• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.9-16
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• 2022

The relevance of the topic is determined by the existence of inconsistencies between economic and environmental aspects of innovative development of urban logistics infrastructure, as well as the conflict of public, state and private commercial interests in this issue. The purpose of the article is to determine the principles and effective tools for innovative development of urban logistics infrastructure, taking into account pandemic constraints. The influence of the environmental aspect on the dynamics of transport flows was analyzed in detail and characterized, the scheme of determining the optimal solution for the development of the city was proposed considering the compromise between economic and ecological interests of society, state and business entities. A scheme of innovative development of urban logistics infrastructure under pandemic constraints was also developed. Materials of the article are relevant for developers of city plans, managers of urban logistics infrastructure, employees of enterprises participating in transport and logistics markets, scientists, and doctoral students.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.423-431
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• 2011

Warfighting experimentation is an important process for identifying requirements against changing military environment and for verifying proposed measures for reforming military service. The wargame simulation experiment is regarded as one of the most effective means to warfighting experimentation, and its importance is increasing than ever. On the other hand, the results of wargame experiments could be unreliable due to the uncertainty involved in the experimental procedure. To improve the reliability of the experimental results, systematic experimental procedures and analysis methods must be employed, and the design and analysis of experiments technique can be used effectively for this purpose. In this paper, AWAM, a wargame simulator, is used to optimize the organization of operational troops. The simulation model describes a warfighting situation in which the 'survival rate of our force' and the 'survival rate of the enemy force' are considered as responses, 'the numbers of weapons in the squad' as control factors, and 'the uncontrollable variables of the battlefield' as noise factors. In addition, for the purpose of effective experimentation, the product array approach in which the inner and outer orthogonal arrays are crossed is adopted. Then, the signal-to-noise-ratio for each response and the desirabilities for the means and standard deviations of responses are calculated and used to determine a compromise optimal solution. The experimental procedures and analysis methods developed in this paper can provide guidelines for designing and analyzing wargame simulation experiments for similar warfighting situations.