A Pythagorean fuzzy ANP-QFD-Grey relational analysis approach to prioritize design requirements of sustainable supply chain

A sustainable supply chain (SSC) is vital for company’s sustainability success, so it is imperative to identify and prioritize SSC’s design requirements (DRs) for better SSC planning. For customer-centric markets, the customer requirements (CRs) need to be integrated into SSC’s DRs. This paper thus proposes a customer-centric approach based on Analytic Network Process (ANP), Quality Function Deployment (QFD), Grey Relational Analysis (GRA), and Pythagorean Fuzzy Set (PFS) to rank SSC’s DRs, considering CRs and information ambiguity. The PFS is combined with ANP, QFD, and GRA to better handle uncertainty in the SSC. The Pythagorean fuzzy ANP is applied to analyze the correlations among the sustainable CRs and determine the corresponding weights. The sustainable CRs are transformed into the DRs using the Pythagorean fuzzy QFD. The relationships among the resulting DRs are analyzed through Pythagorean fuzzy GRA to prioritize DRs. The approach is validated through a case study. The results obtained in this paper shows that the proposed method is efficient to prioritize DRs of SSC with the consideration of sustainable CRs under uncertain environment. The novelties of proposed method are that it not only offers a customer-oriented SSC planning method through the integration of ANP, QFD and GRA, but also can reflect the uncertain information with a broader membership representation space via PFSs. Based on the proposed method, the decision-maker can conduct comprehensive analysis to prioritize DRs and design appropriate SSC to fulfill CRs under uncertain environment.

Differential replay for reward and punishment paths predicts approach and avoidance

Planning is thought to involve neural replay, where states relevant to a task goal are rapidly reactivated in sequence. It remains unclear if, during planning, replay of a path relates to an actual prospective choice. Here, using magnetoencephalography (MEG), we studied participants while they planned to either approach or avoid an uncertain environment that contained paths leading to reward and to punishment. We show significant planning-related forward sequential replay with state-to-state transitions in the range of 20 to 90 ms. Replay of rewarding paths was boosted prior to a decision to avoid, and attenuated prior to a decision to approach. Crucially, a trial-by-trial bias in replaying punishing paths predicted an irrational choice to approach when a prospective environment was more risky, an effect that was particularly marked in more anxious participants. The findings reveal a coupling between the content of forwards replay and rational choice behaviour, such that replay prioritises an online representation of potential reward.

THE STUDY OF SME’S PERFORMANCE IN FURNITURE CARVING INDUSTRY

The center of SMEs carving furniture in Karduluk village, Sumenep Regency in Madura, East Java which has dynamic and uncertain environment and also high level of competition. Such situation needs adequate managerial capabilities so that SME players can sustain their existence from external competition. In spite of its thriving existence, the industry has some potential problems, which need to be identified The purpose of this research is to determine the effect of the entrepreneurship orientation, the capability of business network towards the performance of SMEs through the commitment of the businessmen. This research employed quantitative analysis, which used AMOS as its method of analysis. Data collection was conducted by distributing questionnaires to 105 craftman who were also managers of craving furniture units. This research found that businessmen orientation affected the performance of carving furniture. Business networking capability affected the performance of carving furniture. Behavioral commitment had a partial mediation impact on entrepreneurship orientation towards the performance of carving furniture. Behavioral commitment had a full mediation impact on entrepreneurship orientation towards the performance of carving furniture.

Multi-Objective UAV Trajectory Planning in Uncertain Environment

UAV trajectory planning is one of the research focuses in artificial intelligence and UAV technology. The asymmetric information, however, will lead to the uncertainty of the UAV trajectory planning; the probability theory as the most commonly used method to solve the trajectory planning problem in uncertain environment will lead to unrealistic conclusions under the condition of lacking samples, while the uncertainty theory based on uncertain measures is an efficient method to solve such problems. Firstly, the uncertainties in trajectory planning are sufficiently considered in this paper; the fuel consumption, concealment and threat degree with uncertain variables are taken as the objective functions; the constraints are analyzed according to the maneuverability; and the uncertain multi-objective trajectory planning (UMOTP) model is established. After that, this paper takes both the long-term benefits and its stability into account, and then, the expected-value and standard-deviation efficient trajectory model is established. What is more, this paper solves the Pareto front of the trajectory planning, satisfying various preferences, which avoids the defects of the trajectory obtained by traditional model only applicable to a certain specific situation. In order to obtain a better solution set, this paper proposes an improved backbones particle swarm optimization algorithm based on PSO and NSGA-II, which overcomes the shortcomings of the traditional algorithm such as premature convergence and poor robustness, and the efficiency of the algorithm is tested. Finally, the algorithm is applied to the UMOTP problem; then, the optimal trajectory set is obtained, and the effectiveness and reliability of the model is verified.

Models for MADM with hesitant interval-valued fuzzy information under uncertain environment

This paper is a research of interval-valued fuzzy and Muirhead Mean algorithms. We deduced new algorithms named as hesitant interval-valued fuzzy Muirhead Mean (HIVFMM) and hesitant interval-valued fuzzy Muirhead Mean (HIVFWMM) with Muirhead Mean algorithms based on Hesitant interval-valued fuzzy set (HIVFS). Firstly, we introduced some concepts and operation laws of HIVFS and the formula form of MM, then we combined them both and gave the proof process of properties and theorems, a mathematic model applying to MADM and a numerical example was given to illustrate the effectively and practically.

A Novel Depreciation Approach in an Uncertain Environment: Interval Type-2 Fuzzy Sets in Maritime

This study aims to propose a novel model for the determination of depreciation in an environment of uncertainty. In the study, amortization methods were revised through Interval Type-2 Fuzzy (IT2FSs), and a new approach was proposed for investors to make decisions in an environment of cash flow is uncertainty. In the study, we provide options among different depreciation alternatives in the future investment decisions of maritime companies through the revision of the straight-line depreciation method and the double-declining balance depreciation method. The fuzzy depreciation alternatives we suggest in our study are not only suitable for maritime companies, but also companies in different industries.