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Article
Publication date: 5 July 2022

Ammar Kassab, Rosmini Omar and Hasan Ghura

Governments can influence entrepreneurial growth through public policy. This paper aims to present critical aspects of entrepreneurship policy design for Syrian refugees in Turkey…

249

Abstract

Purpose

Governments can influence entrepreneurial growth through public policy. This paper aims to present critical aspects of entrepreneurship policy design for Syrian refugees in Turkey and evaluate if current policies are effective for Syrian refugees in Istanbul.

Design/methodology/approach

The study adopts an explorative phenomenological approach, contextualized within the entrepreneurial behavior literature. The data was collected through semi-structured interviews with fifteen Syrian entrepreneurs residing in Istanbul.

Findings

The results show that Syrian refugees were “pushed” to start new companies. Moreover, the findings suggest that Syrian entrepreneurs could exploit better business opportunities such as targeting international markets or finding competent partners.

Research limitations/implications

The article offers several practical and social contributions by highlighting how the entrepreneurial behavior of Syrian refugees is driven by their migration or business experiences.

Practical implications

Policymakers in Turkey need to acknowledge how their entrepreneurial policies regarding innovation and internationalization affect the business success rate among Syrian refugees. In this regard, the Turkish government should adopt new measures that provide Syrian refugees more business flexibility. These policies may include easy access to the Turkish financial system or fewer regulations to obtain work permits. This will encourage refugees to join the formal economy and contribute to the Turkish labor market.

Originality/value

This article adds to the expanding body of knowledge on refugee entrepreneurship by emphasizing the link between refugees' personal experiences and starting new ventures. It also highlights how government policy can be strategically utilized to increase entrepreneurship among Syrian refugees in Turkey.

Details

Journal of Entrepreneurship and Public Policy, vol. 11 no. 2/3
Type: Research Article
ISSN: 2045-2101

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Article
Publication date: 16 May 2016

Emad Elbeltagi, Mohammed Ammar, Haytham Sanad and Moustafa Kassab

Developing an optimized project schedule that considers all decision criteria represents a challenge for project managers. The purpose of this paper is to provide a…

1912

Abstract

Purpose

Developing an optimized project schedule that considers all decision criteria represents a challenge for project managers. The purpose of this paper is to provide a multi-objectives overall optimization model for project scheduling considering time, cost, resources, and cash flow. This development aims to overcome the limitations of optimizing each objective at once resulting of non-overall optimized schedule.

Design/methodology/approach

In this paper, a multi-objectives overall optimization model for project scheduling is developed using particle swarm optimization with a new evolutionary strategy based on the compromise solution of the Pareto-front. This model optimizes the most important decisions that affect a given project including: time, cost, resources, and cash flow. The study assumes each activity has different execution methods accompanied by different time, cost, cost distribution pattern, and multiple resource utilization schemes.

Findings

Applying the developed model to schedule a real-life case study project proves that the proposed model is valid in modeling real-life construction projects and gives important results for schedulers and project managers. The proposed model is expected to help construction managers and decision makers in successfully completing the project on time and reduced budget by utilizing the available information and resources.

Originality/value

The paper presented a novel model that has four main characteristics: it produces an optimized schedule considering time, cost, resources, and cash flow simultaneously; it incorporates a powerful particle swarm optimization technique to search for the optimum schedule; it applies multi-objectives optimization rather than single-objective and it uses a unique Pareto-compromise solution to drive the fitness calculations of the evolutionary process.

Details

Engineering, Construction and Architectural Management, vol. 23 no. 3
Type: Research Article
ISSN: 0969-9988

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Expert briefing
Publication date: 28 April 2015

The loss is the most significant defeat suffered by the regime in recent months, following the fall of the provincial capital, Idlib, in late March and Nasib, the last regime-held…

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DOI: 10.1108/OXAN-DB199215

ISSN: 2633-304X

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Article
Publication date: 16 May 2016

Timo Hartmann

374

Abstract

Details

Engineering, Construction and Architectural Management, vol. 23 no. 3
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 4 July 2018

Sameh El-Sayegh

The purpose of this paper is to propose a Non-Linear Integer Programming (NLIP) model that solves the resource leveling problem while reducing the negative effect of the total…

621

Abstract

Purpose

The purpose of this paper is to propose a Non-Linear Integer Programming (NLIP) model that solves the resource leveling problem while reducing the negative effect of the total float loss on risk.

Design/methodology/approach

An NLIP model is formulated to solve the resource leveling optimization problem incorporating float loss cost (FLC). The proposed model is implemented using “What’s Best solver” for Excel. The FLC is calculated using the float commodity approach. An example is solved using the proposed model in order to illustrate its applicability. Sensitivity analysis is also performed.

Findings

The results confirmed that resource leveling reduces the available float of non-critical activities; decreases schedule flexibility and reduces the probability of project completion. The probability of timely completion dropped from 50 percent (for the normal schedule with 32 resource fluctuations) to 13.5 percent for leveled resources with zero fluctuations. Using the proposed method, the number of resource fluctuations is 8 but the probability of completing the project on time improved to 20 percent.

