Abstract
Details
Keywords
Kwasi Gyau Baffour Awuah and Raymond Talinbe Abdulai
Although a basic need, housing and its development activities impinge on the environment. As part of efforts to promote sustainability, there have been several initiatives since…
Abstract
Although a basic need, housing and its development activities impinge on the environment. As part of efforts to promote sustainability, there have been several initiatives since the Brundtland Commission's work in 1987 to minimise the adverse impact of housing development activities on the environment in the developing world such as sub-Saharan Africa (SSA). This chapter explores housing development activities in Ghana within the context of environmental sustainability based on the extant literature. The aim is to examine the state and promotion of environmental sustainability in the housing development sector. The chapter establishes that although there are some efforts to promote environmental sustainability within the housing development sector, uptake of environmental sustainability practices has been less satisfactory due to lack of incentives as stakeholders perceive that environmentally sustainable homes are more expensive than conventional ones. The chapter, therefore, recommends further investigations into the cost and benefit of environmentally sustainable homes as well as other drivers in Ghana to give additional insights to provide the appropriate doses of incentives both contrived and instinctive to drive uptake.
Details
Keywords
Phan N. Duy, Lee Chapman, Miles Tight, Phan N. Linh and Le V. Thuong
Flooding is an emerging problem in Ho Chi Minh City (HCMC), Vietnam, and is fast becoming a major barrier to its ongoing development. While flooding is presently of nuisance…
Abstract
Purpose
Flooding is an emerging problem in Ho Chi Minh City (HCMC), Vietnam, and is fast becoming a major barrier to its ongoing development. While flooding is presently of nuisance value, there is a growing concern that a combination of rapid urban expansion and climate changes will significantly exacerbate the problem. There has been a trend of population being rapidly accommodated in new urban areas, which are considered highly vulnerable to floods, while the development strategy by the local government still attracts more property investments into the three new districts on the right side of Saigon River. This paper aims to discuss the increase in the number of residences vulnerable to flooding, to underline the need for more appropriate future spatial development. For the vision, an application of compact and resilient theories to strategic planning and management of this city is proposed to reduce vulnerability. This paper also highlights the need to better understand growing vulnerability to floods related to urban expansion over low-lying former wetlands and the more important role of planning spatial development accompanied with transportation investment which can contribute to flooding resilience.
Design/methodology/approach
This research uses combined-methods geographical information system (GIS) analysis based on secondary data of flood records, population distributions, property development (with the details of 270 housing projects compiled as part of this research) and flooding simulation. This allows an integrated approach to the theories of urban resilience and compactness to discuss the implication of spatial planning and management in relevance to flooding vulnerability.
Findings
The flooding situation in HCMC is an evidence of inappropriate urban expansion leading to increase in flooding vulnerability. Although climate change impacts are obvious, the rapid population growth and associated accommodation development are believed to be the key cause which has not been solved. It was found that the three new emerging districts (District 2, 9 and ThuDuc) are highly vulnerable to floods, but the local government still implements the plan for attracted investments in housing without an integrated flooding management. This is also in line with the development pattern of many coastal cities in Southeast Asia, as economic development can be seen as a driving factor.
Research limitations/implications
The data of property development are diversified from different sources which have been compiled by this research from the basic map of housing investments from a governmental body, the Department of Construction. The number of projects was limited to 270 per over 500 projects, but this still sufficiently supports the evidence of increasing accommodation in new development districts.
Practical implications
HCMC needs neater strategies for planning and management of spatial development to minimize the areas vulnerable to floods: creating more compact spaces in the central areas (Zone 1) protected by the current flooding management system, and offering more resilient spaces for new development areas (Zone 2), by improving the resilience of transportation system. Nevertheless, a similar combination of compact spaces and resilient spaces in emerging districts could also be incorporated into the existing developments, and sustainable drainage systems or underground water storage in buildings could also be included in the design to compensate for the former wetlands lost.
Social implications
This paper highlights the need to better understand growing vulnerability to floods related to urban expansion over low-lying former wetlands and emphasizes the more important role of planning spatial development accompanied with transportation investment which can contribute to flooding resilience. Coastal cities in southeast countries need to utilize the former-land, whereas feasibility of new land for urban expansion needs to be thoroughly considered under risk of natural disasters.
Originality/value
A combination of compact spaces with improved urban resilience is an alternative approach to decrease the flooding risk beyond that of traditional resistant systems and underlines the increasingly important role of urban planning and management to combat the future impacts of floods.
