A warehouse location-routing problem

Perl, Jossef; Daskin, Mark S.

doi:10.1016/0191-2615(85)90052-9

Cited by 263 publications

(130 citation statements)

References 14 publications

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“…The selection of patients while making a routing decision is like the case of LRP, where facility location and vehicle routing decisions are considered in the same model to avoid suboptimal results. The interdependence between location and routing was first covered by Perl and Daskin [6]. They defined a warehouse location routing model that has the capability of simultaneously solving location and routing problems.…”

Section: A Flexible Hhc Planning Problemmentioning

confidence: 99%

Solving a More Flexible Home Health Care Scheduling and Routing Problem with Joint Patient and Nursing Staff Selection

Nasir

Dang

2018

Sustainability

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Development of an efficient and effective home health care (HHC) service system is a quite recent and challenging task for the HHC firms. This paper aims to develop an HHC service system in the perspective of long-term economic sustainability as well as operational efficiency. A more flexible mixed-integer linear programming (MILP) model is formulated by incorporating the dynamic arrival and departure of patients along with the selection of new patients and nursing staff. An integrated model is proposed that jointly addresses: (i) patient selection; (ii) nurse hiring; (iii) nurse to patient assignment; and (iv) scheduling and routing decisions in a daily HHC planning problem. The proposed model extends the HHC problem from conventional scheduling and routing issues to demand and capacity management aspects. It enables an HHC firm to solve the daily scheduling and routing problem considering existing patients and nursing staff in combination with the simultaneous selection of new patients and nurses, and optimizing the existing routes by including new patients and nurses. The model considers planning issues related to compatibility, time restrictions, contract durations, idle time and workload balance. Two heuristic methods are proposed to solve the model by exploiting the variable neighborhood search (VNS) approach. Results obtained from the heuristic methods are compared with a CPLEX based solution. Numerical experiments performed on different data sets, show the efficiency and effectiveness of the solution methods to handle the considered problem.

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Section: A Flexible Hhc Planning Problemmentioning

confidence: 99%

Solving a More Flexible Home Health Care Scheduling and Routing Problem with Joint Patient and Nursing Staff Selection

Nasir

Dang

2018

Sustainability

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“…Benders' decomposition is suitable for problems with exclusive sub-problem sets or problems that shows some block structures linked by constraints (Benders, 1962). In another example (Perl and Daskin, 1985) split the warehouse location-routing problem into three smaller problems: the complete multi-depot vehicle-dispatch problem, the warehouse location-allocation problem and the multi-depot routing-allocation problem. These three smaller problems were solved in phases and each of them was formulated with mathematical programming and solved by an exact solver.…”

Section: Literature Reviewmentioning

confidence: 99%

Mixed Integer Programming with Decomposition to Solve a Workforce Scheduling and Routing Problem

Laesanklang

Landa-Silva

Castillo-Salazar

2015

Proceedings of the International Conference on Operations Research and Enterprise Systems

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Abstract:We propose an approach based on mixed integer programming (MIP) with decomposition to solve a workforce scheduling and routing problem, in which a set of workers should be assigned to tasks that are distributed across different geographical locations. This problem arises from a number of home care planning scenarios in the UK, faced by our industrial partner. We present a mixed integer programming model that incorporates important real-world features of the problem such as defined geographical regions and flexibility in the workers' availability. Given the size of the real-world instances, we propose to decompose the problem based on geographical areas. We show that the quality of the overall solution is affected by the ordering in which the sub-problems are tackled. Hence, we investigate different ordering strategies to solve the sub-problems and show that such decomposition approach is a very promising technique to produce high-quality solutions in practical computational times using an exact optimization method.

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“…Optimisation models for two-layer distribution systems are presented in Berger (1997) and Hassanzadeh et al (2009). The supply chain distribution system can also be extended to three-layers (Perl 1983;Perl and Daskin 1985) and also four-layers (Hamidi et al 2012). …”

Section: The Dairy Market Supply Chain -Irish Case Reviewmentioning

confidence: 99%

A case analysis of a sustainable food supply chain distribution system—A multi-objective approach

Validi

Bhattacharya

Byrne

2014

International Journal of Production Economics

240

111

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Abstract:Sustainable supply chain management is a topical area which is continuing to grow and evolve. Within supply chains, downstream distribution from producers to customers plays a significant role in the environmental performance of production supply chains. With consumer consciousness growing in the area of sustainable food supply, food distribution needs to embrace and adapt to improve its environmental performance, while still remaining economically competitive. With a particular focus on the dairy industry, a robust solution approach is presented for the design of a capacitated distribution network for a two-layer supply chain involved in the distribution of milk in Ireland. In particular the green multiobjective optimisation model minimises CO2 emissions from transportation and total costs in the distribution chain. These distribution channels are analysed to ensure the non-dominated solutions are distributed along the Pareto fronts. A multi-attribute decision-making approach, TOPSIS, has been used to rank the realistic feasible transportation routes resulting from the trade-offs between total costs and CO 2 emissions. The refined realistic solution space allows the decision-makers to geographically locate the sustainable transportation routes. In addition to geographical mapping the decision maker is also presented with a number of alternative analysed scenarios which forcibly open closed distribution routes to build resiliency into the solution approach. In terms of model performance, three separate GA based optimisers have been evaluated and reported upon. In the case presented NSGA-II was found to outperform its counterparts of MOGA-II and HYBRID.

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A warehouse location-routing problem

Cited by 263 publications

References 14 publications

Solving a More Flexible Home Health Care Scheduling and Routing Problem with Joint Patient and Nursing Staff Selection

Solving a More Flexible Home Health Care Scheduling and Routing Problem with Joint Patient and Nursing Staff Selection

Mixed Integer Programming with Decomposition to Solve a Workforce Scheduling and Routing Problem

A case analysis of a sustainable food supply chain distribution system—A multi-objective approach

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