Fuzzy Application to the Analytic Hierarchy Process for Robot Selection

The problem of Robot Selection is of great relevance in the present times of automation. Traditionally such problems were addressed using conventional techniques of Multi Criteria Decision Making such as The Analytic Hierarchy Process (AHP) and The Multi Attribute Utility Theory (MAUT). This paper proposes a methodology for solving common Robot Selection problems using a modification of the conventional AHP by incorporating ‘Fuzzy Linguistic Variables’ in place of numbers. The methodology encapsulates creation of Fuzzy Interface for conversion of input and output variables into suitable linguistic variables. Further, employing the fuzzification process by assigning the linguistic variables to numerical values of the membership functions and formulating suitable decision rules, the procedure culminates into the defuzzification process for converting fuzzy output into crisp value and obtaining the result in the form of Fuzzy Score. The proposed model is explained using a numerical example. The paper also presents a validation of the proposed methodology over real world problems and provides directions for future research towards the end.Additional support was provided by the National Science Foundation.     

从Hückel分子轨道理论导出激发态周环反应的奇偶定则

本文从Huckel分子轨道理论,导出激发态周环反应的奇偶定则。在推导中Huckel久期行列式的非零元均视为反应坐标的函数,对其数值不作特殊假定。本文的推导也有助于对周环反应的Mobius-Huckel结构理论获得进一步的了解。     

Optimizing inventory decisions in a two-level supply chain with order quantity constraints

A fundamental assumption in traditional inventory models is that all of the ordered items are of perfect quality. A two-level supply chain is considered consists of one retailer and a collection of suppliers that operate within a finite planning horizon, including multiple periods, and a model is formulated that simultaneously determines both supplier selection and inventory allocation problems in the supply chain. It is supposed that the ordered products dependent on the suppliers include a certain percentage of imperfect quality products and have different prices. In this paper, we study the impact of the retailer’s financial constraint. On the other hand, suppliers have restricted capacities and set minimum order quantity (MOQ) policy for the retailer’s order amount happened in each period. So, the problem is modeled as a mixed integer nonlinear programming. The purpose of this model is to maximize the total profit. The nutrients, fishery and fruitage industries give good examples for the proposed model. A numerical example is presented to indicate the efficiency of the proposed model. Considering the complexity of the model, a genetic algorithm (GA) is presented to solve the model. We demonstrate analytically that the proposed genetic algorithm is suitable in the feasible situations.     

Model selection method based on maximal information coefficient of residuals

The traditional model selection criterions try to make a balance between fitted error and model complexity. Assumptions on the distribution of the response or the noise, which may be misspecified, should be made before using the traditional ones. In this article, we give a new model selection criterion, based on the assumption that noise term in the model is independent with explanatory variables, of minimizing the association strength between regression residuals and the response, with fewer assumptions. Maximal Information Coefficient (MIC), a recently proposed dependence measure, captures a wide range of associations, and gives almost the same score to different type of relationships with equal noise, so MIC is used to measure the association strength. Furthermore, partial maximal information coefficient (PMIC) is introduced to capture the association between two variables removing a third controlling random variable. In addition, the definition of general partial relationship is given.     

Integrating effective flexibility measures into a strategic supply chain planning model

This paper develops models for capacity, product mix, distribution and input supply flexibility and integrates them in a strategic level, mixed integer supply chain (SC) planning model as a way of addressing demand and supply uncertainty, as well as improving market responsiveness. Capacity flexibility is modeled via the SC’s production capacity planning to address budgeted demand and ensure the fulfillment of prospective demand increases when considering various market scenarios. This model selects an optimal number of products from fast moving and extended product range options—based on the product mix flexibility. The model confirms a quick response to a changing marketplace by considering elements like transportation and supply lead time along with the probabilities of stock out options when addressing input supply and distribution flexibility. This paper proposes a solution procedure to solve the model for real world problems, and investigates the sensitivity of the model outputs with respect to changes in flexibility measures.     