Practical implications

The proposed model allows project managers to exercise new trade-offs between resource leveling and schedule flexibility which will ultimately improve the chances of successful project delivery.

Originality/value

Resource leveling techniques result in reducing the available total float for the non-critical activities. Existing methods focus on moving noncritical activities within their available float and ignore the impact of the resulting float loss. This reduces the schedule flexibility and increase the risk of project delays. The proposed model incorporates the FLC into the resource leveling optimization problem resulting in more efficient schedules with improved resource utilization while keeping some schedule flexibility.

Details

Engineering, Construction and Architectural Management, vol. 25 no. 5
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 3 July 2017

Domenico Borzacchiello, Jose Vicente Aguado and Francisco Chinesta

The purpose of this paper is to present a reduced order computational strategy for a multi-physics simulation involving a fluid flow, electromagnetism and heat transfer in a…

95

Abstract

Purpose

The purpose of this paper is to present a reduced order computational strategy for a multi-physics simulation involving a fluid flow, electromagnetism and heat transfer in a hot-wall chemical vapour deposition reactor. The main goal is to produce a multi-parametric solution for fast exploration of the design space to perform numerical prototyping and process optimisation.

Design/methodology/approach

Different reduced order techniques are applied. In particular, proper generalized decomposition is used to solve the parameterised heat transfer equation in a five-dimensional space.

Findings

The solution of the state problem is provided in a compact separated-variable format allowing a fast evaluation of the process-specific quantities of interest that are involved in the optimisation algorithm. This is completely decoupled from the solution of the underlying state problem. Therefore, once the whole parameterised solution is known, the evaluation of the objective function is done on-the-fly.

Originality/value

Reduced order modelling is applied to solve a multi-parametric multi-physics problem and generate a fast estimator needed for preliminary process optimisation. Different order reduction techniques are combined to treat the flow, heat transfer and electromagnetism problems in the framework of separated-variable representations.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 27 no. 7
Type: Research Article
ISSN: 0961-5539

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Article
Publication date: 19 September 2024

Mohammad Azim Eirgash and Vedat Toğan

Most of the existing time-cost-quality-environmental impact trade-off (TCQET) analysis models have focused on solving a simple project representation without taking typical…

60

Abstract

Purpose

Most of the existing time-cost-quality-environmental impact trade-off (TCQET) analysis models have focused on solving a simple project representation without taking typical activity and project characteristics into account. This study aims to present a novel approach called the “hybrid opposition learning-based Aquila Optimizer” (HOLAO) for optimizing TCQET decisions in generalized construction projects.

Design/methodology/approach

In this paper, a HOLAO algorithm is designed, incorporating the quasi-opposition-based learning (QOBL) and quasi-reflection-based learning (QRBL) strategies in the initial population and generation jumping phases, respectively. The crowded distance rank (CDR) mechanism is utilized to rank the optimal Pareto-front solutions to assist decision-makers (DMs) in achieving a single compromise solution.

Findings

The efficacy of the proposed methodology is evaluated by examining TCQET problems, involving 69 and 290 activities, respectively. Results indicate that the HOLAO provides competitive solutions for TCQET problems in construction projects. It is observed that the algorithm surpasses multiple objective social group optimization (MOSGO), plain Aquila Optimization (AO), QRBL and QOBL algorithms in terms of both number of function evaluations (NFE) and hypervolume (HV) indicator.

Originality/value

This paper introduces a novel concept called hybrid opposition-based learning (HOL), which incorporates two opposition strategies: QOBL as an explorative opposition and QRBL as an exploitative opposition. Achieving an effective balance between exploration and exploitation is crucial for the success of any algorithm. To this end, QOBL and QRBL are developed to ensure a proper equilibrium between the exploration and exploitation phases of the basic AO algorithm. The third contribution is to provide TCQET resource utilizations (construction plans) to evaluate the impact of these resources on the construction project performance.

Details

Engineering Computations, vol. 41 no. 8/9
Type: Research Article
ISSN: 0264-4401

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Article
Publication date: 17 April 2020

Duc Hoc Tran

Project managers work to ensure successful project completion within the shortest period and at the lowest cost. One of the main tasks of a project manager in the planning phase…

540

Abstract

Purpose

Project managers work to ensure successful project completion within the shortest period and at the lowest cost. One of the main tasks of a project manager in the planning phase is to generate the project time–cost curve, and furthermore, to determine the most appropriate schedule for the construction process. Numerous existing time–cost tradeoff analysis models have focused on solving a simple project representation without regarding for typical activity and project characteristics. This study aims to present a novel approach called “multiple-objective social group optimization” (MOSGO) for optimizing time–cost decisions in generalized construction projects.

