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1

Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems

100%
Ławrynowicz A.
Foundations of Management
|
2011
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vol. 3
|
issue 2
7-26
EN
Scheduling manufacturing operations is a complicated decision making process. From the computational point of view, the scheduling problem is one of the most notoriously intractable NP-hard optimization problems. When the manufacturing system is not too large, the traditional methods for solving scheduling problem proposed in the literature are able to obtain the optimal solution within reasonable time. But its implementation would not be easy with conventional information systems. Therefore, many researchers have proposed methods with genetic algorithms to support scheduling in the manufacturing system. The genetic algorithm belongs to the category of artificial intelligence. It is a very effective algorithm to search for optimal or near-optimal solutions for an optimization problem. This paper contains a survey of recent developments in building genetic algorithms for the advanced scheduling. In addition, the author proposes a new approach to the distributed scheduling in industrial clusters which uses a modified genetic algorithm.
2

Abductive Reasoning Driven Approach to Project - Like Production Flow Prototyping

100%
Bocewicz G., Banaszak Z.
Foundations of Management
|
2009
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vol. 1
|
issue 1
43-62
EN
Constraint Programming (CP) is an emergent software technology for declarative description and effective solving of large combinatorial problems especially in the area of integrated production planning. In that context, CP can be considered as an appropriate framework for development of decision making software supporting scheduling of multi-robot in a multi-product job shop. The paper deals with multi-resource problem in which more than one shared renewable and non-renewable resource type may be required by manufacturing operation and the availability of each type is time-windows limited. The problem belongs to a class of NP-complete ones. The aim of the paper is to present a knowledge based and CLP-driven approach to multi-robot task allocation providing a prompt service to a set of routine queries stated both in straight and reverse way. Provided examples illustrate both cases while taking into account an accurate as well as an uncertain specification of robots and workers operation time.
3
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A Genetic Algorithm to Minimize the Total Tardiness for M-Machine Permutation Flowshop Problems

100%
Chung C.-S., Flynn J., Rom W., Staliński P.
Journal of Entrepreneurship, Management and Innovation
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2012
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vol. 8
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issue 2
26-43
EN
The m-machine, n-job, permutation flowshop problem with the total tardiness objective is a common scheduling problem, known to be NP-hard. Branch and bound, the usual approach to finding an optimal solution, experiences difficulty when n exceeds 20. Here, we develop a genetic algorithm, GA, which can handle problems with larger n. We also undertake a numerical study comparing GA with an optimal branch and bound algorithm, and various heuristic algorithms including the well known NEH algorithm and a local search heuristic LH. Extensive computational experiments indicate that LH is an effective heuristic and GA can produce noticeable improvements over LH.
4

Cost Optimal Project Scheduling

88%
Klanšek U., Pšunder M.
Organizacija
|
2008
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vol. 41
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issue 4
153-158
EN
This paper presents the cost optimal project scheduling. The optimization was performed by the nonlinear programming approach, NLP. The nonlinear total project cost objective function is subjected to the rigorous system of the activity precedence relationship constraints, the activity duration constraints and the project duration constraints. The set of activity precedence relationship constraints was defined to comprise Finish-to-Start, Start-to-Start, Start-to-Finish and Finish-to-Finish precedence relationships between activities. The activity duration constraints determine relationships between minimum, maximum and possible duration of the project activities. The project duration constraints define the maximum feasible project duration. A numerical example is presented at the end of the paper in order to present the applicability of the proposed approach.
5

Declarative Modeling for Production Order Portfolio Scheduling

88%
Banaszak Z., Bocewicz G.
Foundations of Management
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2014
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vol. 6
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issue 3
7-24
EN
A declarative framework enabling to determine conditions as well as to develop decision-making software supporting small- and medium-sized enterprises aimed at unique, multi-project-like and mass customized oriented production is discussed. A set of unique production orders grouped into portfolio orders is considered. Operations executed along different production orders share available resources following a mutual exclusion protocol. A unique product or production batch is completed while following a given activity’s network order. The problem concerns scheduling a newly inserted project portfolio subject to constraints imposed by a multi-project environment The answers sought are: Can a given project portfolio specified by its cost and completion time be completed within the assumed time period in a manufacturing system in hand? Which manufacturing system capability guarantees the completion of a given project portfolio ordered under assumed cost and time constraints? The considered problems regard finding a computationally effective approach aimed at simultaneous routing and allocation as well as batching and scheduling of a newly ordered project portfolio subject to constraints imposed by a multi-project environment. 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 production scheduling. Multiple illustrative examples are discussed.
6
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Multi-criteria human resources planning optimisation using genetic algorithms enhanced with MCDA

