A Simulation Model to Analyze an Inventory System for Deteriorating Items with Service Level Constraint

In this paper an inventory system for continuous decaying items with stochastic lead time and Poisson demand is assumed. Since the products are deteriorating and demand is stochastic it is possible to deliver less than customers' demand to them. Thus, a constraint is introduced which guarantees a specific service level. Shortages are allowed and all the unsatisfied demands are backlogged. Moreover, replenishment is one for one. Our objective is to minimize the expected long-run total cost of the inventory system. Since the stochastic lead time and service level constraint make the analytical model extremely complicated, simulation modeling approach is applied. The simulation model is validated by statistical hypothesis test for the deterministic lead time case. Then the optimizer module of the simulation software is used to find near optimal solutions for a number of examples with stochastic lead time

Determination of start times and ordering plans for two-period projects with interdependent demand in project-oriented organizations: A case study on molding industry

The objective of the present study is to determine the start times and ordering plans for two-period projects in project-oriented organizations. The following assumptions are made: orders can be placed in either of a project’s two consecutive periods; and the same raw materials are used, which are ordered at the start of the periods according to their interdependent demands. The main innovation of the present research is to develop a model that is mainly based on the two-period newsvendor problem, but assumes that demand is interdependent, i.e. it is actually a combination of inventory and project management. After presenting the model, numerical meth-ods are used to approximate the order quantities for each period. Near-optimal solutions of a numerical example, in a case study on molding industry, are obtained using a genetic algorithm. Results show that the proposed model with interdependent demand provides a better solution than independent demand. The model is applicable to large-scale industrial and construction pro-jects where the majority of raw materials have of the same nature

INTERDEPENDENT DEMAND IN THE TWO-PERIOD NEWSVENDOR PROBLEM

The newsvendor problem is a classical task in inventory management. The present paper considers a two-period newsvendor problem where demand of different periods is interdependent (not independent), and seeks to follow this approach to develop a two-period newsvendor problem with unsatisfied demand or unsold quantity. Concerning the complexity of solution of multiple integrals, the problem is assessed for only two periods. In the course of a numerical solution, the probability distribution function of demand pertaining to each period is assumed to be given (in the form of a bivariate normal distribution). The optimal solution is presented in the form of the initial inventory level that maximizes the expected profit. Finally, all model parameters are subjected to a sensitivity analysis. This model can be used in a number of applications, such as procurement of raw materials in projects (e.g., construction, bridge-building and molding) where demand of different periods is interdependent. Proposed model takes into account interdependent demand oughts to provide a better solution than a model based on independent demand

Analyzing A Stochastic Inventory System For Deteriorating Items With Stochastic Lead Time Using Simulation Modeling

We consider an inventory system for continuous decaying items with stochastic lead time and Poisson demand. Shortage is allowed and all the unsatisfied demands are backlogged. Moreover, replenishment is one for one. Our objective is to minimize the long-run total expected cost of the system. Firstly, we have developed the mathematical model with deterministic lead time. Since the stochastic lead time makes the model complex especially when lead time has complicated probability distribution and it is difficult to prove convexity of the objective function, we have applied simulation modeling approach. The simulation model has no limitation on lead time or any other parameters. The simulation model is validated by comparing its outputs and analytical model\u27s results for the deterministic lead time case. Furthermore, we use optimizer module of the applied software to find near optimal solutions for a number of examples with stochastic lead time. © 2011 IEEE

Iterated Local Search Algorithm with Strategic Oscillation for School Bus Routing Problem with Bus Stop Selection

he school bus routing problem (SBRP) represents a variant of the well-known vehicle routing problem. The main goal of this study is to pick up students allocated to some bus stops and generate routes, including the selected stops, in order to carry students to school. In this paper, we have proposed a simple but effective metaheuristic approach that employs two features: first, it utilizes large neighborhood structures for a deeper exploration of the search space; second, the proposed heuristic executes an efficient transition between the feasible and infeasible portions of the search space. Exploration of the infeasible area is controlled by a dynamic penalty function to convert the unfeasible solution into a feasible one. Two metaheuristics, called N-ILS (a variant of the Nearest Neighbourhood with Iterated Local Search algorithm) and I-ILS (a variant of Insertion with Iterated Local Search algorithm) are proposed to solve SBRP. Our experimental procedure is based on the two data sets. The results show that N-ILS is able to obtain better solutions in shorter computing times. Additionally, N-ILS appears to be very competitive in comparison with the best existing metaheuristics suggested for SBR