In this paper, we propose a simple heuristic approach for the inventory control problem with stochastic demand and multiplicative random yield. Our heuristic tries to find the best candidate within a class of policies which are referred to in the literature as the linear inflation rule (LIR) policies. Our approach is computationally fast, easy to implement and intuitive to understand. Moreover,...

Motivated by the problem of packing Virtual Machines on physical servers in the cloud, we study the problem of one-dimensional online stochastic bin packing. Items with sizes sampled independent and identically (i.i.d.) from a distribution with integral support arrive as a stream and must be packed on arrival in bins of size B, also an integer. The size of an item is known when it arrives and t...

it is assumed in most of the existing models that the items can be stored for an unlimited time to meet the future’s demand and their quality and quantity does not change during that period. nevertheless there are special kinds of products which deteriorate or become unusable (such as food products, alcohol, medicines, etc.). therefore if the rate of deterioration is significantly high, the imp...

Two types of decisions that directly affect the performance of a distribution system is the vehicle routing and inventory assignment. These problems have been studied separately for many years. The inventory routing problem (IRP) is integration of above mentioned distribution problems. In the other words, IRP assumes each customer maintains a local inventory of a product and consumes a certain ...

task assignment problem (tap) involves assigning a number of tasks to a number of processors in distributed computing systems and its objective is to minimize the sum of the total execution and communication costs, subject to all of the resource constraints. tap is a combinatorial optimization problem and np-complete. this paper proposes a hybrid meta-heuristic algorithm for solving tap in a h...

this paper deals with a multi-period fixed charge production-distribution problem associated with backorder and inventories. the objective is to determine the size of the shipments from each supplier and backorder and inventories at each period, so that the total cost incurred during the entire period towards production, transportation, backorder and inventories is minimised. a 0-1 mixed intege...

This paper proposes the strategy of optimizing constrained multi-item inventory problems under fuzzy environment using a Genetic Algorithm (GA). The GA is used in the sense that it is computationally simple yet powerful in its search for improvement. The typical inventory analysis is sensitive to reasonable errors in the measurement of relevant inventory costs. Therefore the inventory costs are...

Transportation sector generates a considerable part of each nation's gross domestic product and considered among the largest consumers of oil products in the world. This paper proposes a heuristic method for the vehicle routing problem with hard time windows while incorporating the costs of fuel, driver, and vehicle. The proposed heuristic uses a novel speed optimization algorithm to reach its ...

Expected inventory order crossovers occur if at the moment of ordering it is expected that orders will not arrive in the sequence they are ordered. Recent research has shown that (a) expected inventory order crossovers will be encountered more frequently in future, and that (b) use of a myopic order-up-to policy based on a stochastic dynamic programming approach leads to improved performance co...

The purpose of this article is to review the literature on the topic of deterministic vehicle routing problem (VRP) and to give a review on the exact and approximate solution techniques. More specifically the approximate (meta-heuristic) solution techniques are classified into: tabu search, simulated annealing, genetic algorithm, evolutionary algorithm, hybrid algorithm, and Ant Colony Opti...