Multi-products Location-Routing problem with Pickup and Delivery: Two-Echelon model

Rahmani, Younes; Oulamara, Ammar; Cherif, Wahiba Ramdane

doi:10.3182/20130522-3-br-4036.00039

Cited by 8 publications

(5 citation statements)

References 8 publications

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“…Vector p 0 represents the h-product demands of all processing centres, and vectors p 1 and p 2 give the indices of processing centres in which the products p 1 and p 2 are available. These generalised instances are accessible at Rahmani, Oulamara, and Ramdane Cherif (2015).…”

Section: Computational Experiments 41 Implementation and Benchmark Imentioning

confidence: 99%

The two-echelon multi-products location-routing problem with pickup and delivery: formulation and heuristic approaches

Rahmani

Chérif-Khettaf

Oulamara

2015

International Journal of Production Research

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The two-echelon location-routing problem (LRP-2E) considers the first-level routes that serve from one depot a set of processing centres, which must be located and the second-level routes that serve customers from the opened processing centres. In this paper, we consider an extension of the LRP-2E, where the second-level routes include three constraints that have not been considered simultaneously in the location routing literature, namely multi-product, pickup and delivery, and the use of the processing centre as intermediate facility in the second-level routes. This new variant is named two-Echelon Multi-products Location-Routing problem with Pickup and Delivery (LRP-MPPD-2E). The objective of LRP-MPPD-2E is to minimise both the location and the routing costs, considering the new constraints. The first echelon deals with the selection of processing centres from a set of potential sites simultaneously with the construction of the first-level routes, such that each route starts from the main depot, visits the selected processing centres and returns to the main depot. The second echelon aims at assigning customers to the selected processing centres and defining the second-level routes. Each second-level route, starts at a processing centre, visits a set of customers, through one or several processing centres, and then returns to the first processing centre. We present a mixed-integer linear model for the problem and use a Cplex solver to solve small-scale instances. Furthermore, we propose non-trivial extensions of the nearest neighbour and insertion approaches. We also develop clustering-based approaches that have not been extensively investigated with regards to location routing. Computational experiments are conducted to evaluate and to compare the performances of the proposed approaches. The results confirm the effectiveness of clustering approaches.

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Section: Computational Experiments 41 Implementation and Benchmark Imentioning

confidence: 99%

The two-echelon multi-products location-routing problem with pickup and delivery: formulation and heuristic approaches

Rahmani

Chérif-Khettaf

Oulamara

2015

International Journal of Production Research

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“…Constraint (9) the total loading limited to the maximum capacity of the warehouse. Constraint (10) implies that supplying the customer demands is related to the warehouse capacity. Constraint (11) ensures that any vehicle that is assigned to a customer load its' pick-up demand.…”

Section: Stochastic Mathematical Formulationmentioning

confidence: 99%

“…Constraints (12) to (16) define the domain of variables that are associated with pick-up and delivery products. These constraints, along with constraints (10) and 11that determine the exact value of pick-up and delivery. Constraint (17) expresses the arrival time to customers.…”

Section: Stochastic Mathematical Formulationmentioning

confidence: 99%

“…Contardo et al [9] introduced a branch-and-cut and an adaptive large-neighborhood search Meta heuristic for the two-echelon capacitated location-routing problem. Rahmani et al [10] presented a mixed integer linear programming formulation for modeling multi products location-routing with pick-up and delivery by considering a two-echelon distribution scenario. Perwira Redi et al [11] addressed the open vehicle routing problem with time windows and presented a heuristic algorithm to solve the problem (VSN).…”

Section: Introductionmentioning

confidence: 99%

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Multi-echelon green open-location-routing problem: A robust-based stochastic optimization approach

2020

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In recent years, considering the environmental competencies could help the companies/countries to improve their industries successfully regarding the sustainable development. In this study, a green open location-routing problem with simultaneous pickup and delivery (GOLRPSPD) is considered to minimize the overall costs. In addition to cost minimization, the objective function is provided the environmental competencies regarding the costs of CO 2 emissions and fuel consumptions. Meanwhile, in a complex situation, considering the precise information could lead the results to unreliable in which considering the uncertainty theories could prevent the data loss. In this respect, this study considered the pickup and delivery demand and the travel time as probabilistic parameters. To address the issue, a robust stochastic programming approach is developed to decrease the deviations of imprecise information. Moreover, the proposed approach is implemented based on five scenarios to decide the best decision in different situations. In addition, a practical example of the multi-echelon open-location-routing model is provided to represent the feasibility and applicability of the presented robust stochastic programming approach. Finally, a comparative and sensitivity analysis is considered to indicate the validity of the proposed approach, and also represent the robustness and sensitiveness of the obtained results regarding some significant parameters, respectively.

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“…An extended variant of Location-Routing Problem namely LRP with Multi-Product and Pickup and Delivery (LRP-MPPD) is presented in [76,77]. This variant of the LRP deals with simultaneously selecting one or more facilities from a set of potential hubs (locations), assigning customers to the selected hubs and defining routes of the vehicles for serving multi-product customers demand (MPr in the field α) in such a way that each selected hub must be visited once for delivering, though it can be visited many times for picking up.…”

Section: Applications Of the Proposed Classification Schemamentioning

confidence: 99%

New Notation and Classification Scheme for Vehicle Routing Problems

et al. 2014

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Vehicle Routing Problems have been some of the most studied problems in combinatorial optimisation because they have many applications in transportation and supply chain. They are usually known as Vehicle Routing Problems or VRPs. The related literature is quite large and diverse both in terms of variants of the problems and in terms of solving approaches. To identify the different variants of routing problems, authors generally use initialisms, in which various prefixes and suffixes indicate the presence of different assumptions or constraints. But this identification based on initialisms is inefficient. For example, two variants of a problem may be identified by the same abbreviation, whereas different abbreviations may be assigned to the same problem. This paper proposes a new notation and a new formalism to identify and to classify instances of routing problems. This contribution aims at filling in the gaps of the current identification system. The goal is to allow everyone to position his work accurately in the literature, and to easily identify approaches and results comparable to his research. The proposed notation is inspired by the scheduling formalism. It has four fields (π/α/β/γ), respectively describing the type and horizon of the problem, the system structure, resources and demands, constraints and objectives to be optimized. 26 papers from the literature chosen

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Multi-products Location-Routing problem with Pickup and Delivery: Two-Echelon model

Cited by 8 publications

References 8 publications

The two-echelon multi-products location-routing problem with pickup and delivery: formulation and heuristic approaches

The two-echelon multi-products location-routing problem with pickup and delivery: formulation and heuristic approaches

Multi-echelon green open-location-routing problem: A robust-based stochastic optimization approach

New Notation and Classification Scheme for Vehicle Routing Problems

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