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Open Access
Article
Publication date: 13 October 2022

Niklas Humble and Peter Mozelius

The conducted examination of programming affordances and constraints had the purpose of adding knowledge and value that facilitate the on-going national curricula…

Abstract

Purpose

The conducted examination of programming affordances and constraints had the purpose of adding knowledge and value that facilitate the on-going national curricula revision; knowledge that also could be of general interest outside the Swedish K-12 context.

Design/methodology/approach

With a qualitative approach, the study was conducted as a document analysis where submitted lesson plans were the base for a directed content analysis.

Findings

This study presents findings on how the involvement of programming in mathematics and technology have potential to foster engagement and motivation among students. Findings also indicate that the implementation of programming can develop important general skills that go beyond the boundaries of mathematics and technology. Moreover, the identified constraints could be valuable to improve the on-going curriculum development for K-12 mathematics and technology.

Research limitations/implications

This qualitative study was conducted on a relatively small number of teachers where the majority has taken the courses on a voluntary basis. An important complement would be to conduct a larger quantitative study with data from a more general sample of K-12 teachers.

Practical implications

Results and discussions provide guidance for K-12 teachers and other stakeholders who want to introduce programming as a complementary tool in teaching and learning activities.

Social implications

The study has a contribution to the on-going implementation of the Swedish national curricula for K-12 mathematics and technology.

Originality/value

During the last years, many studies have been published on teacher training in programming, and how the training can be improved. This study goes beyond the actual teacher training and examine aspects teachers translate to theirs daily work after completing the training.

Details

The International Journal of Information and Learning Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2056-4880

Keywords

Article
Publication date: 28 March 2008

Xavier Zwingmann, Daoud Ait‐Kadi, Amadou Coulibaly and Bernard Mutel

The purpose of this paper is to propose a framework to identify all the feasible disassembly sequences for a multi‐component product and to find an optimal disassembly…

Abstract

Purpose

The purpose of this paper is to propose a framework to identify all the feasible disassembly sequences for a multi‐component product and to find an optimal disassembly sequence, according to specific criteria such as cost, duration, profit, etc.

Design/methodology/approach

Taking into account topological and geometrical constraints of a product structure, an AND/OR disassembly graph is built. Each graph node represents a feasible subassembly. Two nodes i and j are connected by an arc (i, j), called a transition, if the subassembly j can be obtained from the subassembly i by removing one or several connectors. Constraint programming approach is used to generate the feasible subassemblies and related transitions.

Findings

If a cost zij is incurred to perform a transition (i, j), an optimal disassembly sequence can be generated for a given subassembly, using the shortest path algorithm or a linear programming model.

Research limitations/implications

The proposed approach performs very well compared to other approaches published in the literature, even when applied to products requiring parallel disassembly and including a large number of parts.

Practical implications

This approach has been successfully applied to assess the wheelchair maintainability at the design stage and will be implemented in CAD systems. One other application, regarding the disassembly process and total revenue maximization for product recycling, is now under consideration.

Originality/value

Applying constraint programming to efficiently generate the set of the feasible subassemblies constitutes the main contribution in this paper. This process is the hardest step in the disassembly sequencing problem.

Details

Journal of Quality in Maintenance Engineering, vol. 14 no. 1
Type: Research Article
ISSN: 1355-2511

Keywords

Article
Publication date: 8 June 2010

Hadi Sadoghi Yazdi, Reza Pourreza and Mehri Sadoghi Yazdi

The purpose of this paper is to present a new method for solving parametric programming problems; a new scheme of constraints fuzzification. In the proposed approach…

Abstract

Purpose

The purpose of this paper is to present a new method for solving parametric programming problems; a new scheme of constraints fuzzification. In the proposed approach, constraints are learned based on deductive learning.

Design/methodology/approach

Adaptive neural‐fuzzy inference system (ANFIS) is used for constraint learning by generating input and output membership functions and suitable fuzzy rules.

Findings

The experimental results show the ability of the proposed approach to model the set of constraints and solve parametric programming. Some notes in the proposed method are clustering of similar constraints, constraints generalization and converting crisp set of constraints to a trained system with fuzzy output. Finally, this idea for modeling of constraint in the support vector machine (SVM) classifier is used and shows that this approach can obtain a soft margin in the SVM.

Originality/value

Properties of the new scheme such as global view of constraints, constraints generalization, clustering of similar constraints, creation of real fuzzy constraints, study of constraint strength and increasing the degree of importance to constraints are different aspects of the proposed method.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 3 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 1 June 2021

Srikant Gupta, Sachin Chaudhary, Prasenjit Chatterjee and Morteza Yazdani

Logistics is the part of the supply chain (SC) that plans, executes and handles forward and reverse movement and storage of products, services and related information, in…

Abstract

Purpose

Logistics is the part of the supply chain (SC) that plans, executes and handles forward and reverse movement and storage of products, services and related information, in order to respond to customers' needs effectively and efficiently. The main concern for logistics is to ensure that the correct product is placed at the right time. This paper introduces a linear model of shipping focused on decision-making, which includes configuration of shipping network, choosing of transport means and transfer of individual customer shipments through a particular transport system.

