ABSTRACT This paper studies a single server renewal input queueing model with multiple vacations in the presence of impatient customers. The server follows an exhaustive vacation policy whenever the system is empty. During vacation, waiting customers become impatient and decide independently whether to abandon the system simultaneously or avail service at the vacation completion instant. Using the supplementary variable and difference equation techniques, we obtain the steady-state system-length distributions at pre-arrival and arbitrary epochs. We present the stochastic decomposition structure for the number of customers in the system and derive several performance measures including the sojourn time. Moreover, we examine the impact of various parameters on the system performance measures. A potential application of the model in the inventory management of an e-commerce company with fresh agricultural products is illustrated. Numerical results discuss the effects of the system parameters and provide insight into the performance of such systems.

ABSTRACT Nowadays, shareholders are being encouraged to enhance supply chain risk management in order to deal with several disruptive and operational risks. Producing spice and flavor is one of the high-risk industries as the main raw material is spice and its quality is variable and strongly depends on suppliers, seeds, and climate. Having a constant quality of spices and producing a flavor that satisfies every customer’s demand is intricate. Therefore, these companies encountered a variety of goods which increased complexity and uncertainty in supply, processing time, and demand. To come up with risks and uncertainties, in this paper a robust bi-objective multi-product mathematical model is developed to consider resiliency and uncertainty in a multi-period, multi-item supply chain network design simultaneously. The first objective function maximizes total profits when the second one maximizes the total score of resiliency in which Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) have been used to obtain the four resiliency factors weights for the objective function. We proposed an approach for making coordination between production planning, distribution, supplier selection, and order allocation in a flavor plant. The -constraint method is used to obtain Pareto solutions for a real case in Iran. Finally, sensitivity analysis has been done for tracking the trade-off between optimization and robustness with different robust parameters and investigating unmet demand and benefits of resilience consideration.

ABSTRACT p-Hub location-allocation problem is one of the most interesting subjects in the location theory. Hubs act as switching points to reduce the transportation cost. In this study, two new solution methods, a constraint programming (CP) based model and a hybrid of k-means and genetic algorithm (KGA), are developed to generate exact and approximate solutions, respectively. The proposed CP formulation is more understandable and straightforward in comparison with the MIP model. The experimental results indicate that the CP model uses the memory of the computer (RAM) more efficiently, which enables us to solve the medium size problems. But, in terms of run time, this method cannot be superior to the MIP model. The CP formulation is also extended for the multi allocation p-hub location problem. K-means algorithm, a well-known algorithm for clustering data, is used to generate initial solutions of GA. Furthermore, a new adaptive crossover operator, which is based on the k-means algorithm, is proposed. The experimental results indicate that the KGA algorithm is superior to the GA, regarding time, objective value, and quality of solution measures.

ABSTRACT This paper considers an F-policy G/G/c/K queueing system with general startup times. Researchers have not yet to develop a mathematical model with which to analyze this queueing system, thereby making it difficult to obtain analytical results. In this study, we build a simulation model using ARENA software to evaluate performance measures of the system. Comparative analysis is performed using extensive computational experiments to verify the efficiency of the proposed simulation model. Moreover, we construct a cost function and use the OptQuest tool in ARENA software to find the optimal threshold F that minimizes the expected cost per unit time.

ABSTRACT An important safety-oriented feature of an automobile is brake; malfunctioning of which can lead to severe consequences. In a typical braking system for an automobile, brake booster valve body is responsible for proper functioning of system and therefore the importance of its construction is coherent. The material for constructing this valve body should be selected considering conditions of operation, usually requiring high tensile strength and ability to maintain its strength at high temperature while at the same time the material should be light and cheap. All variegated aspects in terms of economic, strength and thermal properties of the material should be considered at the time of its selection. Taking into account the involvement of such multi-dimensional factors in the ultimate choice of material for construction of brake booster valve body, a hybrid Multi-Criteria Decision Making (MCDM) methodology, the Fuzzy-Complex Proportional Assessment (COPRAS) method was taken up by the authors as a valid mechanism to tackle the problem. Usage of Fuzzy-based methodologies further adds up to the flexibility of the obtained inference. PA6-GF30 was concluded to be the most suitable material for construction of valve bodies. Similar such mechanisms can also be implemented in any study based on a criteria-based selection analogy.

