Negotiation mechanisms for the multi-agent multi-mode resource investment problem

2021 ◽  
Author(s):  
Andreas Fink ◽  
Patrick Gerhards
Keyword(s):  
Resource Investment ◽  
Investment Problem ◽  
Multi Agent ◽  
Resource Investment Problem ◽  
Multi Mode

scholarly journals The multi-mode resource investment problem: a benchmark library and a computational study of lower and upper bounds

OR Spectrum ◽  
2020 ◽  
Vol 42 (4) ◽  
pp. 901-933
Author(s):  
Patrick Gerhards
Keyword(s):  
Project Scheduling ◽  
Resource Constraints ◽  
Computational Study ◽  
Renewable Resource ◽  
Exact Methods ◽  
Nonrenewable Resource ◽  
Resource Investment ◽  
Investment Problem ◽  
Resource Investment Problem ◽  
Multi Mode

Abstract The multi-mode resource investment problem (MRIP) is the multi-mode extension of the resource investment problem, which is also known under the name resource availability cost problem. It is a project scheduling problem with a given due date as well as precedence and resource constraints. The goal is to find a precedence feasible schedule that minimises the resource costs of the allocated resources. To compute these costs, the maximum resource peak is considered regarding renewable resource types, whereas the sum of allocated nonrenewable resource units is used in the case of nonrenewable resources. Many practical and complex project scheduling settings can be modelled with this type of problem. Especially with the usage of different processing modes, time and cost compromises can be utilised by the project manager. In the literature, some procedures for the MRIP have been investigated; however, the computational experiments in these studies have not been carried out on common benchmark instances. This makes a fair comparison of methods difficult. Therefore, we generated novel instances specifically designed for this problem and published them on the website https://riplib.hsu-hh.de. On this website, the instances as well as best-known solution values are available and researchers can also contribute their findings. We investigate these novel instances by proposing and evaluating lower bounds for the MRIP. Additionally, we analyse the proposed instances by applying heuristic as well as exact methods. These experiments suggest that most of the instances are challenging and further research is needed. Finally, we show some computational complexity properties of the NP-hard MRIP.

scholarly journals Multimode Preemptive Resource Investment Problem Subject to Due Dates for Activities: Formulation and Solution Procedure

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Behrouz Afshar-Nadjafi ◽  
Mohammad Arani
Keyword(s):  
Time Lag ◽  
Solution Procedure ◽  
Mixed Integer ◽  
Test Problems ◽  
Due Dates ◽  
Nonrenewable Resource ◽  
Setup Cost ◽  
Resource Investment ◽  
Investment Problem ◽  
Resource Investment Problem

The preemptive Multimode resource investment problem is investigated. The Objective is to minimize the total renewable/nonrenewable resource costs and earliness-tardiness costs by a given project deadline and due dates for activities. In this problem setting preemption is allowed with no setup cost or time. The project contains activities interrelated by finish-start type precedence relations with a time lag of zero, which require a set of renewable and nonrenewable resources. The problem formed in this way is an NP-hard. A mixed integer programming formulation is proposed for the problem and parameters tuned genetic algorithm (GA) is proposed to solve it. To evaluate the performance of the proposed algorithm, 120 test problems are used. Comparative statistical results reveal that the proposed GA is efficient and effective in terms of the objective function and computational times.

A flexible resource investment problem based on project splitting for aircraft moving assembly line

2019 ◽  
Vol 39 (4) ◽  
pp. 532-547 ◽  
Author(s):  
Yifei Ren ◽  
Zhiqiang Lu
Keyword(s):  
Assembly Line ◽  
Job Scheduling ◽  
Resources Allocation ◽  
Content Type ◽  
Second Stage ◽  
Resource Investment ◽  
Investment Problem ◽  
Flexible Resources ◽  
Flexible Resource ◽  
Resource Investment Problem

Purpose In response to the station design and flexible resources allocation of the aircraft moving assembly line, a new problem named flexible resource investment problem based on project splitting (FRIP_PS), which minimizes total cost of resources with a given deadline are proposed in this paper. Design/methodology/approach First, a corresponding mathematical model considering project splitting is constructed, which needs to be simultaneously determined together with job scheduling to acquire the optimized project scheduling scheme and resource configurations. Then, an integrated nested optimization algorithm including project splitting policy and job scheduling policy is designed in this paper. In the first stage of the algorithm, a heuristic algorithm designed to get the project splitting scheme and then in the second stage a genetic algorithm with local prospective scheduling strategy is adopted to solve the flexible resource investment problem. Findings The heuristic algorithm of project splitting gets better project splitting results through the job shift selection strategy and meanwhile guides the algorithm of the second stage. Furthermore, the genetic algorithm solves resources allocation and job schedule through evaluation rules which can effectively solve the delayed execution of jobs because of improper allocation of flexible resources. Originality/value This paper represents a new extension of the resource investment problem based on aircraft moving assembly line. An effective integrated nested optimization algorithm is proposed to specify station splitting scheme, job scheduling scheme and resources allocation in the assembly lines, which is significant for practical engineering applications.

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