Details
Keywords
YuFei Guo, YongQing Hai and JianFei Liu
During the industrial design process, a product is usually modified and analyzed repeatedly until reaching the final design. Modifying the model and regenerating a mesh for every…
Abstract
Purpose
During the industrial design process, a product is usually modified and analyzed repeatedly until reaching the final design. Modifying the model and regenerating a mesh for every update during this process is very time consuming. To improve efficiency, it is necessary to circumvent the computer-aided design modeling stage when possible and directly modify the meshes to save valuable time. The purpose of this paper is to develop a method for mesh modifications.
Design/methodology/approach
In contrast to existing studies, which focus on one or a class of modifications, this paper comprehensively studies mesh union, mesh gluing, mesh cutting and mesh partitioning. To improve the efficiency of the method, the paper presents a fast and effective surface mesh remeshing algorithm based on a ball-packing method and controls the remeshing regions with a size field.
Findings
Examples and results show that the proposed mesh modification method is efficient and effective. The proposed method can be also applied to meshes with different material properties, which is very different with previous work that is only suitable for the meshes with same material property.
Originality/value
This paper proposes an efficient and comprehensive tetrahedral mesh modification method, through which engineers can directly modify meshes instead of models and save time.
Details
Keywords
Eline de Backer, Joris Aertsens, Sofie Vergucht and Walter Steurbaut
Sustainable agriculture implies the ability of agro‐ecosystems to remain productive in the long‐term. It is not easy to point out unambiguously whether or not current production…
Abstract
Purpose
Sustainable agriculture implies the ability of agro‐ecosystems to remain productive in the long‐term. It is not easy to point out unambiguously whether or not current production systems meet this sustainability demand. A priori thinking would suggest that organic crops are environmentally favourable, but may ignore the effect of reduced productivity, which shifts the potential impact to other parts of the food provision system. The purpose of this paper is to assess the ecological sustainability of conventional and organic leek production by means of life cycle assessment (LCA).
Design/methodology/approach
A cradle‐to‐farm gate LCA is applied, based on real farm data from two research centres. For a consistent comparison, two functional units (FU) were defined: 1ha and 1 kg of leek production.
Findings
Assessed on an area basis, organic farming shows a more favourable environmental profile. These overall benefits are strongly reduced when the lower yields are taken into account. Related to organic farming it is therefore important that solutions are found to substantially increase the yields without increasing the environmental burden. Related to conventional farming, important potential for environmental improvements are in optimising the farm nutrient flows, reducing pesticide use and increasing its self‐supporting capacity.
Research limitations/implications
The research is a cradle‐to‐farm gate LCA, future research can be expanded to comprise all phases from cradle‐to‐grave to get an idea of the total sustainability of our present food consumption patterns. The research is also limited to the case of leek production. Future research can apply the methodology to other crops.
Originality/value
To date, there is still lack of clear evidence of the added value of organic farming compared to conventional farming on environmental basis. Few studies have compared organic and conventional food production by means of LCA. This paper addresses these issues.
Details
Keywords
The purpose of this paper is to present a degenerated simplex search method to optimize neural network error function. By repeatedly reflecting and expanding a simplex, the…
Abstract
Purpose
The purpose of this paper is to present a degenerated simplex search method to optimize neural network error function. By repeatedly reflecting and expanding a simplex, the centroid property of the simplex changes the location of the simplex vertices. The proposed algorithm selects the location of the centroid of a simplex as the possible minimum point of an artificial neural network (ANN) error function. The algorithm continually changes the shape of the simplex to move multiple directions in error function space. Each movement of the simplex in search space generates local minimum. Simulating the simplex geometry, the algorithm generates random vertices to train ANN error function. It is easy to solve problems in lower dimension. The algorithm is reliable and locates minimum function value at the early stage of training. It is appropriate for classification, forecasting and optimization problems.
Design/methodology/approach
Adding more neurons in ANN structure, the terrain of the error function becomes complex and the Hessian matrix of the error function tends to be positive semi‐definite. As a result, derivative based training method faces convergence difficulty. If the error function contains several local minimum or if the error surface is almost flat, then the algorithm faces convergence difficulty. The proposed algorithm is an alternate method in such case. This paper presents a non‐degenerate simplex training algorithm. It improves convergence by maintaining irregular shape of the simplex geometry during degenerated stage. A randomized simplex geometry is introduced to maintain irregular contour of a degenerated simplex during training.
Findings
Simulation results show that the new search is efficient and improves the function convergence. Classification and statistical time series problems in higher dimensions are solved. Experimental results show that the new algorithm (degenerated simplex algorithm, DSA) works better than the random simplex algorithm (RSM) and back propagation training method (BPM). Experimental results confirm algorithm's robust performance.
Research limitations/implications
The algorithm is expected to face convergence complexity for optimization problems in higher dimensions. Good quality suboptimal solution is available at the early stage of training and the locally optimized function value is not far off the global optimal solution, determined by the algorithm.
