Developing algorithms for solving complex optimisation problems has become a challenging topic recently. This study has applied a novel constructive heuristics algorithm named Domino Algorithm for the Traveling Salesman Problem (TSP) case which is aimed to efficiently reduce the calculation complexity and to find the optimal results of TSP best solution of tour lengths. As the study is a basic version of Domino Algorithm, it is decided to use the small TSP data sets consisting of 100 cities or less, such as Eil51, Berlin52, St70, Eil76, Pr76, and Rat99. This study also applied Nearest Neighbor approach to compare its result with that of Domino Algorithm. The results have shown that better tour lengths were achieved by Domino Algorithm (using 1 or 2 player (s)) for Eil51, Eil76, St70, Rat 99; and were resulted by Nearest Neighbor for Berlin52, and Pr76. For further research, the algorithm should be intensively combined with applying the improvement heuristic and should also be hybridized with meta-heuristics algorithm focusing on finding the optimal results by which the application will be moreover quite simple and easy.

The 1-D bin packing problem optimisation using bees algorithm

Supply chain management has increased more significance with the impact of globalization. In the present worldwide market, well-managed supply chain is a standout amongst the most vital requirement to be more competitive in the market. For any organization incorporate cement industry, the most critical decision in initial process of supply chain management is to buy products, materials or services from suppliers. So the role of suppliers is irrefutable important in the global aggressive markets. Appropriate decision of supplier selection can lead to reducing cost in supply chain management. However, it is becoming more complex because of existing various criteria and involving the suitable experts in the company to make valid decision in accordance with its criteria. In this study, the supplier selection of an Indonesia's leading cement company is analyzed by using one of the popular multi-criteria decision making method, Saaty's analytical network process (ANP). It is employed for the selection of the best alternative among three suppliers of pasted bag. Supplier with the highest rank comes from several major steps from building the relationship between various criteria to rating the alternatives with the help of experts from the company. The results show that, Communication capability, Flexible payment terms, Ability to meet delivery quantities are the most important criteria in the pasted bag supplier selection in Indonesian cement industry with 0.155, 0.110 and 0.1 ANP coefficient respectively. And based on the ANP coefficient values in limit supermatrix, the A2 or supplier 2 had the highest score with 64.7% or 0.13 ANP coefficient.

Arctic marine traffic is increasing as ice conditions change, creating greater risks of vessel collisions and groundings. To address the need for more reliable quantitative risk evaluation, this paper presents a new safety risk index tailored to Arctic maritime operations. The index integrates fuzzy-logic linguistic scoring with Multi-Criteria Decision-Making (MCDM) methods to convert expert judgements into a consistent numerical measure. The methodology involves defining qualitative criteria, assigning fuzzy membership functions, constructing expert-driven rule bases, and aggregating results through an MCDM approach. These components are calibrated using expert workshops to improve accuracy. Validation using historical Arctic collision and grounding cases shows that the index reduces false-negative alerts compared with traditional threshold-based tools. Sensitivity analysis identifies which criteria most strongly influence risk outcomes. Overall, the proposed index provides a more objective, transparent, and operationally useful assessment framework to support planners and bridge teams navigating Arctic waters.