•We present a mix-integer linear programming model for warehouse location problem.•The truly optimized warehouse center saves cost by −14.0% on average.•We present a fix-and-optimize heuristic for ...large-sized problems.•Computational experiments are conducted to show the new improvements.
The warehouse location problem (WLP) involves determining one (or multiple) locations as the materials/products collecting/distributing centers for serving a group of customers scattered geographically in a region, at a minimum total transportation cost. The most conventional and widely used approach for solving the WLP is the weighted k-means algorithm. However, this is not a global approach, because it always traps into local optima and is sensitive to the initial settings. Our numeric examples demonstrated that the solutions obtained by the weighted k-means could depart from the optimal values by as much as 16.8% on average. In this paper, we present an optimal programming approach based on mixed-integer linear programming (MILP) for the WLP, which is irrelative to the initial solution and can be optimally solved by commercial solvers. For large-sized datasets, we developed an MILP-based dynamic iterative partial optimization (MILP-DIPO) to search for the near-optimal results with controllable computational time. Experiments on 14 datasets, including 6 small-sized synthesized datasets and 8 variants of the known benchmark datasets in the UEF repository, were performed to validate the proposed model and heuristics. The computational results confirm that improvements with the proposed method could be as great as –22.9% (−14.0% on average) for small-sized datasets. For the eight benchmark datasets, the MILP-DIPO algorithm delivered near-optimal solutions in a reasonable computational time, with up to −8.0% (−2.6% on average) improvement compared to the results obtained by the conventional weighted k-means algorithm.
Today, most of the issues and challenges faced by managers and decision makers are complex and multifaceted. More clearly, due to the developments of technologies, emerging trends in various ...industries, competitive markets, and rapid and transformative changes in the business environment, managers and decision makers have faced an uncertain environments and issues that cannot be resolved definitively. The use of multi-criteria decision-making (MCDM) methods as a practical and decision-supporting tool allows managers to examine decision-making issues in various organizations and industries based on various criteria, alternatives, and objectives and make decisions with greater reliability. The use of fuzzy techniques and concepts in MCDM methods and their mathematical relationships makes it possible to consider complexities and uncertainties in decisions related to various issues and it can lead to better and more realistic decisions. In this paper, the simplified best-worst method (SBWM), which is one of the methods based on pairwise comparisons, has been developed using triangular fuzzy numbers (TFNs) to propose a fuzzy extension of SBWM (F-SBWM). Triangular fuzzy numbers in different symmetric and asymmetric forms have widely been used in MCDM approaches and pairwise comparisons. It is noteworthy that symmetric numbers are used when we are using equal division of the domain due to an increased ambiguity and lack of information. The proposed approach as a simplified fuzzy MCDM method helps managers and decision makers in various industries to solve decision-making problems under uncertainty without the need for complex calculations, specialized skills, and software packages. To check the feasibility and applicability of the proposed approach, two numerical examples and a computational experiment with real data are presented, and the results are analyzed and discussed. Furthermore, to check the robustness of the results obtained from the proposed approach, sensitivity analysis and comparison of methods have been performed.
Abstract
Autoclaved aerated concrete (AAC) is a widely used building material for masonry blocks. Its porous structure and mineral composition lead to low thermal conductivity and fire resistance. ...European AAC production and usage strongly increased in the 1960s and 1970s. Therefore, assuming limited buildings’ lifetimes, significant post-demolition AAC volumes can be expected in the following decades. However, post-demolition AAC recycling in high-value environmentally friendly applications is still to be established as most post-demolition AAC is currently landfilled. Different recycling options for post-demolition AAC are presently being researched. However, a recycling network to implement these options is neither designed nor established. This contribution focuses on creating a European recycling network, including mathematical modelling, data acquisition, and solving the model. i.e. minimising the total costs. The mathematical modelling uses a capacitated warehouse location problem with multi-sourcing and direct delivery. Results show that recycling plants of smaller capacity (100,000 t input/a) are placed in the recycling networks in 2020 and 2025. With higher waste quantities being expected from 2030 onwards, plants with a larger capacity (200,000 t input/a) are added, especially in Poland, where the highest pd-AAC amount in Europe is expected. The recycling network shows a decentralised structure with numerous recycling plants to keep transport costs low. Most network costs result from variable processing costs, showing the highest cost increases from 2020 to 2050. Fixed costs increase with the higher number of recycling plants and account for the second-largest share of total network costs. Transport costs are comparatively low thanks to the decentralised structure of the network. Overall, waste generation is expected to increase by 226% from 2020 to 2050, while the total costs of the recycling network are expected to rise by 151% only. The results support decision-makers in fostering recycling and implementing a circular economy for post-demolition AAC.