Practical implications
Traditional simplex faces convergence difficulty to train ANN error function since during training simplex can't maintain irregular shape to avoid degeneracy. Simplex size becomes extremely small. Hence convergence difficulty is common. Steps are taken to redefine simplex so that the algorithm avoids the local minimum. The proposed ANN training method is derivative free. There is no demand for first order or second order derivative information hence making it simple to train ANN error function.
Originality/value
The algorithm optimizes ANN error function, when the Hessian matrix of error function is ill conditioned. Since no derivative information is necessary, the algorithm is appealing for instances where it is hard to find derivative information. It is robust and is considered a benchmark algorithm for unknown optimization problems.
Details
Keywords
Federico Caniato, Luca Mattia Gelsomino, Alessandro Perego and Stefano Ronchi
Recently, in response to the credit crunch and the increased costs of financing, new solutions for supporting the financial management of supply chains, known as supply chain…
Abstract
Purpose
Recently, in response to the credit crunch and the increased costs of financing, new solutions for supporting the financial management of supply chains, known as supply chain finance (SCF), have been developed. They exploit the strengths of supply chain links to optimise working capital. The purpose of this paper is to provide a reference framework that links together the objectives leading to the adoption of SCF solutions and several moderating variables.
Design/methodology/approach
This paper adopts a multiple case study methodology, analysing 14 cases of the application of SCF solutions among Italian companies.
Findings
The main findings are the identification of the different objectives leading to the adoption of SCF; the analysis of the impact of moderating variables (the level of inter- and intra-firm collaboration, the level of the trade process digitalisation and the bargaining power and financial strength of the leading firm) on SCF adoption; and the formulation of a reference framework supporting the effective adoption of SCF solutions.
Research limitations/implications
This contribution is exploratory in nature; theory-testing contributions should be the focus of further research. Also, the sample is limited to Italian companies. Finally, the service provider’s point of view has been marginally taken into consideration in this study.
Originality/value
The article addresses the need for more empirical research on SCF. It provides a reference framework focused on the objectives and moderating variables leading to effective SCF adoption, providing a theory-building contribution on the general topic of SCF and on the specific topic of the adoption process of different SCF solutions.
Details
Keywords
The purpose of this paper is to develop a new rectilinear branch pipe‐routing algorithm for automatic generation of rectilinear branch pipe routes in constrained spaces of…
Abstract
Purpose
The purpose of this paper is to develop a new rectilinear branch pipe‐routing algorithm for automatic generation of rectilinear branch pipe routes in constrained spaces of aero‐engines.
Design/methodology/approach
Rectilinear branch pipe routing that connects multiple terminals in a constrained space with obstacles can be formulated as a rectilinear Steiner minimum tree with obstacles (RSMTO) problem while meeting certain engineering rules, which has been proved to be an NP‐hard and discrete problem. This paper presents a discrete particle swarm optimization (PSO) algorithm for rectilinear branch pipe routing (DPSO‐RBPRA) problems, which adopts an attraction operator and an energy function to plan the shortest collision‐free connecting networks in a discrete graph space. Moreover, this paper integrates several existing techniques to evaluate particles for the RSMTO problem in discrete Manhattan spaces. Further, the DPSO‐RBPRA is extended to surface cases to adapt to requirements of routing pipes on the surfaces of aero‐engines.
Findings
Pipe routing numeral computations show that, DPSO‐RBPRA finds satisfactory connecting networks while considering several engineering rules, which demonstrates the effectiveness of the proposed method.
Originality/value
This paper applies the Steiner tree theory and develops a DPSO algorithm to plan the aero‐engine rectilinear branch pipe‐routing layouts.
Details
Keywords
Christopher Rose and Jenny Coenen
The purpose of this paper is to present a method for generating a set of feasible, optimized production schedules for the erection process of compact shipyards building complex…
Abstract
Purpose
The purpose of this paper is to present a method for generating a set of feasible, optimized production schedules for the erection process of compact shipyards building complex ship types.
Design/methodology/approach
A bi-objective mathematical model is developed based on the process constraints. A Pareto front of possible erection schedules is created using a the Non-dominated Sorting Genetic Algorithm II with a custom heuristic fitness function and constraint violation.
Findings
It was possible to consistently generate a wide variety of production schedules with superior performance to those manually created by shipyard planner in negligible computational time.
Practical implications
The set of optimized production schedules generated by the developed methodology can be used as a starting point by existing shipyard planners when drafting the initial erection planning for a new project. This allows the planners to consider wider variety of options in less time.
Originality/value
No other published approach for the automatic generation of optimized production schedules of the erection process is specifically tailored to the construction of complex ships.