A facility location allocation model for reusing carpet materials

1999 ◽  
Vol 36 (4) ◽  
pp. 855-869 ◽  
Author(s):  
Dirk Louwers ◽  
Bert J. Kip ◽  
Edo Peters ◽  
Frans Souren ◽  
Simme Douwe P. Flapper
2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Olayinka Waziri Otun

Some people in rural areas are often excluded from using health facilities in developing nations due to political interference in facility location decision-making. Limited attention has been paid in the literature to promoting inclusiveness in public facilities usage in developing nations. Therefore, this study was designed to examine the access to Primary Health Centres (PHCs) in the Yewa region,  Nigeria. Data on the 509 settlements and 91 PHCs in the Yewa region were obtained from government directories. The p-median Location-Allocation model was used for data analyses. The study showed that the number of PHCs increased and access to them improved in the Yewa region between 1991 and 2019. It was also shown that inclusiveness in facilities could be promoted by optimally adding new PHCs. The study assessed the effectiveness of past locational decisions, similar to other studies in Bangladesh and India, and revealed that the military administration performed better than the civilian administration in facility location decision-making between 1991 and 2019. The study showed how new facilities could be optimally located to improve access and inclusiveness in public usage.


2018 ◽  
Vol 10 (12) ◽  
pp. 4580 ◽  
Author(s):  
Li Wang ◽  
Huan Shi ◽  
Lu Gan

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.


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