Competitive strategies and market segmentation for suppliers with substitutable products

This research studies the competition between two coexisting suppliers in a two-echelon supply chain. The suppliers have different inventory cost structures (holding cost and setup cost). Each supplier offers one type of the two substitutable products to multiple buyers. Buyers’ preferences between the substitutable products differ. Each buyer has a particular order profile (order frequency and quantity). A buyer chooses between the suppliers based on the prices offered by both suppliers and his/her own preference. A Hotelling-type model is used to describe buyers’ preferences for the products. We are able to describe the conditions for buyers to switch between the suppliers, and therefore spot the buyer groups that may or may not switch when the suppliers compete. Pricing strategies for different buyer groups are suggested to the competitive suppliers accordingly. Furthermore, equilibrium prices, market segments, and overall profits for the suppliers are revealed based on Game Theory. An algorithm is also proposed to forecast buyers’ reactions to suppliers’ pricing strategies given the buyers’ order profiles and preferences between the substitutable products.     

Production control and replenishment strategy with multiple suppliers

This paper considers the joint supplier selection, replenishment and manufacturing control problem in a dynamic stochastic context. This problem is characterized by conflicting interests between suppliers, the manufacturer, and clients, which raise the need for coordination and information sharing. This paper contributes to the discourse mainly by developing and resolving an integrated mathematical model leading to information sharing strategies for supplier selection, replenishments and production activities. This is an optimal control problem with state constraints and hybrid dynamics. A dynamic stochastic model is thus proposed, and the optimality conditions obtained are then solved numerically. It is shown that the problem considered leads to a modified state-dependent multi-level (s, S) policy for the supplier selection and replenishment strategy and a base-stock policy for the production activities. The fact that these control policies are coupled confirms the necessity of considering the interactions present in the system in an integrated model. The obtained results show clearly that it is always profitable to consider multiple suppliers to make replenishment and production decisions. Moreover, it is shown that the availability rates of the supply chain actors and the replenishment lead time are important parameters to consider when choosing the best supplier.     

Display Selection of a Hybrid Foldamer–Peptide Macrocycle

Expanding the chemical diversity of peptide macrocycle libraries for display selection is desirable to improve their potential to bind biomolecular targets. We now have implemented a considerable expansion through a large aromatic helical foldamer inclusion. A foldamer was first identified that undergoes flexizyme-mediated tRNA acylation and that is capable of initiating ribosomal translation with yields sufficiently high to perform an mRNA display selection of macrocyclic foldamer–peptide hybrids. A hybrid macrocyclic nanomolar binder to the C-lobe of the E6AP HECT domain was selected that showed a highly converged peptide sequence. A crystal structure and molecular dynamics simulations revealed that both the peptide and foldamer are helical in an intriguing reciprocal stapling fashion. The strong residue convergence could be rationalized based on their involvement in specific interactions with the target protein. The foldamer stabilizes the peptide helix through stapling and through contacts with key residues. These results altogether represent a significant extension of the chemical space amenable to display selection and highlight possible benefits of inserting an aromatic foldamer into a peptide macrocycle for the purpose of protein recognition.     

西藏“一江两河”流域主栽品种青稞对土壤重金属的积累特性研究

农业环境重金属污染会带来潜在的农产品质量安全风险,不同品种的作物在重金属积累能力方面存在显著的差异,通过种植低富集品种可以一定程度阻断有毒重金属向人体转移的途径。西藏“一江两河”流域部分农田的重金属污染问题是当地迫切需要解决的问题,同时青稞是西藏地区主要的农作物之一。因此本研究选用目前“一江两河”流域广泛种植的9种不同的青稞品种为筛选对象,以汞(Hg)、铬(Cr)、砷(As)、铅(Pb)、镉(Cd)为主要参数对象,利用电感耦合等离子体质谱(ICP-MS)方法进行检测。通过该流域土壤中As的高含量证实了该地区存在的重金属污染情况,利用富集系数和转运系数分析分别筛选出一些低富集或低转运能力的青稞品种,最后结合聚类分析,确定藏青320品种是最适合“一江两河”流域推广种植,且具备根部重金属高积累,茎、叶、籽粒低积累特性的青稞品种。