Multiple Project Portfolio Scheduling Subject to Mass Customized Service

Bzdyra, Krzysztof; Banaszak, Zbigniew; Bocewicz, Grzegorz

doi:10.1007/978-3-319-15796-2_2

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…The first approach includes exact algorithms, which produce optimum solutions [1,2,3]. The second approach is comprised of algorithms that provide admissible solutions refer to [4,5,6,7]. Very limited work focuses on the joint technological processes, transportation routing and financial [8].…”

Section: Introductionmentioning

confidence: 99%

“…In that context the paper can be seen as continuation of our former work aimed at multi-product production flow planning focused on coordination of processes and activities involved in course of work orders processing [4,5,9,11]. More precisely, the proposed approach provides the framework allowing for considering both precise (crisp), and imprecise (fuzzy) data in a unified way and treat them in a unified form of a discrete Constraint Satisfaction Problem (CSP) [12].…”

Section: Introductionmentioning

confidence: 99%

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Mass Customized Projects Portfolio Scheduling - Imprecise Operations Time Approach

Bzdyra

Bocewicz

Banaszak

2015

AMM

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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.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mass Customized Projects Portfolio Scheduling - Imprecise Operations Time Approach

Bzdyra

Bocewicz

Banaszak

2015

AMM

Self Cite

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“…In that context, CP can be considered as a well-suited framework for the development of decision-making software supporting SMEs in the course of a multi-Zbigniew Banaszak, Grzegorz Bocewicz project-like and mass customized [17,20,23] oriented production where unique production orders grouped into portfolios have to be completed in assumed time periods.…”

Section: Introductionmentioning

confidence: 99%

Declarative Modeling for Production Order Portfolio Scheduling

Banaszak

Bocewicz

2014

Foundations of Management

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Acta Technologica Agriculturae 1/2016Dušan Páleš et al.The most effective way for determination of curves for practical use is to use a set of control points. These control points can be accompanied by other restriction for the curve, for example boundary conditions or conditions for curve continuity (Sederberg, 2012). When a smooth curve runs only through some control points, we refer to curve approximation. The B-spline curve is one of such approximation curves and is addressed in this contribution. A special case of the B-spline curve is the Bézier curve Rédl et al., 2014). The B-spline curve is applied to a set of control points in a space, which were obtained by measurement of real vehicle movement on a slope (Rédl, 2007(Rédl, , 2008. Data were processed into the resulting trajectory (Rédl, 2012;Rédl and Kučera, 2008). Except for this, the movement of the vehicle was simulated using motion equations (Rédl, 2003;Rédl and Kročko, 2007). B-spline basis functionsBézier basis functions known as Bernstein polynomials are used in a formula as a weighting function for parametric representation of the curve (Shene, 2014). B-spline basis functions are applied similarly, although they are more complicated. They have two different properties in comparison with Bézier basis functions and these are: 1) solitary curve is divided by knots, 2) basis functions are not nonzero on the whole area. Every B-spline basis function is nonzero only on several neighbouring subintervals and thereby it is changed only locally, so the change of one control point influences only the near region around it and not the whole curve.These numbers are called knots, the set U is called the knot vector, and the half-opened interval 〈u i , u i + 1 ) is the i-th knot span. Seeing that knots u i may be equal, some knot spans may not exist, thus they are zero. If the knot u i appears p times, hence u i = u i + 1 = ... = u i + p -1 , where p >1, u i is a multiple knot of multiplicity p, written as u i (p). If u i is only a solitary knot, it is also called a simple knot. If the knots are equally spaced, i.e. (u i + 1 -u i ) = constant, for every 0 ≤ i ≤ (m -1), the knot vector or knot sequence is said uniform, otherwise it is non-uniform.Knots can be considered as division points that subdivide the interval 〈u 0 , u m 〉 into knot spans. All B-spline basis functions are supposed to have their domain on 〈u 0 , u m 〉. We will use u 0 = 0 and u m = 1.To define B-spline basis functions, we need one more parameter k, which gives the degree of these basis functions. Recursive formula is defined as follows:This definition is usually referred to as the Cox-de Boor recursion formula. If the degree is zero, i.e. k = 0, these basis functions are all step functions that follows from Eq. (1). N i, 0 (u) = 1 is only in the i-th knot span 〈u i , u i + 1 ). For example, if we have four knots u 0 = 0, u 1 = 1, u 2 = 2 and u 3 = 3, knot spans 0, 1 and 2 are 〈0, 1), 〈1, 2) and 〈2, 3), and the basis functions of degree 0 are N 0, 0 (u) = 1 on interval 〈0, 1) Acta In this co...

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Knowledge Discovery in Enterprise Databases for Forecasting New Product Success

Relich

Bzdyra

2015

Intelligent Data Engineering and Automated Learning – IDEAL 2015

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Multiple Project Portfolio Scheduling Subject to Mass Customized Service

Cited by 7 publications

References 10 publications

Mass Customized Projects Portfolio Scheduling - Imprecise Operations Time Approach

Mass Customized Projects Portfolio Scheduling - Imprecise Operations Time Approach

Declarative Modeling for Production Order Portfolio Scheduling

Knowledge Discovery in Enterprise Databases for Forecasting New Product Success

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