Design/methodology/approach

In this study, authors try to address the problem of supply chain network (SCN) where the primary goal is to determine the appropriate order allocation of products from different sources to different destinations. They also seek to minimize total transportation cost and inventory cost by simultaneously determining optimal locations, flows and shipment composition. The formulated problem of getting optimal allocation turns out to be a problem of multi-objective programming, and it is solved by using the max-addition fuzzy goal programming approach, for obtaining optimal order allocation of products. Furthermore, the problem demand and supply parameters have been considered random in nature, and the maximum likelihood estimation approach has been used to assess the unknown probabilistic distribution parameters with a specified probability level (SPL).

Findings

A case study has also been applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. Results of this study are very relevant for the manufacturing sector in particular, for those facing logistics issues in SCN. It enables researchers and managers to cope with various types of uncertainty and logistics risks associated with SCN.

Research limitations/implications

The principal contribution of the proposed model is the improved modelling of transportation and inventory, which are affected by different characteristics of SCN. To demonstrate computational information of the suggested methods and proposed model, a case illustration of SCN is provided. Also, environmentalism is increasingly becoming a significant global concern. Hence, the concept proposed could be extended to include environmental aspects as an objective function or constraint.

Originality/value

Efficient integration of logistical cost components, such as transportation costs, inventory costs, with mathematical programming models is an important open issue in logistics optimization. This study expands conventional facility location models to incorporate a range of logistic system elements such as transportation cost and different types of inventory cost, in a multi-product, multi-site network. The research is original and is focused on case studies of real life.

Open Access
Article
Publication date: 16 October 2017

Pawel Sitek, Jaroslaw Wikarek and Peter Nielsen

The purpose of this paper is the need to build a novel approach that would allow flexible modeling and solving of food supply chain management (FSCM) problems. The models…

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Abstract

Purpose

The purpose of this paper is the need to build a novel approach that would allow flexible modeling and solving of food supply chain management (FSCM) problems. The models developed would use the data (data-driven modeling) as early as possible at the modeling phase, which would lead to a better and more realistic representation of the problems being modeled.

Design/methodology/approach

An essential feature of the presented approach is its declarativeness. The use of a declarative approach that additionally includes constraint satisfaction problems and provides an opportunity of fast and easy modeling of constrains different in type and character. Implementation of the proposed approach was performed with the use of an original hybrid method in which constraint logic programming (CLP) and mathematical programming (MP) are integrated and transformation of a model is used as a presolving technique.

Findings

The proposed constraint-driven approach has proved to be extremely flexible and efficient. The findings obtained during part of experiments dedicated to efficiency were very interesting. The use of the constraint-driven approach has enabled finding a solution depending on the instance data up to 1,000 times faster than using the MP.

Research limitations/implications

Due to the limited use of exact methods for NP-hard problems, the future study should be to integrate the CLP with environments other than the MP. It is also possible, e.g., with metaheuristics like genetic algorithms, ant colony optimization, etc.

Practical implications

There is a possibility of using the approach as a basis to build a decision support system for FSCM, simple integration with databases, enterprise resource planning systems, management information systems, etc.

Originality/value

The new constraint-driven approach to FSCM has been proposed. The proposed approach is an extension of the hybrid approach. Also, a new decision-making model of distribution and logistics for the food supply chain is built. A presolving technique for this model has been presented.

Article
Publication date: 15 July 2020

Abdessamed Mogtit, Noureddine Aribi, Yahia Lebbah and Mohand Lagha

Airspace sectorization is an important task, which has a significant impact in the everyday work of air control services. Especially in recent years, because of the…

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Abstract

Purpose

Airspace sectorization is an important task, which has a significant impact in the everyday work of air control services. Especially in recent years, because of the constant increase in air traffic, existing airspace sectorization techniques have difficulties to tackle the large air traffic volumes, creating imbalanced sectors and uneven workload distribution among sectors. The purpose of this paper is to propose a new approach to find optimal airspace sectorization balancing the traffic controller workload between sectors, subject to airspace requirements.

Design/methodology/approach

A constraint programming (CP) model called equitable airspace sectorization problem (EQASP) relies on ordered weighted averaging (OWA) multiagent optimization and the parallel portfolio architecture has been developed, which integrates the equity into an existing CP approach (Trandac et al., 2005). The EQASP was evaluated and compared with the method of Trandac et al. (2005), according to the quality of workload balancing between sectors and the resolution performance. The comparison was achieved using real air traffic low-altitude network data sets of French airspace for five flight information regions for 24 h a day and the Algerian airspace for three various periods (off peak hours, peak hours and 24 h).

Findings

It has been demonstrated that the proposed EQASP model, which is based on OWA multicriteria optimization method, significantly improved both the solving performance and the workload equity between sectors, while offering strong theoretical properties of the balancing requirement. Interestingly, when solving hard instances, our parallel sectorization tool can provide, at any time, a workable solution, which satisfies all geometric constraints of sectorization.

