2,699 research outputs found
Penghasilan manual rjngkas penggunaan alat Total Station Sokkia Set5f dan Perisian Sdr Mapping & Design untuk automasi ukur topografi
Projek ini dilaksanakan untuk menghasilkan manual ringkas penggunaan alat Total Station Sokkia SET5F dan Perisian SDR Mapping & Design dalam menghasilkan pelan topografi yang lengkap mengikut konsep field to finish. Manual telah dihasilkan dalam dua bentuk iaitu buku dan CD-ROM. Manual ini telah dinilai berdasarkan data yang diperolehi daripada 7 orang responden melalui kaedah Borang Penilaian Manual. Analisis data dilakukan menggunakan perisian SPSS versi 11.0. Hasil analisis skor min menunjukkan kesemua responden bersetuju bahawa manual dalam bentuk buku ini menarik Min ( M ) ^ ^ dan Sisihan Piawai (SD) = .535 tetapi kurang interaktif (M) = 2.29 dan (SD) = 0.488. Berbanding dengan manual dalam format CD-ROM yang mencatat nilai (M) = 3.57 dan (SD) = 0.535 semua responden bersetuju bahawa manual ini mesra pengguna dan lebih interakti
An Interactive Fuzzy Satisficing Method for Fuzzy Random Multiobjective 0-1 Programming Problems through Probability Maximization Using Possibility
In this paper, we focus on multiobjective 0-1 programming problems under the situation where stochastic uncertainty and vagueness exist at the same time. We formulate them as
fuzzy random multiobjective 0-1 programming problems where coefficients of objective functions are fuzzy random variables. For the formulated problem, we propose an interactive fuzzy satisficing method through probability maximization using of possibility
Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain
In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method
Observation of temporary accommodation for construction workers according to the code of practice for temporary construction site workers amenities and accommodation (ms2593:2015) in Johor, Malaysia
The Malaysian government is currently improving the quality of workers temporary
accommodation by introducing MS2593:2015 (Code of Practice for Temporary Site Workers
Amenities and Accommodation) in 2015. It is in line with the initiative in the Construction
Industry Transformation Programme (2016-2020) to increase the quality and well-being of
construction workers in Malaysia. Thus, to gauge the current practice of temporary
accommodation on complying with the particular guideline, this paper has put forth the
observation of such accommodation towards elements in Section 3 within MS2593:2015. A total
of seventeen (17) temporary accommodation provided by Grade 6 and Grade 7 contractors in
Johor were selected and assessed. The results disclosed that most of the temporary
accommodation was not complying with the guideline, where only thirteen (13) out of fifty-eight
(58) elements have recorded full compliance (100%), and the lowest compliance percentage
(5.9%) are discovered in the Section 3.12 (Signage). In a nutshell, given the significant gap of
compliance between current practices of temporary accommodation and MS2593:2015, a
holistic initiative need to be in place for the guideline to be worthwhile
Insecticidal and repellant activities of Southeast Asia plants towards insect pests: a review
Crops are being damaged by several plant pests. Several strategies have been developed to restrict the damage of cultivated plants by using synthetic pesticides and repellants. However, the use to control these insects is highly discouraged because of their risks on humans. Therefore, several alternatives have been developed from plant extracts to protect crops from plant pests. Accordingly, this review focuses on outlining the insecticidal and repellant activities of Southeast Asia plants towards insect pests. Several extracts of plants from Southeast Asia were investigated to explore their insecticidal and repellant activities. Azadiracha indica (neem) and Piper species were highly considered for their insecticidal and repellant activities compared to other plants. This review also addressed the investigation on extracts of other plant species that were reported to exert insecticidal and repellant activities. Most of the conducted studies have been still in the primarily stage of investigation, lacking a focus on the insecticidal and repellant spectrum and the identification of the active constituents which are responsible for the insecticidal and repellant activity
FUZZINESS IN FOREST SURVEY DESIGN OPTIMIZATION
When using optimization techniques to optimize a sampling with partial replacement design, it is often assumed that the following parameters are known exactly: 1) desired level of sampling error or total sampling cost for the survey; 2) variable costs; and 3) population variance and correlation coefficients. In practice, however, these parameters needed for finding the optimal design are only educated guesses. The parameters can be considered to be fuzzy. In this paper, brief consideration is given to the optimization of a sampling with partial replacement design using nonlinear programming techniques with fuzzy parameters. The basis of this method is to obtain the optimal solution by minimizing the objective function, subject to some restrictions, when the parameters that appear in both the objective function and restriction functions are fuzzy. The method is applied to a two-occasion continuous forest inventory
Interactive Fuzzy Random Two-level Linear Programming through Fractile Criterion Optimization
This paper considers two-level linear programming problems involving fuzzy random variables. Having introduced level sets of fuzzy random variables and fuzzy goals of decision makers, following fractile criterion optimization, fuzzy random two-level programming problems are transformed into deterministic ones. Interactive fuzzy programming is presented for deriving a satisfactory solution efficiently with considerations of overall satisfactory balance
Fuzzy Random Noncooperative Two-level Linear Programming through Absolute Deviation Minimization Using Possibility and Necessity
This paper considers fuzzy random two-level linear programming problems under noncooperative behaviorof the decision makers. Having introduced fuzzy goals of decision makers together with the possibiliy and necessity measure, following absolute deviation minimization, fuzzy random two-level programin problems are transformed into deterministic ones. Extended Stackelberg solutions are introduced andcomputational methods are also presented
Application of Multi-Objective Optimization Based on Genetic Algorithm for Sustainable Strategic Supplier Selection under Fuzzy Environment
Purpose: The incorporation of environmental objective into the conventional supplier selection
practices is crucial for corporations seeking to promote green supply chain management (GSCM).
Challenges and risks associated with green supplier selection have been broadly recognized by
procurement and supplier management professionals. This paper aims to solve a Tetra “S” (SSSS)
problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply
chain environment. In this empirical study, a mathematical model with fuzzy coefficients is
considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model
is developed to tackle this problem.
Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are
typically multi-objectives in nature and it is an important part of green production and supply
chain management for many firms. The proposed uncertain model is transferred into
deterministic model by applying the expected value measure (EVM) and genetic algorithm with weighted sum approach for solving the multi-objective problem. This research focus on a multiobjective
optimization model for minimizing lean cost, maximizing sustainable service and
greener product quality level. Finally, a mathematical case of textile sector is presented to
exemplify the effectiveness of the proposed model with a sensitivity analysis.
Findings: This study makes a certain contribution by introducing the Tetra ‘S’ concept in both
the theoretical and practical research related to multi-objective optimization as well as in the study
of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results
suggest that decision makers tend to select strategic supplier first then enhance the sustainability.
Research limitations/implications: Although the fuzzy expected value model (EVM) with
fuzzy coefficients constructed in present research should be helpful for solving real world
problems. A detailed comparative analysis by using other algorithms is necessary for solving
similar problems of agriculture, pharmaceutical, chemicals and services sectors in future.
Practical implications: It can help the decision makers for ordering to different supplier for
managing supply chain performance in efficient and effective manner. From the procurement and
engineering perspectives, minimizing cost, sustaining the quality level and meeting production
time line is the main consideration for selecting the supplier. Empirically, this can facilitate
engineers to reduce production costs and at the same time improve the product quality.
Originality/value: In this paper, we developed a novel multi-objective programming model
based on genetic algorithm to select sustainable strategic supplier (SSSS) under fuzzy
environment. The algorithm was tested and applied to solve a real case of textile sector in
Pakistan. The experimental results and comparative sensitivity analysis illustrate the effectiveness
of our proposed model.Peer Reviewe
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