The resource allocation problem for demand forecasting and performance measurement

We consider a retailer investing in two monitoring functions for unobservable demand and salesperson’s effort. We show that improving effort monitoring is more effective. Moreover, demand monitoring may be less preferable when it becomes relatively cheaper and balancing these two may be worse when they become more complementary.     

An efficient task allocation framework for scheduled data in edge based Internet of Things using hybrid optimization algorithm approach

Allocation of tasks in IoT is an integral and critical approach to finding a perfect match between scheduled tasks of a particular application and Edge-based processing devices for instant response and efficient utilization of resources to make them renewable. We need a protocol to help optimize the problem of allocating processing devices to the tasks, as task allocation is considered an NP-hard problem to prevent problems with energy consumption and response time problems. For this, a hybrid bio-inspired Swarm-based approach will improve the solution to optimize the matching of a task to a particular device. This paper proposed a Meta-heuristic algorithm to optimize Energy and Time-delay for allocating tasks to the edge-based Processing device in IoT. The proposed algorithm called the Hybrid Artificial Bee Colony whales Optimization algorithm (HAWO) is formulated by integrating Artificial Bee Colony with the Whales Optimization algorithm to overcome the search process of an Artificial Bee Colony, which converges too soon due to the local search of Employee Bee phase and Onlooker Bee phase causing the problem of looping. From the simulation results conducted in Matlab, it is observed that the integrated HAWO method shows promising results in terms of Energy and Time Delay when compared with Artificial Bee Colony and Whales Optimization algorithms separately. Also, proposed method when compared with the benchmark work shows significant improvements of 50%, 25% and 60% in terms of Energy, Time Delay and Best cost, respectively.     

沿海港口集装箱空箱调运策略优化模型

我国沿海港口进出口箱分布非常不均衡,由此产生了集装箱空箱调运现象,合理的空箱调运策略能够有效地降低航运成本。本文研究了沿海港口间的空箱调运问题。在传统确定目的港策略的基础上,提出了一种新的空箱调运策略,不确定目的港策略。针对两种不同调运策略分别建立了以总调运费用最小为目标的规划模型。并以中国沿海港口空箱调运为例,运用遗传算法,在不同的空箱供需情况下,对两种调运策略费用进行了优化求解。结果表明,供需平衡模式下,固定目的港策略略有优势;在供需不平衡模式中,不确定目的港策略优势更加明显。此研究能够为港口间空箱调运提供辅助决策。     

How many samples does it take to see all the balls in an urn?

Let an urn containN balls, numbered from 1 toN. A random number of balls are drawn without replacements from the urn, their numbers are noted and the balls are then returned to the urn. This is done repeatedly, the sample sizes being independent identically distributed. Letv be the number of samples needed to see all the balls. A simple approximation forEv and the asymptotic distribution ofv asN are obtained.Translated fromMatematicheskie Zametki, Vol. 64, No. 1, pp. 58–63, July, 1998.This research was supported by the Russian Foundation for Basic Research under grant No. 97-01-00387.     

图书采购流程中资金分配模型研究

本应用现代经济理论的择优分配原理，在图书产出效益函数的性质探讨的基础上，将效益函数的约束条件转化为对资金变量的约束条件，从而简化了资金分配方案的求解。提出了资金在各类别图书中的分配模型，指导图书馆图书采购工作。     

Analytical models for supplier selection and order quantity allocation

In the literature, decision models and techniques for supplier selection do not often consider inventory management of the items being purchased as part of the analysis. In this article, two mixed integer nonlinear programming models are proposed to select the best set of suppliers and determine the proper allocation of order quantities while minimizing the annual ordering, inventory holding, and purchasing costs under suppliers’ capacity and quality constraints. The first model allows independent order quantities for each supplier while the second model restricts all order quantities to be of equal size, as it would be required in a multi-stage (supply chain) inventory model. Illustrative examples are used to highlight the advantages of the proposed models over a previous model introduced in the literature.     

Resource allocation in rooted trees for VLSI applications

ABSTRACT

Several optimization problems of modifying the weight of vertices in rooted trees, some of which are special cases of the inverse 1-median problem, are solved. Such problems arise in Very Large Scale Integration (VLSI) design of hardware security circuits, circuit synchronization, and analog-to-digital converters. These problems require assigning costly hardware (demands) to the leaves of rooted trees. One common property of these problems is that a resource allocated to an internal node can be shared by the entire sub-tree emanated at the node. Two types of problems are studied here. (1) A tree node employs an addition operation and the demands at the leaves are obtained by summing the resources allocated to nodes along the root-to-leaf paths. A linear-time bottom-up algorithm is shown to minimize the total resources allocated to tree nodes. (2) A tree’s node employs a multiplication operation and the demands at the leaves are obtained by multiplying the resources allocated to nodes along the root-to-leaf paths. A bottom-up dynamic programming algorithm is shown to minimize the total resources allocated to the tree’s nodes. While the above problems are usually solved by design engineers heuristically, this paper offers optimal solutions that can be easily programmed in CAD tools.     

一类带时间窗车辆分配问题的贪婪算法

本文对一类带时间窗的车辆分配问题进行了分析,引入了车辆任务的概念,并将问题转化为车辆与车辆任务的匹配问题,同时制订了运输任务选择和车辆选择的贪婪策略,并在此基础上设计了车辆分配问题的贪婪算法,最后通过实例验证了算法的有效性。     

A polynomial expression for the Owen value in the maintenance cost game

The class of maintenance cost games was introduced in 2000 to deal with a cost allocation problem arising in the reorganization of the railway system in Europe. The main application of maintenance cost games regards the allocation of the maintenance costs of a facility among the agents using it. To that aim it was first proposed to utilize the Shapley value, whose computation for maintenance cost games can be made in polynomial time. In this paper, we propose to model this cost allocation problem as a maintenance cost game with a priori unions and to use the Owen value as a cost allocation rule. Although the computation of the Owen value has exponential complexity in general, we provide an expression for the Owen value of a maintenance cost game with cubic polynomial complexity. We finish the paper with an illustrative example using data taken from the literature of railways management.     

Inventory allocation and shipping when demand temporarily exceeds production capacity

We address the concept of an integrated inventory allocation and shipping model for a manufacturer with limited production capacity and multiple types of retailers with different backorder/waiting and delivery costs. The problem is to decide how to allocate and deliver produced items when the total retailer demand exceeds the production capacity, so that total retailer backorder and delivery costs are minimized. Our analytical model provides optimal allocation and shipping policies from the manufacturer’s viewpoint. We also investigate the allocation strategy of a manufacturer competing with other retailers to directly sell to end consumers.