In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time.

The design and operation of high volume conveyor systems in distribution centers are important due to its high cost, large footprint and critical role in the system. However, there is no analytical model available. In this paper, we study the characteristics of the conveyor sortation system, develop a generic model of a complex conveyor network. We then use the Delay and Stock abstraction to develop an approximate analytical method using sample path analysis and dynamic network flow model. The decision variables include length of accumulation segments and the speeds of conveyor components aforementioned decision variables. This analytical solution provides faster analysis, insights and useful subgradient with respect to the decision variables.

We first propose a series of similarity measures for intuitionistic fuzzy values (IFVs) based on the intuitionistic fuzzy operators (Atanassov 1995). The parameters in the proposed similarity measures can control the degree of membership and the degree of non-membership of an IFV, which can reflect the decision maker’s risk preference. Moreover, we can obtain some known similarity measures when some fixed values are assigned to the parameters. Furthermore, we apply the similarity measures to aggregate IFVs and develop some aggregation operators, such as the intuitionistic fuzzy dependent averaging operator and the intuitionistic fuzzy dependent geometric operator, whose prominent characteristic is that the associated weights only depend on the aggregated intuitionistic fuzzy arguments and can relieve the influence of unfair arguments on the aggregated results. Based on these aggregation operators, we develop some group decision making methods, and finally extend our results to interval-valued intuitionistic fuzzy environment.

A challenging problem in real world logistics applications consists in planning service territories for customer deliveries, in contexts where customers must be clustered into groups that satisfy various conditions such as balance and connectivity. In this paper we propose new algorithms for producing such clusters based upon special procedures for exploiting Thiessen polygons. Our methods are able to handle multiple criteria for balancing the clusters, such as the number of customers in each cluster, the service revenue in each cluster, or the delivery/pickup quantity in each cluster. Computational results demonstrate the efficacy of our new procedures, which are able to assist users to plan service personal service territories and vehicle routes more efficiently.

Most inventory researches assume that production level can fluctuate arbitrarily. However, large fluctuation of the production level in many firms may be much costly. This paper addresses the coordinating pricing and inventory control problem in a bounded production system with uncertain yield, in which the production level is constrained between a maximum and minimum level in each period and the price can be adjusted dynamically. We show that the optimal policy is the interval base-stock-list-price policy. Also, we study the impact of the production bounds and uncertainty of the yield on the production system. Numerical experiments are also performed to study the impact of parameters on the system.

We study an M/PH/1 queue with phase type working vacation and vacation interruption where the vacation time follows a phase type distribution. The server serves the customers at a lower rate in a vacation period. The server comes back to the regular busy period at a service completion without completing the vacation. Such policy is called vacation interruption. In terms of quasi birth and death process and matrix-geometric solution method, we obtain the stationary queue length distribution. Moreover we obtain the conditional stochastic decomposition structures of queue length and waiting time when the service time distribution in the regular busy period is exponential.

This note points outs the inappropriateness of an accuracy function introduced by Ye [Ye, J. (2009). Multicriteria fuzzy decision-making method based on a novel accuracy function under interval-valued intuitionistic fuzzy environment. Expert Systems with Applications, 36 (3): 6899–6902] and its misleading use for comparing two interval-valued intuitionistic fuzzy numbers.