=Paper=
{{Paper
|id=Vol-2683/paper16
|storemode=property
|title=Searching for resilient project structure
|pdfUrl=https://ceur-ws.org/Vol-2683/paper16.pdf
|volume=Vol-2683
|authors=Judyta Ciemcioch,Grzegorz Ginda
}}
==Searching for resilient project structure==
https://ceur-ws.org/Vol-2683/paper16.pdf
Searching For Resilient Project Structure
Judyta Ciemcioch Grzegorz Ginda
AGH University of Science AGH University of Science
and Technology and Technology
Cracow, Poland Cracow, Poland
judyta.ciemcioch@gmail.com gginda@zarz.agh.edu.pl
Abstract—Project optimization often deals with simple Possible scale of project optimization depends mainly on
minimization of its makespan and cost for a given order of the assumed order of project components. The role of order of
project components i.e. project structure. However, project project components is nevertheless often neglected. And as a
execution effects may be improved at most with the application result – project optimization results in a suboptimal project
of appropriate project order. The problem of the utilization of implementation only.
appropriate project structure is nevertheless often neglected.
This is why project optimization efforts usually result in Possible project disruption caused by adverse changes in
suboptimal project implementation. Moreover, the actual surrounding environment are usually neglected while
effects of optimized project depend on possible disruptions in optimizing a project due to project analysis complexity.
surrounding environment. The meaningful disruptions may Hence the actual appearance of project disruptions result in
have different e.g. financial and other resource-based, societal, optimized project implementation performance which is far
environmenal nature etc. It is necessary, therefore, to make away from expected performance. Considering possible
project disruption-proof. This is why a framework for the project disruptions during project optimization becomes
framework that is capable of delivering project structure that important, therefore, to ensure expected project
makes project implementation resilient to possible disruptions implementation effects that are at least close to the expected
is presented in the paper. effects in the presence of disruptions. It seems that, because
to the fundamental role of applied project structure for final
Keywords—project management, project structure, disruption, performance of project implementation, the application of
resiliency appropriate choice of the structure would to make project
resilient to possible disruption resulting from changes in
surrounding environment.
I. INTRODUCTION
Rising of diverse natural, societal, political, and technical
Projects are used in diverse areas to obtain different goals. threads cause that resiliency to uncontrollable changes in
Successful project implementation depends on careful project surrounding environment becomes more and more interesting
preparation and project management. However, the topic for scientific research [1]. However, up to our
uncontrolled influence of continuously changing surrounding knowledge, despite an urgent need for providing reliable tools
environment, contemporary complex projects are for resilient planning of project implementation, no proposal
implemented in, may disrupt actual project implementation currently addresses coping with improving project resiliency
effects as well. For example, such influence may result from to disruptions changes in surrounding environment by means
changing fiscal, political, societal and environmental issues. of proper project structure choice. This is why a framework
This is why the implementation of contemporary complex for project optimization which is capable of delivering a
projects should be prepared in a way that makes such project project structure that makes project resilient to possible
resilient to possible disruptions in as much as it is only surrounding environment-induced disruptions. Thus, the rest
possible. of the paper is structured as follows. The second section is
Projects are optimized to provide necessary means for the devoted to tentative assumptions. The elements of actual
best possible project implementation results. Project disruption-aware project optimization framework are
optimization is aimed at obtaining the best possible levels of presented in the third section. Final conclusions are included
project characteristics – makespan, cost etc. Limits of in the last section.
available resources are included in this regard. The
optimization results in a project implementation timeline. II. TENTATIVE ASSUMPTIONS
Resulting project timeline deals with the applied order of A project consists of n components. The components are
project components – activities that make obtaining necessary related to one another by an obligatory precedence order. The
intermediate project implementation results – intermediate precedence order decides if each pair of project components
goals – possible. An order of project components is called may be applied only in sequence or in any way. Note that
project structure in the paper. A permissible project structure number of possible admissible project structures may rise a
results from pre-order of project components. The pre-order is lot with the cardinality of a set of project components.
defined by obligatory precedence of project components.
Once the implementation of project component starts it
doesn’t stop until its successful end. The same deals is true in
Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)
the case of the implementation of project components. Each Γ− = Γ+ ()
project component is responsible for some intermediate goals.