ABSTRACT The main objective of this study is to develop a two-stage stochastic programming framework for lot-sizing and scheduling the production activities at a kitting facility to support a manufacturing plant. The novelty of the study lies in modeling multiple uncertainties using two-stage stochastic programming to solve a kitting specific production planning problem in a manufacturing setting. The demand for the kits and the yield of the kitting workers are the two sources of uncertainties considered in this study. The first-stage decisions include the baseline production schedule and the workforce requirement, while the second stage makes recourse decisions on overtime production. The proposed decision-making framework is validated on a multi-period, multi-product case study involving a kitting facility supporting a manufacturing plant producing braking equipment. The main conclusion of the study is that uncertainties have significant impacts on kitting planning decisions and that the proposed two-stage stochastic programming model was robust in determining optimal production plans under uncertainty.

ABSTRACT Against the backdrop of the full-blown trade war, this study investigates the price discrimination strategies and tariff policies for the dual international supply chains in trade war via game-theoretical modeling and numerical and sensitivity analyses approaches. Three key findings from the study are: (1) both the free trade and trade war scenarios are bilateral and stable, and the free trade scenario is preferable to the trade war scenario. (2) in free trade scenario, the combination of free competition strategy and ‘actionless governance’ policy forms a ‘win-win’ state, which is the best choice for all trade stakeholders from the perspective of long-term sustainable development. (3) in trade war scenario, the combination of aggressive price discrimination strategy and tit-for-tat tariff counterattack policy forms a ‘prisoner’s dilemma’ state.

ABSTRACT Open-Pit Production Scheduling (OPPS) is an NP-hard problem. In this article, Genetic Algorithm (GA) is used to encode the solutions of OPPS problem. The orebody is characterized as a three-dimensional (3D) array of blocks. Therefore, in this study, a 3D GA array is employed in the solution space of the OPPS problem to reflect the 3D feature of the real mine block model. The penalty and normalization methods are utilized for handling of the capacity and sequencing constraints, respectively. The proposed method is implemented on a Marvin orebody data set and observed a considerable improvement compared with a commercial scheduler.

ABSTRACT In developing countries like India, patients bypass primary health centers (PHCs) and visit larger hospitals for minor ailments and thereby overburden the facilities responsible for specialized consultative health care. This is an undesirable phenomenon and governments are spending more on primary care and setting up more community and primary health centers. In this article, we propose an integer linear programming model for locating PHCs with the explicit objective of reducing unwanted load on tertiary care hospitals. The model offers holistic utilization of existing and new facilities. Moreover, the question of equity in allotment of more desirable facilities which can be built only in limited numbers, is discussed for the first time. This article contributes in the following ways. It describes a decision problem which has social relevance. The dual issues of excessive uneven distribution of health service workload and equity in distribution of public resources in the context of primary care are discussed. Using the novel optimization model developed in the article, major policy directions can be derived. The implementation of this model should ensure better utilization of public money and greater service to the target population. This is also demonstrated through a small real-life case study. A heuristic algorithm has also been proposed for solving the optimization model.

ABSTRACTThis paper analyses an M/M/c queueing system with variant working vacations. The service times during regular busy periods, working vacation periods and vacation times are exponentially distributed and are mutually independent. During working vacation, customers may renege due to impatience and the impatient timer follows an exponential distribution. We derive the probability generating function of the steady-state probabilities and obtain some performance measures. The cost function associated with the model is also constructed and its optimization is investigated using quadratic fit search method. We have also presented the numerical illustrations of the effect of some parameters on the performance measures using graphs.