Logistics support planning model in the conditions of limited resources

Introduction/purpose: The paper presents a model of logistics support planning in the conditions of limited logistic resources based on the prioritization of customer requirements and resource allocation. Decisionmakers play a crucial role in the efficient and equitable allocation of resources as they prioritize among different user requirements. Methods: Requirement prioritization techniques that use nominal scale, ordinal scale, and ratio scale, and five methods for converting ranks into weighting coefficients have been applied to determine the degree of significance of user requirements. The Requirements triage method has been used for establishing relative priorities, while the heuristic algorithm determining the Kemeny median was used to consolidate individually ranked requests into a group rank. In order to balance opposing demands of users, consensus measures of group decision making were used. For obtaining an optimal planned solution of logistic support, the methods and techniques of resource allocation were applied. Results: A model for adaptive planning of logistics support in the conditions of limited resource capacities of the logistics system has been developed. Conclusion: The proposed model can be effectively applied in other areas of resource allocation.

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An Optimized Mathematical Model for Items Supplies Planning of a Logistic System

Modern Applied Science ◽

10.5539/mas.v10n10p133 ◽

2016 ◽

Vol 10 (10) ◽

pp. 133

Author(s):

Mohammad Ali Nasiri Khalili ◽

Mostafa Kafaei Razavi ◽

Morteza Kafaee Razavi

Keyword(s):

Mathematical Model ◽

Mixed Integer ◽

Logistics System ◽

Proposed Model ◽

Multiple Objective Decision Making ◽

System Requirements ◽

Purchasing Logistics ◽

The Cost ◽

The Mathematical Model ◽

First Time

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.

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The Integrated Networks Model: Explaining Resource Allocations in Network Markets

Journal of Marketing ◽

10.1509/jmkg.67.1.29.18586 ◽

2003 ◽

Vol 67 (1) ◽

pp. 29-45 ◽

Cited By ~ 110

Author(s):

Judy K. Frels ◽

Tasadduq Shervani ◽

Rajendra K. Srivastava

Keyword(s):

Resource Allocation ◽

Value Added ◽

Information Technology Professionals ◽

Integrated Networks ◽

Windows Nt ◽

Proposed Model ◽

Network Markets ◽

Business Customers ◽

The Relationship ◽

Allocation Decisions

The last decade has witnessed a shift from a focus on the value created by a single firm and product to an examination of the value created by networks of firms (or product ecosystems) in which assets are comingled with external entities. The authors examine these market-based assets in the context of network markets and propose an Integrated Networks model in which three types of networks—user, complements, and producer—add value or enhance the attractiveness of the associated focal product. The authors empirically test the proposed model by surveying information technology professionals on their resource allocation decisions regarding the Unix and Windows NT operating systems. The findings suggest that the value added by these three networks is significantly and positively associated with resources allocated by business customers to competing products. The results also show that the three networks mediate the relationship between stand-alone product performance and resource allocation.

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Cuckoo optimization algorithm in reverse logistics: A network design for COVID-19 waste management

Waste Management & Research ◽

10.1177/0734242x211003947 ◽

2021 ◽

pp. 0734242X2110039

Author(s):

Elham Shadkam

Keyword(s):

