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Elbarkouky, M M G and Fayek, A R (2011) Fuzzy Similarity Consensus Model for Early Alignment of Construction Project Teams on the Extent of Their Roles and Responsibilities. Journal of Construction Engineering and Management, 137(06), 432–40.

Evia, C (2011) Localizing and Designing Computer-Based Safety Training Solutions for Hispanic Construction Workers. Journal of Construction Engineering and Management, 137(06), 452–9.

Hong, T, Cho, K, Hyun, C and Han, S (2011) Simulation-Based Schedule Estimation Model for ACS-Based Core Wall Construction of High-Rise Building. Journal of Construction Engineering and Management, 137(06), 393–402.

Lee, S, Jeon, R, Kim, J and Kim, J (2011) Strategies for Developing Countries to Expand Their Shares in the Global Construction Market: Phase-Based SWOT and AAA Analyses of Korea. Journal of Construction Engineering and Management, 137(06), 460–70.

Ozorhon, B, Arditi, D, Dikmen, I and Birgonul, M T (2011) Toward a Multidimensional Performance Measure for International Joint Ventures in Construction. Journal of Construction Engineering and Management, 137(06), 403–11.

Said, H and El-Rayes, K (2011) Optimizing Material Procurement and Storage on Construction Sites. Journal of Construction Engineering and Management, 137(06), 421–31.

  • Type: Journal Article
  • Keywords: Procurement; Inventories; Optimization; Algorithms; Construction management; Construction materials; Storage; Materials procurement; Inventory control; Dynamic layout planning; Optimization; Genetic algorithms;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000307
  • Abstract:
    Efficient planning of materials procurement and storage on construction sites can lead to significant improvements in construction productivity and project profitability. Existing research studies focus on material procurement and storage layout as two separate planning tasks without considering their critical and mutual interdependencies. This paper presents the development of a new optimization model for construction logistics planning that is capable of simultaneously integrating and optimizing the critical planning decisions of material procurement and material storage on construction sites. The model utilizes genetic algorithms to minimize construction logistics costs that cover material ordering, financing, stock-out, and layout costs. The model incorporates newly developed algorithms to estimate the impact of potential material shortages on-site because of late delivery on project delays and stock-out costs. An application example is analyzed to demonstrate the capabilities of the construction logistics planning model in simultaneously optimizing material procurement decisions and storage layout plans.

Shen, L, Wu, Y and Zhang, X (2011) Key Assessment Indicators for the Sustainability of Infrastructure Projects. Journal of Construction Engineering and Management, 137(06), 441–51.

Tserng, H P, Liao, H, Tsai, L K and Chen, P (2011) Predicting Construction Contractor Default with Option-Based Credit Models—Models’ Performance and Comparison with Financial Ratio Models. Journal of Construction Engineering and Management, 137(06), 412–20.