Neutrosophic sets have been commenced as a generalization of crisp, fuzzy and intuitionistic fuzzy sets to depict vague, incompatible and deficient information about a real world dilemma. Interval-valued fuzzy sets have widely been acknowledged as more proficient in modeling suspicions and practical in assigning an interval of values where allotting an accurate and precise number to an expert’s outlook is too restrictive. They endow with a more appropriate background to characterize higher order of uncertainties and fuzziness of real world. To solve linear programming network problems with constraints concerning interval-valued neutrosophic numbers, a technique has been established by using score function and upper and lower membership functions of interval-valued neutrosophic numbers. An application of energy scheduling problem with constraints represented as interval-valued trapezoidal neutrosophic numbers has been discussed and solved via this technique. Also an additional example to exemplify the proposed method by implementing it on minimum spanning tree and shortest path problem is employed. Furthermore, a comparative examination was performed to validate the effectiveness and usefulness of the projected methodology.

中智集已经开始作为对清晰，模糊和直觉模糊集的概括，以描述关于现实困境的模糊，不兼容和不足的信息。区间值模糊集被公认为在建模怀疑方面更加熟练，并且在分配值的区间时非常实用，而在这种区间中，为专家的观点分配准确和精确的数字过于严格。他们具有更合适的背景，可以表征现实世界中更高级别的不确定性和模糊性。为了解决关于区间值中智数的约束的线性规划网络问题，已经建立了一种利用得分函数以及区间值中智数的上下隶属函数的技术。已经讨论并通过这种技术解决了以约束为间隔值梯形中智数的约束的能量调度问题的应用。另外，通过在最小生成树和最短路径问题上实施该方法来举例说明所提出的方法。此外，进行了比较检查以验证所预测方法的有效性和实用性。