Improving Solutions of a Class of Allocation Problems by Cyclic Shifts of Resources

1981 ◽  
Vol 32 (5) ◽  
pp. 401-404 ◽  
Author(s):  
John M. Einbu
Keyword(s):  
Allocation Problems ◽  
Cyclic Shifts

A Forward-Solving Numerical Technique for Dynamic Consumption and Portfolio Allocation Problems

2005 ◽  
Author(s):  
George Chacko ◽  
Maxim Golts ◽  
Mihir A. Desai ◽  
Vladimir Novakovsky
Keyword(s):  
Numerical Technique ◽  
Portfolio Allocation ◽  
Allocation Problems

Complexity of Allocation Problems in Spectrum Markets with Interference Complementarities

2013 ◽  
Vol 31 (3) ◽  
pp. 489-499 ◽  
Author(s):  
Hang Zhou ◽  
Randall Berry ◽  
Michael L. Honig ◽  
Rakesh Vohra
Keyword(s):  
Allocation Problems ◽  
Spectrum Markets

scholarly journals Healthcare Facility Location-Allocation Optimization for China’s Developing Cities Utilizing a Multi-Objective Decision Support Approach

2018 ◽  
Vol 10 (12) ◽  
pp. 4580 ◽  
Author(s):  
Li Wang ◽  
Huan Shi ◽  
Lu Gan
Keyword(s):  
Heuristic Algorithms ◽  
Programming Model ◽  
Rapid Development ◽  
Supply And Demand ◽  
Healthcare Facility ◽  
Allocation Model ◽  
Location Allocation ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Allocation Problems

With rapid development of the healthcare network, the location-allocation problems of public facilities under increased integration and aggregation needs have been widely researched in China’s developing cites. Since strategic formulation involves multiple conflicting objectives and stakeholders, this paper presents a practicable hierarchical location-allocation model from the perspective of supply and demand to characterize the trade-off between social, economical and environmental factors. Due to the difficulties of rationally describing and the efficient calculation of location-allocation problems as a typical Non-deterministic Polynomial-Hard (NP-hard) problem with uncertainty, there are three crucial challenges for this study: (1) combining continuous location model with discrete potential positions; (2) introducing reasonable multiple conflicting objectives; (3) adapting and modifying appropriate meta-heuristic algorithms. First, we set up a hierarchical programming model, which incorporates four objective functions based on the actual backgrounds. Second, a bi-level multi-objective particle swarm optimization (BLMOPSO) algorithm is designed to deal with the binary location decision and capacity adjustment simultaneously. Finally, a realistic case study contains sixteen patient points with maximum of six open treatment units is tested to validate the availability and applicability of the whole approach. The results demonstrate that the proposed model is suitable to be applied as an extensive planning tool for decision makers (DMs) to generate policies and strategies in healthcare and design other facility projects.

scholarly journals A Building-Block-Based Genetic Algorithm for Solving the Robots Allocation Problem in a Robotic Mobile Fulfilment System

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Jingtian Zhang ◽  
Fuxing Yang ◽  
Xun Weng
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Scheduling ◽  
Building Blocks ◽  
Allocation Problem ◽  
Accurate Analysis ◽  
Allocation Problems ◽  
Scheduling Method ◽  
Project Scheduling Problem ◽  
Block Based ◽  
Better Than

Robotic mobile fulfilment system (RMFS) is an efficient and flexible order picking system where robots ship the movable shelves with items to the picking stations. This innovative parts-to-picker system, known as Kiva system, is especially suited for e-commerce fulfilment centres and has been widely used in practice. However, there are lots of resource allocation problems in RMFS. The robots allocation problem of deciding which robot will be allocated to a delivery task has a significant impact on the productivity of the whole system. We model this problem as a resource-constrained project scheduling problem with transfer times (RCPSPTT) based on the accurate analysis of driving and delivering behaviour of robots. A dedicated serial schedule generation scheme and a genetic algorithm using building-blocks-based crossover (BBX) operator are proposed to solve this problem. The designed algorithm can be combined into a dynamic scheduling structure or used as the basis of calculation for other allocation problems. Experiment instances are generated based on the characteristics of RMFS, and the computation results show that the proposed algorithm outperforms the traditional rule-based scheduling method. The BBX operator is rapid and efficient which performs better than several classic and competitive crossover operators.

The implementation of capital budgeting analysis for distributed generation allocation problems

2015 ◽  
Vol 97 (3) ◽  
pp. 225-238 ◽  
Author(s):  
Rene Prenc ◽  
Davor Škrlec ◽  
Marijana Živić Đurović
Keyword(s):  
Distributed Generation ◽  
Capital Budgeting ◽  
Allocation Problems
Sign in / Sign up

Export Citation Format

Share Document