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During the past two decades, some industries have been moving towards project-centered systems in many modern countries. Therefore, managing simultaneous projects with considering the limitations in resources, equipment and manpower is very crucial. In the real world, project-based organizations are always facing with two main important features. First, the construction projects are decentralized and their distances are long, and second, there are several construction projects undertaken at different time periods. Therefore, appropriate selection of projects with regard to the capabilities of the organization may lead with increasing an expected profitability. This paper investigates the multi-period decentralized multi construction-project and scheduling problem subject to resource constraints, optimal resource pool location, deterioration and batch ordering of nonrenewable resources altogether, for the first time in the literature. In order to describe the problem under consideration in this paper and obtaining the optimal solutions, a mixed integer linear programming model is developed. Finally, the impact of decision integration on the profit profile of an organization is comprehensively investigated by solving numerical examples and through developing some heuristic methods.

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In decentralized construction projects, costs are mostly related to investment, material, holding, logistics, and other minor costs for implementation. For this reason, simultaneous planning of these items and appropriate scheduling of activities can significantly reduce the total costs of the project undertaken. This paper investigates the decentralized multiple construction projects scheduling problem with the aim of minimizing 1) the completion time of the construction projects and 2) the costs of project implementation. Initially, a bi-objective integer programming model is proposed which can solve small-size problems using the method. Then, a Priority Heuristic Algorithm (PHA), Non-dominate Sorting Artificial Bee Colony (NSABC) and Non-dominate Sorting Genetic Algorithm II (NSGA-II) are developed to handle large-size problems using a modified version of Parallel Schedule Generation Scheme (PSGS). The computational investigations significantly reveal the performance of the proposed heuristic methods over exact ones. Finally, the proposed methods are ranked using TOPSIS approach and metric definition. The results show that NSGA-II-100 (NSGA-II with 100 iterations), NSABC-100 (NSABC with 100 iterations) and PHA are ranked as the best known solution methods, respectively.

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Explosions are inevitable in today’s world; therefore, building structures may be dynamically loaded by an intense loading during the explosion. This is why regulatory bodies have provided instructions for determining the response of structures under the explosion load. Previous research has shown that when the explosion happens close to a structure, the ground explosion load can be modeled as tensile and compressive loads. This research investigates the response of an elastic-plastic single-degree-of-freedom system subjected to different explosive loads with different positive durations. The maximum intensity of blast load and blast duration remains constant, and the positive phase duration is the only variable that changes. The nonlinear dynamic responses of a single-degree-of-freedom system (i.e., displacement, velocity, acceleration, and ductility) are calculated using the linear acceleration method. The results show that increasing the positive phase duration and the amount of positive impact can increase the maximum displacement and ductility of the system. Also, it can be concluded that the maximum acceleration of the studied systems remains constant when the values for the blast impact and positive phase durations change.
 

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A new type of seismic control device is introduced—the elastoplastic inerter-tuned mass damper—which omits the conventional viscous damping element and instead incorporates stiffness with elastoplastic behavior. The key objective is to benchmark its earthquake performance against alternative vibration mitigation strategies, including the standard tuned mass damper, the elastoplastic tuned mass damper, and the inerter-tuned mass damper. For each configuration, the design variables are optimized by minimizing the Park–Ang damage index, thereby maximizing the structure’s seismic resilience. A nine-story moment-resisting frame is employed and is modeled with the OpenSees software nonlinearly. Simulation results reveal that the proposed elastoplastic inerter-tuned mass damper surpasses all other examined systems. Specifically, it delivers up to a 38% drop in the global damage index and a 50% damage reduction in the lower stories.

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In thermomechanical topology optimization, variations in material distribution influence not only the structural stiffness but also the temperature field and thermal loads induced by constrained thermal expansion. In this study, a moving morphable component (MMC)-based framework is proposed for thermomechanical topology optimization, in which the density-based representation of the SIMP method is replaced with an explicit geometry description using an MMC. In the proposed approach, steady-state heat conduction analysis, equivalent thermomechanical load formulation, and structural mechanical analysis are retained, whereas compliance minimization subject to a volume constraint is adopted as the optimization objective. The elemental density field is derived from the topology description and Heaviside functions, and the sensitivity of the objective function with respect to the geometric parameters of the MMC is evaluated using the chain rule. Numerical examples demonstrate that the proposed method achieves satisfactory thermomechanical performance while producing smoother boundaries and a more explicit geometric representation than the conventional SIMP method.