Waste Management ◽

Network Design ◽

Optimization Algorithm ◽

Reverse Logistics ◽

Heuristic Algorithms ◽

Programming Model ◽

Fixed Costs ◽

Logistics System ◽

Cuckoo Optimization Algorithm ◽

Proposed Model

Today, reverse logistics (RL) is one of the main activities of supply chain management that covers all physical activities associated with return products (such as collection, recovery, recycling and destruction). In this regard, the designing and proper implementation of RL, in addition to increasing the level of customer satisfaction, reduces inventory and transportation costs. In this paper, in order to minimize the costs associated with fixed costs, material flow costs, and the costs of building potential centres, a complex integer linear programming model for an integrated direct logistics and RL network design is presented. Due to the outbreak of the ongoing global coronavirus pandemic (COVID-19) at the beginning of 2020 and the consequent increase in medical waste, the need for an inverse logistics system to manage waste is strongly felt. Also, due to the worldwide vaccination in the near future, this waste will increase even more and careful management must be done in this regard. For this purpose, the proposed RL model in the field of COVID-19 waste management and especially vaccine waste has been designed. The network consists of three parts – factory, consumers’ and recycling centres – each of which has different sub-parts. Finally, the proposed model is solved using the cuckoo optimization algorithm, which is one of the newest and most powerful meta-heuristic algorithms, and the computational results are presented along with its sensitivity analysis.

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A Multiobjective Allocation Model for Emergency Resources That Balance Efficiency and Fairness

Mathematical Problems in Engineering ◽

10.1155/2018/7943498 ◽

2018 ◽

Vol 2018 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Yanyan Wang ◽

Baiqing Sun

Keyword(s):

Resource Allocation ◽

Particle Swarm Optimization ◽

Particle Swarm ◽

Allocation Model ◽

Swarm Optimization ◽

Emergency Relief ◽

Resource Allocation Model ◽

Proposed Model ◽

Emergency Resource

Efficiency and fairness are two important goals of disaster rescue. However, the existing models usually unilaterally consider the efficiency or fairness of resource allocation. Based on this, a multiobjective emergency resource allocation model that can balance efficiency and fairness is proposed. The object of the proposed model is to minimize the total allocating costs of resources and the total losses caused by insufficient resources. Then the particle swarm optimization is applied to solve the model. Finally, a computational example is conducted based on the emergency relief resource allocation after Ya’an earthquake in China to verify the applicability of the proposed model.

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Digital transformation and optimization models in the sphere of logistics

SHS Web of Conferences ◽

10.1051/shsconf/20184400009 ◽

2018 ◽

Vol 44 ◽

pp. 00009

Author(s):

Vladimir Anisimov ◽

Evgenii Anisimov ◽

Tatiana Saurenko ◽

Artem Smolenskiy ◽

Oleg Yastrebov

Keyword(s):

Wide Spectrum ◽

Optimization Procedure ◽

Transportation Systems ◽

Digital Transformation ◽

Key Factors ◽

Optimal Plan ◽

Logistics System ◽

Proposed Model ◽

Challenging Tasks ◽

Discrete Programming

The efficiency, optimization, speed and time limits have always been of crucial importance for the logistics system, while saving of speed and time in the real-time mode are the key factors with transition to digital technologies and establishment of Industry 4.0 since they become the competitive advantages. The innovative use of technologies in such fields as data analysis, Internet of things and cloud calculations significantly change the logistical and transportation systems as a result of mating digital and existing supply chains becoming the catalyst of transition to “Logistika 4.0”. This work offers a model and method of shaping an optimal plan of fulfilling a complex of interrelated logistical operations for such changing conditions.The model is based on the presentation of optimization procedure as a non-linear task of discrete programming consisting in minimization of time of fulfilling the above complex of operations by a limited number of contractors partially interchangeable under conditions of limited budgeting. A model obtained thereat for establishing an optimal plan will belong to the class of nonpolynimially challenging tasks. In order to solve these tasks, a method has been suggested supported by a procedure of branches and boundaries. Thealgorithmisbasedon dichotomous branchingdiagram. Itsapplicationprovidesforreceivingboth quasi-optimalandoptimallogisticsplansfor the finite number of steps. Atthat, theassessmentofaccuracy is provided for quasi-optimal plans. The proposed model and method help solve a wide spectrum of practical tasks of logistical planning under conditions of digital transformation.