88%
Jurczak M., Miebs G., Bachorz R. A.
Operations Research and Decisions
|
2022
|
vol. 32
|
issue 4
EN
The main objective of this paper is to present an example of the IT system implementation with advanced mathematical optimisation for job scheduling. The proposed genetic procedure leads to the Pareto front, and the application of the multiple criteria decision aiding (MCDA) approach allows extraction of the final solution. Definition of the key performance indicator (KPI), reflecting relevant features of the solutions, and the efficiency of the genetic procedure provide the Pareto front comprising the representative set of feasible solutions. The application of chosen MCDA, namely elimination et choix traduisant la réalité (ELECTRE) method, allows for the elicitation of the decision maker (DM) preferences and subsequently leads to the final solution. This solution fulfils all of the DM expectations and constitutes the best trade-off between considered KPIs. The proposed method is an efficient combination of genetic optimisation and the MCDA method.
7

Project Realization Scheduling and its Multi Criteria Evaluation

75%
Witkowski T., Antczak P., Antczak A.
Foundations of Management
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2009
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vol. 1
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issue 2
25-44
EN
The paper focuses on project scheduling classification issues according to the type of constraints and optimization directions. Special attention was paid to production scheduling, presenting the basic issues in relation with product flow organizational criterion. Open-cluster issue was formulated and analyzed with the use of modern heuristics. Solution was evaluated with multiple criteria, mainly on the basis of time characteristics. Production process flow relations, in coordinates determined by operation sequence at particular workplaces, as well as the production type factor were presented.
8
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Method of planning construction projects, taking into account risk factors

75%
SKORUPKA D.
Operations Research and Decisions
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2009
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vol. 19
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issue 3
119-128
EN
This paper presents an original method of planning construction projects, taking into account the influence of potential risk factors. The method is called the Method of Construction Risk Assessment (MOCRA). According to this method, first the material-financial plan of a project (a construction project in the example provided) is analyzed. Then risk factors are identified, taking into account the project’s specificity. The end result of this stage is a list of risk factors. In the third stage the risk is reduced or minimized where possible. Finally, the specified risk factors are quantified, which is a difficult task. The effectiveness of the risk assessment depends on how thoroughly this task is carried out. Since point scale assessment of risk does not appeal to engineers, in MOCRA quantified risk is allocated in the material-financial plan. Thanks to this, one can prepare contingency plans, i.e. plans (action variants) to be implemented when particular risk factors occur. Having completed the project, one can use MOCRA to check the accuracy of the assessment (forecast) and select the best contingency action variant, whereby the method’s effectiveness in planning future projects is improved.
PL
W artykule przedstawiono autorską metodę planowania przedsięwzięć budowlanych z możliwością uwzględniania wpływu potencjalnych czynników ryzyka. Metoda nosi nazwę MOCRA (Method of Construction Risk Assessment). W pierwszym etapie proponowanej metody przeprowadza się analizę planu rzeczowo-finansowego przedsięwzięcia (w przedstawionym przykładzie jest to przedsięwzięcie budowlane). Następnie, biorąc pod uwagę specyfikę wykonywanego obiektu, dokonuje się identyfikacji czynników ryzyka. Ten element analizy jest jednocześnie drugim etapem metody MOCRA, którego finalny efekt sprowadza się do opracowania zestawienia – listy czynników ryzyka. Etap trzeci polega na redukcji lub zminimalizowaniu ryzyka tam, gdzie jest to możliwe. W kolejnym etapie dokonuje się kwantyfikacji wyspecyfikowanych czynników ryzyka. Etap ten jest trudny, ale od rzetelności jego wykonania zależy w dużym stopniu efektywność oceny ryzyka. Ocena punktowa ryzyka nie trafia do wyobraźni inżynierów, dlatego w metodzie MOCRA dokonuje się alokacji skwantyfikowanego ryzyka w planie rzeczowo-finansowym. Konsekwencją takiego działania jest możliwość budowy planów awaryjnych, czyli planów realizowanych na wypadek wystąpienia poszczególnych czynników ryzyka. Taki plan awaryjny można traktować jako wariant działania. Po zrealizowaniu inwestycji istnieje możliwość, na bazie metody MOCRA, określenia trafności oceny (prognozy) i wybrania najlepszego wariantu awaryjnego, co poprawia skuteczność metody w planowaniu kolejnych przedsięwzięć. Biorąc pod uwagę aspekt utylitarny metody, przedstawiono przykład jej zastosowania w planowaniu realizacji przedsięwzięcia budowlanego, którego wykonawcą była średnia firma budowlana. Podsumowując, przedstawiona metoda nie może być traktowana jako „magiczna skrzynka”, która rozwiązuje wszystkie problemy predykcji potencjalnych zagrożeń oraz ich wpływu na realizację inwestycji. Można jednak traktować ją jako narzędzie wspomagające proces decyzyjny, związany z planowaniem realizacji przedsięwzięcia budowlanego.
9
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Zarządzanie czasem w projekcie z uwzględnieniem ryzyka

