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Given the growing interest in modern construction techniques and the emergence of innovative technologies, construction site layout planning research has progressively been investigating approaches to adopt innovative concepts and incorporate renewed approaches to improve widespread efficiency. This research develops a decision-making tool that optimizes construction site layout plans. The developed model targets two main objectives: minimizing material transportation costs and maximizing safety by optimally placing facilities on construction sites.

A novel approach is devised based on the integration of Building Information Modeling and Generative Design (BIM-GD). This engine is used to optimize the multi-objective site layout problems to identify layout alternatives in the early project stages. Parametric modeling uses Dynamo to construct the model and explore constraints initially. Finally, the GD environment is utilized to create different design alternatives, and then the decision-making procedure selects the most appropriate design alternative. Additionally, a case study is applied to validate the effectiveness of the developed model.

The results indicate the effectiveness of the proposed GD tool and its potential for more complex applications. The GD engine examined optimal layout plans, balancing different objectives and adhering to appointed geometric constraints. A case study was conducted to assess the model's effectiveness and showcase its suitability. Construction Site Layout Planning (CSLP) is an essential step in design that can influence considerable aspects, such as material transportation expenses and different safety standards on the site. Employing visual programming for parametric modeling within Dynamo-Revit creates an expedient and user-friendly platform for planning engineers who may require more programming expertise to create and program algorithmic models visually. Utilizing GD in CSLP has proven to be a powerful tool with consequential prospects for improving applications and executing more models.

The findings from this framework are intended to help construction practitioners select the most appropriate site layout during early project stages while incorporating different safety criteria inside construction sites to alleviate actual safety risks.

A new approach is proposed that utilizes an integrated BIM-GD engine to optimize multi-objective site layout problems. This approach targets two main objectives: minimizing material transportation costs and maximizing safety by optimally placing facilities in construction sites.

Considers selenium and various aspects of its analysis. Looks at various factors relating to its measurement and underlines the need for elements such as sound experimental design and critical application of results to move analysis forward.

Considers the role of selenium as an essential nutrient. Identifies its key function as being an essential component of a wider range of proteins. Looks at some of the problems related to selenium deficiency such as associations with increased incidence of cancer of heart disease. Reports falling selenium intakes in the UK over the last 15‐20 years and describes a supplementation trial based in Scotland.

Notes that, despite its abundance as an essential trace element in the body, relatively little is known about dietary copper requirements. Looks at factors such as copper metabolisms and minimum dieting requirements. Reports on studies funded by MAFF in this area.

The purpose of this paper is to identify potential helicopter pilots’ errors during their interaction with the flight deck in the process of starting a helicopter in night-time conditions.

Systematic Human Error Reduction and Prediction Approach is used for the analysis of the pilot–flight deck interaction. This methodology was used for the identification of errors for 30 pilots during a period of 10 years. In total, 55 errors were identified, and most common errors noted are: error of omission, caused by pilots’ lack of attention or longer periods of no flying, and error of wrong execution, caused by misunderstanding a situation.

Hierarchical task analysis and classification of pilot’s tasks were used for the analysis of consequences, probability of occurrence, criticality and remedial strategies for the identified pilot error.

This paper does not give an ergonomic analysis of the flight deck, as that is not its subject. However, results of the research presented in this paper, together with results presented in references, clearly show that there are disadvantages in the ergonomic design of flight decks.

Based on the identified pilot errors and with respect of existing ergonomic solution, it is possible to begin with the reconstruction of flight decks.

Higher quality of pilot–flight deck interaction must be ensured for both pilots’ and passengers’ safety, as even a slightest error can lead to catastrophic consequences.

The value of this paper lies in the fact that it points to the need for synergy of ergonomic design and human reliability methods.

Repetitive projects play an important role in the construction industry. A crucial point in scheduling this type of project lies in enabling timely movement of crews from unit to unit so as to minimize the adverse effect of work interruptions on both time and cost. This paper aims to examine a repetitive scheduling problem with work continuity constraints, involving a tradeoff among project duration, work interruptions and total project cost (TPC). To enhance flexibility and practicability, multi-crew execution is considered and the logic relation between units is allowed to be changed arbitrarily. That is, soft logic is considered.

This paper proposes a multi-objective mixed-integer linear programming model with the capability of yielding the optimal tradeoff among three conflicting objectives. An efficient version of the e-constraint algorithm is customized to solve the model. This model is validated based on two case studies involving a small-scale and a practical-scale project, and the influence of using soft logic on project duration and total cost is analyzed via computational experiments.

Using soft logic provides more flexibility in minimizing project duration, work interruptions and TPC, especial for non-typical projects with a high percentage of non-typical activities.

The main limitation of the proposed model fails to consider the learning-forgetting phenomenon, which provides space for future research.

This study assists practitioners in determining the “most preferred” schedule once additional information is provided.

This paper presents a new soft logic-based mathematical programming model to schedule repetitive projects with the goal of optimizing three conflicting objectives simultaneously.

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.

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.

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.

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.

Airline scheduling is an extremely complex process. Moreover, disruption in a single flight may damage the entire schedule tremendously. Using an efficient recovery scheduling strategy is vital for a commercial airline. The purpose of this paper is to present an integrated aircraft and crew recovery plans to reduce delay and prevent delay propagation on airline schedule with the minimum cost.

A mixed-integer linear programming model is proposed to formulate an integrated aircraft and crew recovery problem. The main contribution of the model is that recovery model is formulated based on individual flight legs instead of strings. This leads to a more accurate schedule and better solution. Also, some important issues such as crew swapping, reassignment of aircraft to other flights as well as ground and sit time requirements are considered in the model. Benders’ decomposition approach is used to solve the proposed model.

The model performance is also tested by a case including 227 flights, 64 crew, 56 aircraft and 40 different airports from American Airlines data for a 24-h horizon. The solution achieved the minimum cost value in 35 min. The results show that the model has a great performance to recover the entire schedule when disruption happens for random flights and propagation delay is successfully limited.

The authors confirm that this is an original paper and has not been published or under consideration in any other journal.

Deployment of optimal size of resources is a key issue in repetitive construction projects. This paper describes a simulation model based on queuing theory for the resource scheduling of a real repetitive housing project involving 320 dwelling units constructed in East Delhi, India. The optimal size of resources, defined as the minimum size required to keep the project duration a minimum, has been identified from the results of a series of sensitivity analyses in which the size of the resources was varied one at a time. The duration of the project, the period of utilization of the resources, and the queue length of activities waiting for service are also reported in this paper. It has been shown that reduction in size of resources is achievable without increasing the duration of the project and queue length of activities. Increase in the size of some specialised crews is also proved advantageous.