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While in multi-periodic inventory control problems the usual assumption are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this research, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space, budget and service level constraints, incremental discount is considered to purchase products and a combination of back-order and... 

In this article, a capacitated location allocation problem is considered in which the demands and the locations of the customers are uncertain. The demands are assumed fuzzy, the locations follow a normal probability distribution, and the distances between the locations and the customers are taken Euclidean and squared Euclidean. The fuzzy expected cost programming, the fuzzy β-cost minimization model, and the credibility maximization model are three types of fuzzy programming that are developed to model the problem. Moreover, two closed-form Euclidean and squared Euclidean expressions are used to evaluate the expected distance between customers and facilities. In order to solve the problem... 

This study solves a chance-constraint supply chain problem with stochastic demand which follows a uniform distribution. Fuzzy delay times (moving, waiting and setup time) are assumed to be lot size dependent and shortage is partially backordered. The buyer is responsible for the costs incurred in ordering, holding, shortage and transportation, while the vendor is responsible for setup and holding costs. The service rate of each product has a chance constraint and the buyer has a budget constraint. Our objective is to determine the re-order point and the order quantity of the products such that the total cost is minimized. Since the problem is uncertain integer-nonlinear, two hybrid... 

While the usual assumptions in multi-periodic inventory control problems are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this article, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming that the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space and service level constraints, total discount are considered to purchase products and a combination of back-order and lost-sales... 

This paper introduces how to incorporate fuzzy set theory with discrete-event simulation in order to model uncertain activity duration in simulating a real-world system, especially when insufficient or no sample data are available. A case study is developed to apply this method to select a scenario to implement the maintenance program in a constant work in process (CONWIP) system. The maintenance activities directly or indirectly affect on production system performance such as response time production costs and etc. so we used the fuzzy simulation to determine the maintenance affects on the system performance. Finally we used the fuzzy simulation result to develop a fuzzy multi attribute... 

In this paper, a multiproduct multi-chance constraint stochastic inventory control problem is considered, in which the time-periods between two replenishments are assumed independent and identically distributed random variables. For the problem at hand, the decision variables are of integer-type, the service-level is a chance constraint for each product, and the space limitation is another constraint of the problem. Furthermore, shortages are allowed in the forms of fuzzy random quantities of lost sale that are backordered. The developed mathematical formulation of the problem is shown to be a fuzzy random integer-nonlinear programming model. The aim is to determine the maximum level of... 

Multi-periodic inventory control problems are mainly studied by employing one of two assumptions. First, the continuous review, where depending on the inventory level, orders can happen at any time, and next the periodic review, where orders can only be placed at the beginning of each period. In this paper, we relax these assumptions and assume the times between two replenishments are independent random variables. For the problem at hand, the decision variables (the maximum inventory of several products) are of integer-type and there is a single space-constraint. While demands are treated as fuzzy numbers, a combination of back-order and lost-sales is considered for the shortages. We... 

In this paper, we develop the multi-product, multi-constraint, Single Period Problem (SPP) with uncertain demands, considering an incremental discount situation. Three new models are presented for multi-product, multi-constraint SPP in fuzzy, stochastic and rough environments. We consider constraints, such as service rate, restriction on order quantity and restrictions on warehouse space and budget. We also consider that the order quantity is a multiplier of predefined batch size. Furthermore, three kinds of solution algorithm, (1) harmony search, (2) hybrid intelligent based on harmony search and fuzzy simulation and (3) hybrid intelligent based on harmony search and rough simulation, are... 

This article introduces a methodology to integrate fuzzy multiattribute decision making (FMADM) and fuzzy simulation. According to this method, a fuzzy simulation method is applied to study the effect of different alternative on system's performance and decision criteria taking into account fuzzy inputs. Using a fuzzy analytical hierarchy process (FAHP) and the results of fuzzy simulation, a FMADM is conducted to select the best alternative. This article introduces how to incorporate fuzzy set theory with discrete-event simulation in order to model uncertain activity duration in simulating a realworld system, especially when insufficient or no sample data are available. A case study is... 

An uncertain economic order quantity (UEOQ) model with payment in advance is developed to purchase high-price raw materials. A joint policy of replenishments and pre-payments is employed to supply the materials. The rate of demand is considered LR-fuzzy variables, lead-time is taken to be constant, and it is assumed that shortage does not occur in the cycles. The cycle is divided into three parts; the first part is the time between the previous replenishment-time to the next order-time (t0), the second part is the period between t0 to a payment-time (tk), and the third part is the period between tk to the next replenishment-time. At the start of the second part (t0), α% of the purchasing...