Practical implications

This study can be used to design well-balanced air sectors in terms of workload between control units in the strategic phase. To fulfil the airspace users’ constraints, one can refer to this study to assess the capacity of each air sector (especially the overloaded sectors) and then adjust the sector’s shape to respond to the dynamic changes in traffic patterns.

Social implications

This theoretical and practical approach enables the development and support of the definition of the “Air traffic management (ATM) Concept Target” through improvements in human factors specifically (balancing workload across sectors), which contributes to raising the level of capacity, safety and efficiency (SESAR Vision of ATM 2035).

Originality/value

In their approach, the authors proposed an OWA-based multiagent optimization model, ensuring the search for the best equitable solution, without requiring user-defined balancing constraints, which enforce each sector to have a workload between two user-defined bounds (Wmin, Wmax).

Details

Aircraft Engineering and Aerospace Technology, vol. 92 no. 8
Type: Research Article
ISSN: 1748-8842

Keywords

Book part
Publication date: 6 November 2013

Ronald K. Klimberg, George P. Sillup, Kevin J. Boyle and Alyssa Beck

A common problem that many universities face, especially with their specialized programs, is coordinating faculty availability and class offerings. The schedule is usually…

Abstract

A common problem that many universities face, especially with their specialized programs, is coordinating faculty availability and class offerings. The schedule is usually developed using paper and pencil after numerous iterations. As a result, the objectives of the program, such as course integration, length of course, and student workload, are most likely compromised in lieu of faculty availability. This chapter describes a multiple objective approach to this class assignment problem that considers the program’s objectives and faculty preferences. The results of applying this class assignment model to an Executive MBA (EMBA) program are presented.

Article
Publication date: 18 June 2021

R. Ghasemy Yaghin and P. Sarlak

This paper studies the textile supply chain tactical planning under demand fuzziness through considering environmentally friendly and social responsibility. Hence, carbon…

Abstract

Purpose

This paper studies the textile supply chain tactical planning under demand fuzziness through considering environmentally friendly and social responsibility. Hence, carbon emission in textile production and transportation is considered along with supply chain profitability.

Design/methodology/approach

The authors present a fuzzy multi-objective mathematical optimization model with credibilistic chance constraints to determine the fabric procurement quantities and production plan under uncertainty. The solution procedure makes use of credibility measure and fuzzy aggregation operator to attain compromise solutions.

Findings

A trade-off among carbon emissions, social performance and supply chain total profit is conducted. The analyses indicate the importance of transportation costs and carbon emission while determining the supply chain's tactical plan.

Originality/value

The textile supply chain's social sustainability alongside carbon emissions of textile operations is contemplated to provide apparel production and distribution logistics planning under uncertainty. In doing so, the authors propose a hybrid credibility-possibility mathematical optimization model to determine a compromise solution for textile managers.

Details

International Journal of Clothing Science and Technology, vol. 34 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 7 April 2021

Emre Cevikcan and Yildiz Kose

An appropriate space allocation among different residence types gives higher profitability and liquidity for cash flow management in real estate projects for developers…

Abstract

Purpose

An appropriate space allocation among different residence types gives higher profitability and liquidity for cash flow management in real estate projects for developers. Thereby, a balance between debt and equity should be kept for capital formation in developers where high level of cost, profit and risk exists. The purpose of this paper is to provide cash flow optimization under debt and equity financing while providing an appropriate space allocation of residence types via synchronous consideration of profitability and liquidity.

Design/methodology/approach

A novel optimization methodology that includes project financing, optimization and experimental design modules is proposed. The first module, project financing, considers the flexibility of utilizing one or both of debt financing and equity financing when making capital. The optimization module addresses space allocation among different residence types for a construction while maximizing profitability and liquidity using two mixed-integer linear programming models in a pre-emptive manner. The experimental design module assesses the effects of decisive parameters within the methodology via multivariate analysis of variance (MANOVA).

Findings

The proposed methodology is applied to a real-life residential project in Istanbul. The optimization module yielded 42.5% profitability via the first linear programming model and 2.2% trade-off between liquidity and profitability while minimizing the payback period by the second linear programming model. Meanwhile, MANOVA results showed that profit per square meter and sale rate trends are the most prominent factors considering their significant effects on net present value and payback period.

Originality/value

To the best knowledge of the author, related papers focused only on profitability under equity financing. Liquidity (as an objective) and equity financing (as a financing method) have not been handled. Hence, this paper not only performs profitability and liquidity-oriented cash flow optimization under debt and equity financing but also optimizes space allocation of residences for the first time.

Details

Built Environment Project and Asset Management, vol. 11 no. 2
Type: Research Article
ISSN: 2044-124X

Keywords

Article
Publication date: 11 November 2019

Marimuthu Kannimuthu, Benny Raphael, Palaneeswaran Ekambaram and Ananthanarayanan Kuppuswamy

Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an…

Abstract

Purpose

Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint).

Design/methodology/approach

A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India.

Findings

Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution.

Research limitations/implications

It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified.

Originality/value

An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 4
Type: Research Article
ISSN: 0969-9988

Keywords

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