Development and application of a hybrid genetic algorithm for resource optimization and management

Ugwu, O. O.; Tah, J.H.M.

doi:10.1046/j.1365-232x.2002.00237.x

Cited by 4 publications

(4 citation statements)

References 19 publications

(27 reference statements)

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“…Unlike traditional searching algorithms, GA solves the problem iteratively by introducing genetic operators, such as selection, crossover, mutation and eventually converges to the best chromosome within a finite number of iterations. The advantage of GA is that the model variables are recoded as chromosome for computation, rather than handled directly (UGWU and TAH, 2002). Constraints are largely cut off during GA searching, as a result, the likelihood of falling into local optima is decreased.…”

Section: Two Phase Cluster-based Approachmentioning

confidence: 99%

Network planning of urban underground logistics system with hub-and-spoke layout: two phase cluster-based approach

Dong

Hwang

Ren

et al. 2020

ECAM

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PurposeUnderground logistics system (ULS) is recognized as sustainable alleviator to road-dominated urban logistics infrastructure with various social and environmental benefits. The purpose of this study is to propose effective modeling and optimization method for planning a hub-and-spoke ULS network in urban region.Design/methodology/approachUnderground freight tunnels and the last-mile ground delivery were organized as a hierarchical network. A mixed-integer programming model (MIP) with minimum system cost was developed. Then a two-phase optimization schema combining Genetic-based fuzzy C-means algorithm (GA-FCM), Depth-first-search FCM (DFS-FCM) algorithm and Dijkstra algorithm (DA), etc. was designed to optimize the location-allocation of ULS facilities and customer clusters. Finally, a real-world simulation was conducted for validation.FindingsThe multistage strategy and hybrid algorithms could efficiently yield hub-and-spoke network configurations at the lowest objective cost. GA-FCM performed better than K-means in customer-node clustering. The combination of DFS-FCM and DA achieved superior network configuration than that of combining K-means and minimum spanning tree technique. The results also provided some management insights: (1) greater scale economies effect in underground freight movement could reduce system budget, (2) changes in transportation cost would not have obvious impact on ULS network layout and (3) over 90% of transportation process in ULS network took place underground, giving remarkable alleviation to road freight traffic.Research limitations/implicationsDemand pairs among customers were not considered due to lacking data. Heterogeneity of facilities capacity parameters was omitted.Originality/valueThis study has used an innovative hybrid optimization technique to address the two-phase network planning of urban ULS. The novel design and solution approaches offer insights for urban ULS development and management.

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Section: Two Phase Cluster-based Approachmentioning

confidence: 99%

Network planning of urban underground logistics system with hub-and-spoke layout: two phase cluster-based approach

Dong

Hwang

Ren

et al. 2020

ECAM

View full text Add to dashboard Cite

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“…Managing a multi-project environment is arduous and challenging (Blismas et al , 2004; Patanakul and Milosevic, 2009). Resource optimization is essential to improve portfolio performances (Kannimuthu et al , 2018; Ugwu and Tah, 2002). However, there is not much literature on the MRCMPS category involving multi-objective optimization.…”

Section: Studies On Resource-constrained Project Scheduling Problems In a Multi-project Environmentmentioning

confidence: 99%

Comparing optimization modeling approaches for the multi-mode resource-constrained multi-project scheduling problem

Kannimuthu

Raphael

Palaneeswaran

et al. 2019

ECAM

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Purpose Construction firms keep minimal resources to maintain productive working capital. Hence, resources are constrained and have to be shared among multiple projects in an organization. Optimal allocation of resources is a key challenge in such situations. Several approaches and heuristics have been proposed for this task. The purpose of this paper is to compare two approaches for multi-mode resource-constrained project scheduling in a multi-project environment. These are the single-project approach (portfolio optimization) and the multi-project approach (each project is optimized individually, and then heuristic rules are used to satisfy the portfolio constraint). Design/methodology/approach A direct search algorithm called Probabilistic Global Search Lausanne is used for schedule optimization. Multiple solutions are generated that achieve different trade-offs among the three criteria, namely, time, cost and quality. Good compromise solutions among these are identified using a multi-criteria decision making method, Relaxed Restricted Pareto Version 4. The solutions obtained using the single-project and multi-project approaches are compared in order to evaluate their advantages and disadvantages. Data from two sources are used for the evaluation: modified multi-mode resource-constrained project scheduling problem data sets from the project scheduling problem library (PSPLIB) and three real case study projects in India. Findings Computational results prove the superiority of the single-project approach over heuristic priority rules (multi-project approach). The single-project approach identifies better solutions compared to the multi-project approach. However, the multi-project approach involves fewer optimization variables and is faster in execution. Research limitations/implications It is feasible to adopt the single-project approach in practice; realistic resource constraints can be incorporated in a multi-objective optimization formulation; and good compromise solutions that achieve acceptable trade-offs among the conflicting objectives can be identified. Originality/value An integer programming model was developed in this research to optimize the multiple objectives in a multi-project environment considering explicit resource constraints and maximum daily costs constraints. This model was used to compare the performance of the two multi-project environment approaches. Unlike existing work in this area, the model used to predict the quality of activity execution modes is based on data collected from real construction projects.

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“…We show a bibliographical review of problems of optimization developed recently, mono-objective (Table 1) [1][2][3][4][5][6][7] and multi-objective (Table 2) [8][9][10][11][12][13][14][15]. These tables are arranged in six columns.…”

Section: Bibliographical Reviewmentioning

confidence: 99%

Optimization of Resource in the Industry of Construction

García¹,

Díaz²,

Luis³

2014

JCEA

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Time and cost are two of the most important factors to consider in each construction project. In order to maximize performance, both the client and the contractor will work to optimize both the duration of the project and its cost. We show a model of linear entire mixed programming to solve the considered problem. The aim is to minimize the project total time, by means of the assignment of equipments of work to the different production lines of the activities to realizing. The fundamental beginning is to support the same production (rate of production in meters/day of the activity in view of the equipment of work) for the different equipments to achieve the maximum efficiency in each period of time. With the limited availability of resources, the work must be continuous and the period of time between operations and final must be kept. However, this paper also presents the bibliographical study on methodologies of the optimization of construction processes in response to the two objectives: time and cost. This will consider the use of meta-heuristic techniques, such as population based algorithms.

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Development and application of a hybrid genetic algorithm for resource optimization and management

Cited by 4 publications

References 19 publications

Network planning of urban underground logistics system with hub-and-spoke layout: two phase cluster-based approach

Network planning of urban underground logistics system with hub-and-spoke layout: two phase cluster-based approach

Comparing optimization modeling approaches for the multi-mode resource-constrained multi-project scheduling problem

Optimization of Resource in the Industry of Construction

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