Recycling uncontaminated excavated construction soil is beneficial because it reduces the costs to abandon excess soil or obtain refill soil from a distant location while alleviating environmental burdens. For this reason, various methods and techniques to support on-site soil reuse have been explored. However, in order to increase the reuse rate, excavated soil should be recycled among different construction sites as well. As a prerequisite for reusing excess soil in this context, the construction schedules, type of soil, trading volume, and incurred costs must be coordinated. In order to consider all of these aspects, earthmoving among construction sites needs to be planned by means of multi-objective optimization. This paper aims to present a practical solution supporting inter-site soil trade by introducing a non-dominated sorting algorithm-II (NSGA-II), a type of multi-objective evolutionary algorithm (MOEA). A description of the optimization procedure is provided, and computational results are presented to prove the effectiveness of the selected method.
Due to the variety of processes that are mainly influenced by the modification of law and regulations, it is difficult to propose a formal procedure of urban renewal projects. In addition, conflicts among various participants and stake-holders have made urban renewal difficult to manage. Needs for new systems to support management of this type of projects have been raised. This system should enable users to manage program aspects as well as projects given that the urban renewal consists of several projects. According to analysis of current context, the requirements of the system are classified as follows: a method to create flexible systems to cope with various process; functions to provide data on cost and schedule; user-friendly visualized tools enhancing understand of non-experts or less-experienced participants. This paper summarizes the background, requirements, concept and model of the system. Currently, prototype systems have been developed. Regarding outputs presented so far, potential benefits of the system are presented as well.
Recently, in an attempt to overcome the defects of quiescent power shutdown system, smart quiescent power control system has been developed. However, due to its higher investment costs, feasibility evaluation must be conducted. While LCCA (Life Cycle Cost Analysis) model is useful to estimate net savings of alternatives that differ with respect to initial costs and operating costs, the environmental burdens are not considered. On the contrary, LCA (Life Cycle Assessment) model is suitable to assess environmental impacts associated with the stages of a product's life but it does not consider costs. In this study, a comprehensive analysis on the economic and environmental impacts of smart quiescent power control system is conducted by using LCCA and LCA model. In addition, sensitivity analysis is carried out to quantify accuracy of estimates.
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