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Intelligent System of Limited Resource Allocation for Large-Scale Agent Systems

Studies in Big Data - Machine Intelligence and Big Data in Industry ◽

10.1007/978-3-319-30315-4_17 ◽

2016 ◽

pp. 201-215

Author(s):

Jakub Weclawski ◽

Stanislaw Jankowski

Keyword(s):

Resource Allocation ◽

Large Scale ◽

Intelligent System ◽

Limited Resource ◽

Agent Systems

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Multi-Economic Agent Grid Resource Allocation Strategies in the Signaling Game Theory Analysis Model

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.29-32.1093 ◽

2010 ◽

Vol 29-32 ◽

pp. 1093-1099 ◽

Cited By ~ 1

Author(s):

Jun Xie ◽

Ji Guang Li

Keyword(s):

Resource Allocation ◽

Analysis Model ◽

Theory Analysis ◽

Grid Resource ◽

Trading Agents ◽

Proposed Model ◽

Finite Set ◽

Optimal Resource ◽

Resource Allocation Strategy ◽

Allocation Strategies

The paper presents a market oriented resource allocation strategy for grid resource. The proposed model uses the utility functions for calculating the utility of a resource allocation. This paper is target to solve above issues by using utility-based optimization scheme. We firstly point out the factors that influence the resources’ prices; then make out the trading flow for resource consumer agents and provider agents. By doing these, the two trading agents can decide their price due to the dynamic changes of the Grid environment without any manmade interferences. Total user benefit of the computational grid is maximized when the equilibrium prices are obtained through the consumer’s market optimization and provider’s market optimization. The economic model is the basis of an iterative algorithm that, given a finite set of requests, is used to perform optimal resource allocation.

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Resource Allocation in Grid Computing Environment Using Genetic–Auction Based Algorithm

International Journal of Grid and High Performance Computing ◽

10.4018/ijghpc.2018010101 ◽

2018 ◽

Vol 10 (1) ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Kuppani Satish ◽

A. Rama Mohan Reddy

Keyword(s):

Genetic Algorithm ◽

Resource Allocation ◽

Grid Computing ◽

Genetic Approach ◽

Simulation Environment ◽

Computing Environment ◽

Cost Constraints ◽

Proposed Model ◽

Core Functionality ◽

Made In

The main core functionality of Grid Computing is resource allocation and scheduling. With the idea of genetic algorithms and microeconomics, it is proposed a Resource allocation method called a genetic-auction based algorithm [GAAB]. This algorithm contains two modules, auction module and genetic approach. Auction module find outs resource-trading price between resource provider and resource buyer, and the resource allocation carried out by Genetic algorithm by considering both time and cost constraints simultaneously. In this article, evaluations are made in the simulation environment and the results show the effectiveness of the proposed model.

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Drone-Based Parcel Delivery Using the Rooftops of City Buildings: Model and Solution

Applied Sciences ◽

10.3390/app10124362 ◽

2020 ◽

Vol 10 (12) ◽

pp. 4362 ◽

Cited By ~ 1

Author(s):

Junsu Kim ◽

Hongbin Moon ◽

Hosang Jung

Keyword(s):

Urban Areas ◽

Programming Model ◽

Computation Time ◽

Intelligent Transportation ◽

Mixed Integer ◽

Operation Planning ◽

Logistics System ◽

Proposed Model ◽

Optimality Gap ◽

Good Operation

In general, the demand for delivery cannot be fulfilled efficiently due to the excessive traffic in dense urban areas. Therefore, many innovative concepts for intelligent transportation of freight have recently been developed. One of these concepts relies on drone-based parcel delivery using rooftops of city buildings. To apply drone logistics system in cities, the operation design should be adequately prepared. In this regard, a mixed integer programming model for drone operation planning and a heuristic based on block stacking are newly proposed to provide solutions. Additionally, numerical experiments with three different problem sizes are conducted to check the feasibility of the proposed model and to assess the performance of the proposed heuristic. The experimental results show that the proposed model seems to be viable and that the developed heuristic provides very good operation plans in terms of the optimality gap and the computation time.

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