Design/methodology/approach

In this paper, a novel MOGSO to mimic the time–cost tradeoff problem in generalized construction projects is proposed. The MOSGO has slightly modified the mechanism operation from the original algorithm to be a free-parameter algorithm and to enhance the exploring and exploiting balance in an optimization algorithm. The evidential reasoning technique is used to rank the global optimal obtained non-dominated solutions to help decision makers reach a single compromise solution.

Findings

Two case studies of real construction projects were investigated and the performance of MOSGO was compared to those of widely considered multiple-objective evolutionary algorithms. The comparison results indicated that the MOSGO approach is a powerful, efficient and effective tool in finding the time–cost curve. In addition, the multi-criteria decision-making approaches were applied to identify the best schedule for project implementation.

Research limitations/implications

Accordingly, the first major practical contribution of the present research is that it provides a tool for handling real-world construction projects by considering all types of construction project. The second important implication of this study derives from research finding on the hybridization multiple-objective and multi-criteria techniques to help project managers in facilitating the time–cost tradeoff (TCT) problems easily. The third implication stems from the wide-range application of the proposed model TCT.

Practical implications

The model can be used in early stages of the construction process to help project managers in selecting an appropriate plan for whole project lifecycle.

Social implications

The proposal model can be applied to multi-objective contexts in diversified fields. Moreover, the model is also a useful reference for future research.

Originality/value

This paper makes contributions to extant literature by: introducing a method for making TCT models applicable to actual projects by considering general activity precedence relations; developing a novel MOSGO algorithm to solving TCT problems in multi-objective context by a single simulation; and facilitating the TCT problems to project managers by using multi-criteria decision-making approaches.

Details

Engineering, Construction and Architectural Management, vol. 27 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

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Article
Publication date: 1 February 2022

Chijoo Lee

Work crew productivity and the application of limited resources are necessary elements in construction duration delay analysis. This study thus proposes a method to analyze…

274

Abstract

Purpose

Work crew productivity and the application of limited resources are necessary elements in construction duration delay analysis. This study thus proposes a method to analyze construction delays and resource reallocation based on work crew productivity and resource constraints. The study also presents an economic feasibility analysis that maximizes economic effect by reducing construction duration, the cost of resource reallocation, delay liquidated damages (DLDs) and incentives for reducing contractual duration.

Design/methodology/approach

The proposed method involved three steps. First, work crew characteristics such as productivity, unit price and workload helped analyze delay information, including delay duration, reducible duration and daily reduced cost. Next, a goal programming method assessed resource reallocation based on the priority (as determined by decision-makers) of each constraint condition, such as the available number of workers, cost, goal workload and statutory working hours. Lastly, the level of reallocation was analyzed based on the results of the economic feasibility analysis and decision-makers’ delay attitudes.

Findings

A case study was performed to test the proposed method's applicability. Its involved sensitivity analysis indicated proposing to decision-makers a scenario based on the prioritization of economic feasibility. The proposed method's applicability proved high for decision-makers, as they can determine whether to reduce construction duration per the proposed data.

Originality/value

The proposed method's main contribution is the reallocation of resources to reduce construction duration based on work crew productivity and the prioritization of limited resources. The proposed method can analyze the differences in productivity between the plan and actual progress, as well as calculate the necessary number of workers. Decision-makers can then reduce the appropriate level of contractual duration based on their own delay attitude, constraint condition prioritization and results from daily economic feasibility analyses.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 4
Type: Research Article
ISSN: 0969-9988

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Article
Publication date: 8 November 2018

Mahmood Kasravi, Amin Mahmoudi and Mohammad Reza Feylizadeh

Construction projects managers try their best for the project to go according to the plans. They always attempt to complete the projects on time and consistent with the…

379

Abstract

Purpose

Construction projects managers try their best for the project to go according to the plans. They always attempt to complete the projects on time and consistent with the predetermined budgets. Amid so many problems in project planning, the most critical and well-known problem is the Resource-Constrained Project Scheduling Problem (RCPSP). The purpose of this paper is to solve RCPSP using hybrid algorithm ICA/PSO.

Design/methodology/approach

Due to the existence of various forms for scheduling the problem and also the diversity of constraints and objective functions, myriad of research studies have been conducted in this realm of study. Since most of these problems are NP-hard ones, heuristic and meta-heuristic methods are used for solving these problems. In this research, a novel hybrid method which is composed of meta-heuristic methods of particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) has been used to solve RCPSP. Finally, a railway project has been examined for RCPS Problem in a real-world situation.

Findings

According to the results of the case study, ICA/PSO algorithm has better results than ICAs and PSO individually.

Practical implications

ICA/PSO algorithm could be used for solving problems in a multi-mode situation of activities or considering more constraints on the resources, such as the existence of non-renewable resources and renewable. Based on the case study in construction project, ICA/PSO algorithm has a better solution than PSO and ICA.

Originality/value

In this study, by combining PSO and ICA algorithms and creating a new hybrid algorithm, better solutions have been achieved in RCPSP. In order to validate the method, standard problems available in PSPLib library were used.

Details

Journal of Advances in Management Research, vol. 16 no. 2
Type: Research Article
ISSN: 0972-7981

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