The goal may be achieved by means of using different This is why one of them is sufficient to describe obligatory
possible ways (modes). The application of each mode order of project components.
requires utilization of some resources. The resources deal
with manpower, equipment, materials, space, financial means Structure of project is defined by a digraph G(U,V) and a
etc. Actual availability of resources is limited and may corresponding n by n matrix G, where U denotes digraph’s
change in time. However, it is assumed that once a given vertices and V – digraph’s arcs. Note that in the case of all
resource is engaged, it becomes entirely involved in the above mentioned digraphs vertices (nodes) represent project
implementation of a project component til its successful components while the arcs – the precedence of project
completion. The availability of resources may be limited in components.
both time and space. Note that limited nature of resources A notion of a network S(G,Φ,Ψ) is applied to express
needed by project components may cause delays in actual actual project implementation. The network is based on a
start of project component implementation. digraph G. Symbols Φ, Ψ express sets of attributes describing
Implementation of project components may undergo project components and sets of attributes which define their
disruptions resulting from changes in surrounding economic, immediate precedence, respectively.
societal, technological, political, fiscal environment and The effects of project implementation are expressed by a
natural phenomena. Disruptions may result in diverse adverse set of meaningful attributes. The set may include casual
effects: delays, cost overruns, unnecessary blocking of tangible project attributes: makespan, cost, starting date, due
resources, a need for etc. Possible modes for project date as well as other original tangible attributes e.g. level of
component implementation may differ in actual sensitivity to the utilization of available resources. The application of
disruptions. intangible project attributes is also possible. All in all, project
Several attributes may be applied to assess the effects of implementation attributes result from actual network S.
project implementation. Both tangible attributes (makespan, However, they may be also directly influenced by changes in
cost etc.) and intangible attributes (influence on surrounding surrounding environment.
environment etc.) may be applied in this regard. Level of To provide necessary means for recommending project
project attributes results from attributes levels obtained for implementation and assess project implementation quality, a
individual project components. The attributes can be utilised vector function F is introduced. The function makes final
to assess the effects of the implementation of overall project recommendation of project implementation(s) possible. The
and its components. recommendation is results from a multi-level optimization
Note that clear recommendation of best project with the following goal function:
implementation involves making several decisions at once.
The decisions deal with the indication of appropriate:
• project structure;
G
0 S
min min min F S (G, Φ,Ψ ), ( )
()
• modes for the implementation of project components
which also define required resources;
where: Γ denotes a set of permissible project structures, θ0 is
• project starting date. a starting date for actual project implementation, and ω(t)
expresses the influence of surrounding environment which
III. PROJECT IMPLEMENTATION MODELLING changes in time t.
A. Princples The goal function is accompanied by a set of constraints
imposed on considered attributes of whole project and its
The application of flexible and universal means is components. Considered optimization problem belongs to the
welcome to model project implementation in a comfortable general class of multi-criteria multi-mode resource-
way. A notion of a joint directed graph (digraph) is applied, constrained project scheduling problems [2]. It is nevertheless
therefore, as a basis for description of both obligatory a peculiar and unique class instance because it considers
precedence of project components and a project structure. intangibles and unknown influence of surrounding
Note that a digraph may be expressed by a matrix. The actual environment.
application of such digraph representation facilitates project
optimization process a lot. It is visible from goal function (2) that consecutive
optimization levels deal with individual decisions. The
The digraph of predecessors Γ- and digraph of successors decisions pertain to the choice of appropriate:
Γ+ are applied to express admissible precedence of project
components. The digraphs may be expressed by • Project structure.
a corresponding binary n by n binary matrix of (project
component) predecessors Γ- and a corresponding n by n • Starting date for actual project implementation.
binary matrix of (project component) successors Γ+, • Actual modes for project components.
respectively. The matrices are strictly related to each other:
Note that higher level decisions impose considerable
restraints on permissible lower level decisions.
Goal function is intentionally given in a general form (2). permissible project structures. The first inner loop pertains to
This is because such form allows to make use of both tangible simulations of changes in surrounding environment. It
and intangible project attributes while optimizing project contains two inner loops. The outer one allows to consider
implementation. Moreover, the general nature of the goal influence of actual allocation of modes to project components
function (2) doesn’t favour use of any particular optimization on project implementation outcomes. The inner one deals
model class and opens presented framework to the wide with the influence of starting date θ0 on the outcomes. Note
family of optimization model classes. that replying of calculations for different starting dates makes
sense because of possible time-dependent changes in
B. The optimization surrounding environment.
Several challenges arise while considering the The application of each tuple consisting of considered:
optimization of project implementation. The main problems
deal with the need for: • project structure G,
• Considering all permitted project structures and • surrounding environment state ω(τ),
modes for project components. • actual mode allocations to project components,
• The use of both tangible and intangible project • starting date θ0.
attributes.
results in a network S corresponding with a distinct project
• The influence of surrounding environment. implementation. The pair-wise comparison of the attributes of
The problems impede optimization efforts. Monte Carlo such project implementation with attributes of previously
simulations were finally chosen to generate permitted project identified non-dominated project implementation(s) to check
structures, to select actual modes for project components and if it is a non-dominated in the sense of Pareto-efficiency. If
to simulate changes in surrounding environment. A notion of so, it is applied to update the set of non-dominated project
Pareto efficiency-based dominance and pair-wise implementations. nS. Note that the identification of new non-
comparisons helped to address a need for use of both tangible dominated project implementation may also require
and intangible project attributes. deepening nS update by removing project implementations
which become dominated by the newly added project
START
implementation.