In 1970, Tobler produced a movie simulating population growth in the City of Detroit. He argued that his model did not need to include terms for faraway places like Singapore, while still being ...relative accurate in his forecast by invoking what he called the first law of geography. In spatial optimization, like the general warehouse location problem (GWLP), it is assumed that all possible linkages need to be included, as arbitrarily dropping potential variables may prevent optimal solutions from being identified. In this article, it is demonstrated that it may be possible to meet such exacting standards in spatial optimization, while at the same time being guided by Tobler’s argument for being simple and frugal. This article gives a demonstration of how this might be achieved using the GWLP as an example. A new model form is proposed which distinguishes between “near” (low cost) allocations and “far” (high cost) allocations and uses both explicit and implicit variables for capacity allocations. Computational experience in using this new model is given which shows that optimal solutions can be identified and verified while eliminating a substantial number of allocation/transport variables and constraints. This article ends with a challenge for the reformulation and redevelopment of other spatial optimization problems in regional science.
Fast moving consumable goods require good supply chain operation. In this paper, a leading Egyptian FMCG is considered. The company wants to optimize its distribution network design considering ...several supply chain strategic objectives. The company wants to determine the number of warehouses to build, their sizes, customers assigned to each warehouse, and their layout. The objective is to reduce the distribution cost taking into consideration the company's strategic decision such as giving higher priority to important customers and assigning the nearest warehouse to each customer, and also the real live applicability of the suggested solution. We first segment the customer according to different strategic factors. Then a non-linear model is proposed for solving the problem. A hybrid heuristic is proposed that solves the problem by iterating between the optimal suggested location and the possible locations available for business in the real life according to availability and other strategic factors. Different layouts for the selected locations are evaluated using Monte-Carlo Simulation.
China is one of the countries suffering from the most disasters in the world, so national emergency warehouse location is critical for the country to reduce loss resulting from disasters. Considering ...that emergency management is more concerned about effectiveness than efficiency, the paper proposes an emergency warehouse location problem (EWLP) model—an extension of the classic P-center model, for the Chinese national emergency warehouse location problem. Some features, including population distribution, economic condition, transportation, and multi-coverage for some vital areas, are put into the proposed model, which are characterized with data gathered from the reality. A Variable Neighborhood Search (VNS) based heuristic algorithm is developed to solve the extensional model. The computational result gained is cmopared with current emergency warehouse location planning in China. It is shown that huge saving can be gained with the guarantee that the rescue resources could be delivered in time. Moreover, the proposed VNS based algorithm shows its good performance in the computational experiment.
Facility Location Problem (FLP) is a critical aspect in supply chain that is difficult to be solved in order to design an efficient supply chain. The terms of location problem refers to modeling, ...formulating, and solving problem, which is determining the location of facilities in certain area. Warehouse Location Problem is one model of Facility Location Problem which aims to locate the set of warehouses as one of distribution facility. In this study, a mathematical model of Single Stage Capacitated Warehouse Location Problem (SSCWLP) has been developed to determine the optimal warehouse location in fertilizer distribution of PT. Petrokimia Gresik in Sumatera Island, Indonesia. Basically, SSCWLP is an NP-Hard problem that requires long computing time to be solved by using exact methods. The weakness is resolved by using metaheuristics algorithm, namely Simulated Annealing (SA). The next step is testing the performance of SA by comparing the results of SA with those of branch & bound (BB). The algorithm provides results which are better to the existing solutions and have small gaps with those of exact method.
In this paper we solve a single stage warehouse location, distribution problem with inventory and shortage costs. This is an extension to the work of Sharma (1991) 1 as it considered only inventory ...carrying costs and did not consider shortage costs. For the general problem of shortage costs (along with warehouse location, distribution problem with inventory costs), we use the method given by Vimal Kumar (2012) 2 to eliminate shortage costs, and this results in several computational advantages. Next, we add linking constraints, so that problem is amenable to be solved by Lagrangian method as here sub problems are easily solvable. Few extensions of this problem is considered.
Some researchers have not used the ‘strong’ formulations for single and multistage warehouse location problems despite it being well known earlier. In this paper we give ‘strong’ and ‘weak’ ...formulations of the single stage uncapacitated warehouse location problem (SSUWLP) by borrowing from the literature on capacitated version of the problem. The constraints borrowed are ‘weak’ constraints, demand side ‘strong’ constraints and the supply side ‘strong’ constraints. We give four different formulations of the SSUWLP and also empirical results for the relative strengths of their linear programming (LP) relaxations.
PDF