63%
Zoła M.
Organizacja i Zarządzanie : kwartalnik naukowy
|
2014
|
vol. nr 2
153--166
EN
The article presents an overview of the development of the methods for analysing and managing risk involved in the realisation of the project schedule. Classic approaches were described as well as recent trends in the field, both in scientific research and business practice. The paper also enumerates the limitations of these methods and makes remarks on their practical implementation in project management.
PL
W pracy przedstawiono zarys rozwoju metod, pozwalających na analizę i zarządzanie ryzykiem związanym z realizacją harmonogramu projektu. Opisano klasyczne podejścia, jak również najnowsze trendy w tej dziedzinie, pojawiające się zarówno w badaniach naukowych, jak i praktyce biznesowej. Zostały także wskazane ograniczenia tych metod oraz obserwacje, dotyczące ich praktycznej implementacji w zarządzaniu projektami.
10
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Optimization of Complex Operations in the Supply Chain Through the Implementation of Advanced Planning System

63%
Rut J., Kulińska E.
Logistics and Transport
|
2018
|
vol. 40
91-96
EN
Contemporary variability of the environment and market dynamics force enterprises to optimize operations in the supply chain. Advanced IT systems such as the Advanced Planning System are a powerful tool that supports many areas in supply chain management. An efficient supply chain is a key element in gaining a competitive advantage in the market. Therefore, the foundation of the material and information flow regulation in manufacturing enterprises is the efficient exchange of information with both the internal and external environment of the organization. The article presents the optimization process of complex operations taking place in the supply chain by implementing the Advanced Planning System in the examined enterprise. It also enumerates significant benefits resulting from the implementation.
11
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Generowanie struktur harmonogramuz jednoczesnym rozwiązywaniem zadańpoziomu dolnego różnymi metodami

51%
Mirosław Dytczak M.
Zeszyty Naukowe Wyższej Szkoły Bankowej we Wrocławiu
|
2013
|
issue 2(34)
115-129
PL
W artykule rozważono zagadnienie identyfikacji najbardziej korzystnego uporządkowania operacji technologicznych przedsięwzięcia budowlanego. Problem jest trudny do rozwiązania z uwagi na zwykle bardzo dużą liczbę dopuszczalnych uporządkowań operacji. Przedstawiono też wielokryterialny model wykorzystujący wybrane dopuszczalne uporządkowania operacji przedsięwzięcia pozwalający na rozwiązanie tego zagadnienia. Do identyfikacji optymalnego z uwagi na czas i koszt realizacji przedsięwzięcia uporządkowania operacji wykorzystuje się dwuetapowe podejście. W pierwszym etapie są generowane dopuszczalne uporządkowania technologicznych operacji przedsięwzięcia przy wykorzystaniu symulacji Monte Carlo oraz algorytmów ewolucyjnych. Drugi etap służy przydzieleniu odpowiednich sposobów wykonania poszczególnym operacjom. Uwzględnia się przy tym ograniczoną dostępność zasobów odnawialnych w postaci zestawów środków technicznych niezbędnych do wykonania operacji poszczególnymi sposobami. Do optymalizacji wykorzystuje się programowanie liniowe (podejście MC-PL) oraz losowe przydziały sposobów wykonania operacji (podejście MC-MC). Zastosowane metody optymalizacji uzupełniają się, ponieważ pierwsza okazuje się bardziej skuteczna w przypadku przedsięwzięć o mniejszych, druga zaś – o większych rozmiarach.
EN
The problem of identification of the most beneficial order of technological operations of a complex construction project is dealt with in the paper. The problem is hard to solve because of a large number of feasible orders. A special approach is proposed to effectively solve the matter in question. The approach applies multi-criteria optimisation to project realisation based on selected feasible orders of operations. The paper proposes a two-step approach to determine the best, in terms of project execution time and cost, schedule of the project. Simulation is utilised in the first stage to determine feasible orders of project operations. Monte Carlo simulations and evolutionary algorithms are applied for generating of the operation orders. The second stage is devoted to identification of the best ways to perform different technological project operations, taking into account limited availability of required renewable resources – sets of technical measures. Different methods are applied with this regard. The MC-LP and MC-AE methods concern linear programming to allocate execution modes to operations, while MC-MC applies a random assignment with this regard. Utilised optimisation methods are complementary as they allow to identify optimal assignments of execution modes to project operations for both less and more complex construction projects.
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