Note that to obtain reliable results and facilitate
calculations core simulations should be carefully prepared.
Generating permissible Several experimental simulation runs are needed, therefore, to
project structure identify appropriate probability density models and to
indentify necessary parameters e.g. number of required core
Surrounding environement simulation runs. Particular care is indispensable with regard
state generating to the preparation of simulations of surrounding environment
Search for the best project structures
state. This is because the reliability of the framework is
extremely sensitive to any inadequacy in capturing
Allocation of modes surrounding environment state reality [3]. Multiple repetitions
in surrounding environment
to project components of optimization framework is also recommended to consider
Simulation of changes
as much possible permitable project implementations as
possible.
Starting date update
The optimization of project implementation may result in
Mode allocation
Starting date variation
one or a set of several non-dominated candidates for the
recommended project implementation. In the latter case there
Set of the best networks appears problem which dominated project implementation to
recommend for final application? Pair-wise comparisons may
nS update
prove helpful in this regard, again. The ability to consider
difference in importance of project implementation attributes
End
End
End
End
is nevertheless needed here.
NO
Loop
Loop
Loop
Loop
Loop
????
For example, a multi-attribute value theory-based
technique like Saaty’s AHP [4,5] may prove to be a relatively
YES easy to use tool. Another possibility deals with the application
of a outranking-based technique like Bran’s PROMETHEE
STOP [6]. There are also some well known strategies of
psychological origin available e.g. intuitionistic heuristic
Fig. 1. Illustration of general idea of proposed framework techniques like Tversky’s semi-lexoicogrpahic strategy and
aspect-wise elimination strategy [7,8]. Note that some
The general scheme for proposed optimization framework additional limitations imposed on main or auxiliary project
is presented in Fig.1. Four embedded loops are applied in this implementation attributes may also help a lot in the
regard. The outermost loop deals with the generation of identification of the most valuable project implementation.
To avoid pitfalls with regard to the identification of the There are also several FLOSS options available that seem
really best non-dominated project implementation alternative, suitable for the implementation of the proposed framework.
the application of sensitivity analysis is recommended. The For example example, GNU OCTAVE - a multi-platform
analysis can deal with the influence of different decision scientific programming language system available at
support tools or differences in preferences toward different https://www.gnu.org/software/octave provides necessary
project implementation attributes. means for matrix, numerical and simulation analysis.
A general two-stage framework for final recommendation Another suitable option is provided by core programming
of project implementation (Fig.2) consists of two stages languages with useful extensions. It seems that, due to
which are devoted to:
universality and rising popularity, the application of van
• The identification of non-dominated project Rossum’s Python programming language should be
implementations. recommended in this regard. Python implementations are
freely available at web page dedicated to the language:
• Final indication of the most advantageous non- https://www.python.org.
dominated project implementation.
C. Software implementation IV. CONCLUSIONS
Complexity of proposed framework makes software Contemporary projects are implemented in specific multi-
application support indispensible. Fortunately, the dimensional surrounding environment. The complexity of
development in information and communication technology interactions with surrounding environment result in a
delivers a lot of possible options available that are capable of considerable dependence of actual project implementation
facilitating software implementation of the framework. Many outcomes on actual changes in surrounding environment.
of them are freely available under free and libre open source Therefore, it is necessary to plan the implementation of
software (FLOSS) framework. For meaningful details consult contemporary projects in a way which would make them
for example the Floss for Science initiative presented at resilient to possible changes in surrounding environment as
https://flossforscience.com. much as only possible. A framework is thus presented in the
paper which is capable of recommending project
START implementation which would be resilient to changes in
surrounding environment at the highest possible level. The
framework makes use of appropriate choice of project
structure in this regard.
Data input
Besides the capability of including tangible and intangible
influence of surrounding environment changes, the main
merits of the framework cover the ability to include both
tangible and intangible effects of project implementation. The
The identifiaction
of non-dominated
framework is also capable of including different possible
project implementations uS ways for implementing project components while considering
limited availability of necessary resources. Therefore, it
seems also to be a tool that considerably improves to the
reliability of solutions of wide class of multi-criteria multi-
YES
-mode resource constrained project scheduling problems.
| nS | = 1
? Universal and comprehensive nature of proposed
framework makes it well suited for recommending reliable
project structure and a resulting schedule in different areas.
NO
Actual reliability of indispensable software implementation of
the framework heavily depends, however, on the adequacy of
Elaboration modeling influence of surrounding environment. Specific
of final project implementation implementation of the framework requires, therefore, careful
recommendation
adjustment to actual needs. Hopefully, the application of
available FLOSS tools makes it approachable.
Presentation ACKNOWLEDGMENT
of final recommendation
The authors wish to thank AGH UST for providing
financial means for the research and publication of the paper.
STOP REFERENCES
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Fig. 2. General scheme of the proposed recommendation framework optimization of the resilience of independent infrastructures under
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