There is an ever increasing need of providing quick, yet improved solution to dynamic scheduling by better responsiveness following simple coordination mechanism to better adapt to the changing environments. In this endeavor, a cognitive agent based approach is proposed to deal with machine failure. A Multi Agent based Holonic Adaptive Scheduling (MAHoAS) architecture is developed to frame the schedule by explicit communication between the product holons and the resource holons in association with the integrated process planning and scheduling (IPPS) holon under normal situation. In the event of breakdown of a resource, the cooperation is sought by implicit communication. Inspired by the cognitive behavior of human being, a cognitive decision making scheme is proposed that reallocates the incomplete task to another resource in the most optimized manner and tries to expedite the processing in view of machine failure. A metamorphic algorithm is developed and implemented in Oracle 9i to identify the best candidate resource for task re-allocation. Integrated approach to process planning and scheduling realized under Multi Agent System (MAS) framework facilitates dynamic scheduling with improved performance under such situations. The responsiveness of the resources having cognitive capabilities helps to overcome the adverse consequences of resource failure in a better way.

In this article, a framework is proposed to define and identify knowledge work intensity in jobs, quantitatively. For determining the Knowledge Work Intensity Score (KWIS) of a job, it is supposed that the job comprises some tasks and KWIS of the job is determined based on knowledge intensity of these tasks. Functional Job Analysis (FJA) method is applied to determine tasks of jobs and then Task’s Knowledge Intensity Score (TKIS) is computed by using Fuzzy integral method. Besides, importance weight and time weight of tasks are determined by utilizing appropriate methods. Finally, KWIS is calculated by a formula composed of tasks’ TKISs and the weights. For evaluating applicability of the framework, it is applied to calculate KWISs of two jobs (Deputy of Finance and service, Laboratory technician).

The aim of this work is to present a reliability and profit analysis of a two-dissimilar parallel unit system under the assumption that operative unit cannot fail after post repair inspection and replacement and there is only one repair facility. Failure and repair times of each unit are assumed to be uncorrelated. Using regenerative point technique various reliability characteristics are obtained which are useful to system designers and industrial managers. Graphical behaviors of mean time to system failure (MTSF) and profit function have also been studied. In this paper, some important measures of reliability characteristics of a two non-identical unit standby system model with repair, inspection and post repair are obtained using regenerative point technique.

Wind farms are designed to supply power to the consumers at a minimal price. The cost of wind power production directly or indirectly depends on proper selection of vendors. The present paper highlights a model for selection and ranking of vendors for a wind farm based on fuzzy set theory to determine criteria weights and an additive ratio assessment (ARAS) method to analysis criteria values. The objective of the paper is to establish the ARAS method as an effective method for Vendor selection. A case study is shown to ascertain the proposed method especially when the criteria are interdependent and conflicting in nature. The result is validated with another popular MCDM technique, COPRAS, which shows that the models are effective and applicable, and provide decision makers with better solutions for decision making.

Differential Search (DS) algorithm is a new meta-heuristic for solving real-valued numerical optimization. This paper introduces a new method based on DS for solving Resource Constrained Project Scheduling Problem (RCPSP). The RCPSP is aimed to schedule a set of activities at minimal duration subject to precedence constraints and the limited availability of resources. The proposed method is applied to PSPLIB case studies and its performance is evaluated in comparison with some of state of art methods. Experimental results show that the proposed method is effective. Also, it is among the best algorithms for solving RCPSP.

This study presents optimization of performance characteristics in unidirectional glass fiber reinforced plastic composites using Taguchi method and Grey relational analysis. Performance characteristics such as surface roughness and material removal rate are optimized during rough cutting operation. Process parameters including tool nose radius, tool rake angle, feed rate, cutting speed, cutting environment and depth of cut are investigated using mixed L18 orthogonal array. Grey relation analysis is used to optimize the parameters and Principal Component Analysis is used to find the relative significance of performance characteristics. Depth of cut is the factor, which has great influence on surface roughness and material removal rate, followed by feed rate. The percentage contribution of depth of cut is 54.399% and feed rate is 5.355%.

In the context of supply chain management, supplier selection plays a key role in reaching desirable production planning. In today & apos; s competitive world, many enterprises have focused on selecting the appropriate suppliers in an attempt to reduce purchasing costs and improve quality products and services. Supplier selection is a multi-criteria decision problem, which includes different qualitative and quantitative criteria such as purchase cost, on time delivery, quality of service, etc. In this study, a fuzzy multi-objective mathematical programming model is presented to select appropriate supplier and assign desirable order to different supplies. The proposed model was implemented for an organization by considering 16 different scenarios and the results are compared with two other existing methods.

This paper considers a multi-objective version of the Multiple Traveling Salesman Problem (MOmTSP). In particular, two objectives are considered: the minimization of the total traveled distance and the balance of the working times of the traveling salesmen. The problem is formulated as an integer multi-objective optimization model. A non-dominated sorting genetic algorithm (NSGA-II) is proposed to solve the MOmTSP. The solution scheme allows one to find a set of ordered solutions in Pareto fronts by considering the concept of dominance. Tests on real world instances and instances adapted from the literature show the effectiveness of the proposed algorithm.

Keeping in view the concern about environmental protection, the study investigates effects of remanufacturing in an integrated production inventory model consisting of forward and reverse supply chain over infinite planning horizon. This article is developed for the deteriorating products with stock dependent demand under shortages. To make the model more realistic, flexibility of production system has been incorporated during forward manufacturing. We derive total cost function and using the results of calculus, optimum production policy is derived, which minimizes the total cost incurred. The results are discussed with a numerical example to illustrate the theory.

The main aim of the present paper is to analyze the stochastic behavior of a cold standby system with concept of preventive maintenance, priority and maximum repair time. For this purpose, a stochastic model is developed in which initially one unit is operative and other is kept as cold standby. There is a single server who visits the system immediately as and when required. The server takes the unit under preventive maintenance after a maximum operation time at normal mode if one standby unit is available for operation. If the repair of the failed unit is not possible up to a maximum repair time, failed unit is replaced by new one. The failure time, maximum operation time and maximum repair time distributions of the unit are considered as exponentially distributed while repair and maintenance time distributions are considered as arbitrary. All random variables are statistically independent and repairs are perfect. Various measures of system effectiveness are obtained by using the technique of semi-Markov process and RPT. To highlight the importance of the study numerical results are also obtained for MTSF, availability and profit function.