability to implement soft and logical constraints is a very important functionality for supply chain optimization models. Such constraints are particularly useful for modeling problems resulting from commercial agreements, contracts, competition, technology, safety, and environmental conditions. Two programming and solving environments, mathematical programming (MP) and constraint logic programming (CLP), were combined in the hybrid method. This integration, hybridization, and the adequate multidimensional transformation of the problem (as a presolving method) helped to substantially reduce the search space of combinatorial models for supply chain optimization problems. The operation research MP and declarative CLP, where constraints are modeled in different ways and different solving procedures are implemented, were linked together to use the strengths of both. This approach is particularly important for the decision and combinatorial optimization models with the objective function and constraints, there are many decision variables, and these are summed (common in manufacturing, supply chain management, project management, and logistic problems). The system with Eplex library was proposed to implement a hybrid method. Additionally, the proposed hybrid transformed model is compared with the MILP-Mixed Integer Linear Programming model on the same data instances. For illustrative models, its use allowed finding optimal solutions eight to one hundred times faster and reducing the size of the combinatorial problem to a significant extent.

Mass Customized Projects Portfolio Scheduling - Imprecise Operations Time Approach

Declarative framework enabling to determine conditions employed in a decision support systems aimed at small and medium size enterprises involved in a unique, multi project-like and mass customized oriented production is discussed. The unique production orders grouped into the set of portfolio orders is considered. To each production order treated as an activity network of common shared resources, known in advance, however by nature imprecise operation times are allotted. The problem concerns of scheduling of a newly inserted projects portfolio taking into account imprecise operations imposed by a multi–project environment. The answer sought is: Whether a given portfolio can be completed within assumed time period in a manufacturing system in hand The goal is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi project-like and mass customized oriented production scheduling. The attached calculation example illustrates the computational efficiency of the proposed solution.

Estimating New Product Success with the Use of Intelligent Systems

Abstract The paper presents identifying success factors in new product development and selecting new product portfolio. The critical success factors are identified on the basis of an enterprise system, including the fields of project management, marketing and customer’s comments concerning the previous products. The model of measuring the success of a product includes the indicators such as duration and cost of product development, and net profit from a product. The proposed methodology is based on identification of the relationships between product success and project environment parameters with the use of artificial neural networks and fuzzy neural system that is compared with the results from linear model. The presented method contains the stages of knowledge discovery process such as data selection, data preprocessing, and data mining in the context of an enterprise resource planning system database. The illustrative example enhances a performance comparison of intelligent systems in the context of data preprocessing.

Constraint programming approach to design of deadlock-free schedules in concurrent production systems

This work presents constraint programming (CP) approach applied to determine deadlock-free schedules in concurrent production processes. The rules of resource conflict resolution have been expressed by means of a set of predicates, which define constraints for the problem decisive variables. Predicate model has been defined in time and event domains and implemented in procedures of propagating and distributing the variable values. The predicates define sufficient conditions for existence of deadlock-free schedules of operations, which meet the prescribed qualitative and quantitative constraints

A declarative decision support framework for scheduling groups of orders

This paper deals with declarative decision support framework for scheduling groups of orders. All orders in a group should be delivered at the same time after processing. The authors present a novel declarative approach to modeling and solving scheduling problems as a declarative decision support framework. The proposed framework makes it possible to ask different types of questions (general, specific, logical, etc.). It also allows, scheduling emerging orders or groups of orders without changing the existing schedules. To implement was used CLP (Constraint Logic Programming) environment. To increase the efficiency of the framework, particularly in the area of optimization made its integration with MP (Mathematical Programming) environment. The paper also presents the implementation of illustrative model, using the proposed framework. In addition, an efficiency analysis of the presented solution in relation to the application of mathematical programming have been conducted.

Robust Scheduling Subject to Multi-project Environment Constraints

The main objective is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multi project-like and mass customized oriented multi-product scheduling. Its formal representation enables to formulate the straight and reverse problem scheduling of a newly inserted orders portfolio subject to constraints imposed by an enterprise multi-project environment. Considered problems correspond to the routine questions faced by decision makers and are formulated either in the straight or reverse way, e.g. Is it possible to undertake a new portfolio under given resources availability (e.g. constrained in time) while guaranteeing disturbance-free execution of the already executed portfolios? What values and of what decision variables guarantee the production order (or orders portfolio) will completed while following assumed set of performance indexes? In that context a computationally effective approach aimed at simultaneous routing and allocation as well as batching and scheduling of a new portfolio subject to constraints imposed by a multi-project environment is sought. Provided examples illustrate both cases while taking into account robust scheduling requirements imposed by multi-project environment constraints.

Usefulness of Software Valuation Methods at Initial Stages of ERP Implementation

Abstract This work discusses the problem of selecting methods for valuing the costs and estimating the time of implementing computer systems in cases when system modification is necessary. The methods presented in literature are reviewed and the stages of strategic phase of implementation characterised. On the basis of the analysis of data required by each method and the data obtained at different stages, appropriate selection of methods for each stage was proposed.

The Software Cost Estimation Method Based on Fuzzy Ontology

Abstract In the course of sales process of Enterprise Resource Planning (ERP) Systems, it turns out that the standard system must be extended or changed (modified) according to specific customer’s requirements. Therefore, suppliers face the problem of determining the cost of additional works. Most methods of cost estimation bring satisfactory results only at the stage of pre-implementation analysis. However, suppliers need to know the estimated cost as early as at the stage of trade talks. During contract negotiations, they expect not only the information about the costs of works, but also about the risk of exceeding these costs or about the margin of safety. One method that gives more accurate results at the stage of trade talks is the method based on the ontology of implementation costs. This paper proposes modification of the method involving the use of fuzzy attributes, classes, instances and relations in the ontology. The result provides not only the information about the value of work, but also about the minimum and maximum expected cost, and the most likely range of costs. This solution allows suppliers to effectively negotiate the contract and increase the chances of successful completion of the project.