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Agricultural sector not only meets the nutritional requirements of all living creatures but also generates the primary source of the raw material provided by various branches of industry to fulfill their functions. It is of great importance to increase studies on oilseeds which have an important role in Turkey's agricultural products. They are grown in almost all of the country, which are vital for the nutrition and many sectors. The main purpose of the study is to offer an integrated approach to determine potential warehouse locations for oilseeds.

This is the first study that integrates Delphi, analytical hierarchical process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), P-Median and Panel data analysis in a real case. This integrated approach consists of the following steps, respectively: (1) The criteria were determined by the Delphi method. (2) The weights of the criteria were calculated by AHP and the provinces with the highest oilseed warehouse potential in seven regions of Turkey were specified by TOPSIS. (3) Oilseed warehouse numbers and locations were obtained by P-Median. (4) In order to answer whether the distribution network is profitable in the future with the determined center locations, a forecast model based on panel data analysis was created. (5) Regional representatives were determined for 2030, and the distribution network was analyzed again. (6) The costs that arose in 2018 and 2030 were computed and compared by cost analysis. (7) The effect of the change in criteria weights on the alternative results was tested by scenario analysis.

The findings indicated that oilseed crop production potential and oilseed crop production area turned out to be the most important criteria. Furthermore, the results showed that this model is robust and suitable for warehouse location selection studies.

The study can serve as a guide for local and central policy makers with both the criteria it uses and the model it develops.

The main contribution of this study is that the integrated approach has been used for the first time in location selection in a real case.

The study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.

The paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.

It is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.

This study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.

The purpose of this paper is to develop a stochastic multi-criteria decision-making approach to solute the warehouse location problem in the stochastic environment which contains uncertain condition.

In developed approach, the weight of criteria was calculated by using the stochastic analytic hierarchy process (SAHP) method. Alternative ranking was made and evaluated by fuzzy VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje).

This study dealt with warehouse location selection problem of a supermarket that has sellers in many regions in Turkey and selected proper warehouse.

This study combined SAHP and fuzzy VIKOR methods as a solution approach for warehouse location selection problems.

The purpose of this research is to identify a province in Thailand where total transportation cost for shipping grocery goods from this province to customers in all other provinces is the lowest.

Transportation distances among provinces, freight rate and the number of population in each province were gathered. Total transportation cost was computed by taking distance, tapering freight rate and population including that in original province into account.

Based on pre-set assumptions, it reveals that Saraburi province has the lowest total transportation cost.

This research emphasizes only transportation cost. For future research, other monetary and non-monetary factors such as land, labor, investment incentive, local government regulation should be considered together.

This is an industry-based research especially for retail and fast-moving consumer goods businesses.

This practitioner paper is one of the first to identify population, freight rate and distance-based warehouse location which can be determined as a location for Thailand’s logistics hub, particularly for retail or fast-moving consumer goods business in Thailand.

Locating disaster response centers is one of the key elements of efficient relief operations. The location and infrastructure of the candidate facilities usually conform to the required criteria at different levels. This study aims to identify the criteria for the main and local distribution center location problem separately and prioritize each candidate distribution center using a hybrid multiple criteria decision-making approach.

The proposed model incorporates analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) under interval type-2 fuzzy sets (IT2FSs) to overcome the uncertainty of experts` judgments and expressions in the evaluations of candidate distribution centers. In the proposed approach, weights of the criteria are determined using type-2 fuzzy AHP and the candidate distribution centers are prioritized using type-2 fuzzy TOPSIS.

Transportation, cost, infrastructure and security are determined as the main criteria for the main distribution center location criteria. Cost, warehouse facilities and security are the main criteria for local distribution center location selection. Prioritization enables decision-makers to assess each alternative accordingly to be able to select the best locations/facilities for efficient disaster response operations.

This study proposes new multi-criteria decision support models for prioritizing disaster response distribution centers. IT2FSs are used to be able to reflect both the complexity and vagueness of disaster environment and expert opinions. Different support models are suggested for main and local distribution centers considering their different missions. The proposed methodology is applied in Istanbul city, Turkey, where a high-magnitude earthquake is expected.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

The learning outcomes are as follows: to understand the strategic importance of location selection within the organization and how it influences other’s performance; to understand the impact of supply chain drivers on sales performance and to understand the role of other stakeholders in location selection strategy; to analyze the constraints in decision-making for selection of warehouse location and its remedies; to analyze the alternative options for warehouse in the light of top level management’s instruction or organizational strategies; to select the best possible alternate for long-term sustainability of warehouse location.

Ishaq Bashir, who has recently joined Super Distribution Services as Facility Manager, is indecisive in selecting a rental location for its offices and warehouse, either SDS had to move back to the old location or continue with existing warehouse facility. This existing location was selected by Ex Facility Manager around six months ago because SDS had to vacate their old location due to graving concern the owner of the premises. SDS had to search for a new facility and vacate the older premises within three months’ time as per “evacuation notice” received from the owner, and finally, the company shifted to the new location by 28 February 2017. After six months in September 2017, sales team realized a serious dip in sales by 1 per cent, and they claimed that this had happened due to wrong selection of the location of the warehouse which was far from the city. Now Bashir had to decide either to continue with the existing facility or move to the previous one or search for any third feasible location.

BBA and MBA.

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CSS 9: Operations and Logistics.

Applies the concept of buyer‐seller relationship to long‐term planning of wholesaling operations. Current practices indicate that this kind of relational exchange reduces overall costs more than the traditional market exchange. Aims to help to operationalize this partnership by selecting a stable set of manufacturers and warehouses for an entire planning period. Develops a multi‐period optimization model incorporating constraints necessary for such stable solutions. This model requires a large number of variables and constraints, and is computationally challenging for most practical‐sized problems. Therefore proposes heuristic method to decompose the model into subproblems by partitioning the planning period into blocks of years and then synthesize the subproblem solutions. Such decomposition may also be useful to solve large dynamic location planning problems.

The purpose of this paper is to shed light on the development and change in priority of international warehouse location criteria during a business cycle (i.e. from years 2006 to 2010), by examining the responses of Finnish and Swedish companies on their European‐based facilities. The authors also investigate how the size of European warehouses will develop within medium term.

The authors' research is based on three online surveys completed during years 2006, 2009, and 2010. The 120 respondents were large Finnish and Swedish companies.

Finnish companies tend to focus on the emerging East European markets through their warehousing network structure, while Swedish companies focus more on Western Europe. Selection of warehouse location is dominated by three criteria, namely distribution cost, road transportation connection, and proximity of assembly and manufacturing units. Most of the longitudinal changes occur in less important warehousing criteria; companies seem to see warehousing decisions as less complex, incorporating a lower amount of criteria in the decision. Warehouse size analysis shows that in the future, the average size will slowly continue to increase, however, both small and large warehouses have justification for their existence. Finnish and Swedish respondents were mostly aligned in terms of warehouse location criteria, however, in terms of warehouse size Swedish companies are in favor of larger units.

Research is limited in terms of geography and respondent size. This will limit the generalizability of the results.

This research is based on a longitudinal survey, and provides insight on the evolution of warehouse location criteria in changing economic conditions.

Determination of new warehouse locations is an important managerial decision. The problem typically involves a number of considerations such as cost per distance of distribution to and from the warehouse, volume of distribution, fixed and variable site costs, service performance of the warehouse and potential increases in demand (or service), as well as many other factors. The economic significance of warehouse location decisions is increasing, particularly due to expected increases in transportation costs, competition for market share and changing demand patterns.