Formulations for the orienteering problem with additional constraints

Palomo-Martínez, Pamela J.; Salazar-Aguilar, M. Angélica; Albornoz, Víctor M.

doi:10.1007/s10479-017-2408-4

Cited by 7 publications

(3 citation statements)

References 32 publications

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“…The concept was introduced into OP by Gendreau et al [14]. Palomo-Martínez et al [15] model the OP with mandatory visits and conflict (OPMVC). The model supports both compulsory and conflicted POIs.…”

Section: B Op For Ttdpmentioning

confidence: 99%

“…The second one is the minimum total distance which is often selected when the tourists consist of elders or young children in tours. OP 1998 [14], 2017 [15], 2017 [16]  P 2009 [23], 2015 [24], 2015 [25], 2017 [26], 2018 [27], 2018 [28], 2020 [29] P1 P2 OPTW 2007 [4]  P 2011 [17]  P 2016 [30] P1 P2 The proposed model    P (D) TOPTW. 2011 [11]  P 2019 [13]    P 2015 [34], 2016 [35] * * 2018 [31] P1 P2 2018 [32], 2019 [33] P (D)…”

Section: Itinerary Selection From Pareto Frontmentioning

confidence: 99%

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Multi-Objective Trip Planning With Solution Ranking Based on User Preference and Restaurant Selection

2022

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The tourist trip design problem (TTDP) helps the trip planners, such as tourists, tour companies, and government agencies, automate their trip planning. TTDP solver chooses and sequences an optimal subset of point of interest (POIs), which adhere to the POIs attributes and tourist preferences, and then generates a travel itinerary that maximizes their pleasure. However, the traditional TTDP does not include the lunch period at a local restaurant, which causes the rest of the itinerary in the afternoon to shift, nor compulsory POIs that the trip planners must be included in the itinerary. Moreover, as tourism contributes to high greenhouse gas emissions, especially from its transportation, minimizing the itinerary's total distance is also considered. Unfortunately, this objective conflicts with the profit scores; no single itinerary can optimize both objectives simultaneously. Hence, the multi-objective technique and the results of non-dominated itineraries can be organized as a Pareto front. The trip planners can choose one suitable itinerary from the Pareto front based on their preferences. To address these real-world issues, we formulate a new variant of the well-known orienteering problem with time windows (OPTW) called the multi-objective orienteering problem with Time Windows, Restaurant Selection, and Compulsory POIs (MOPTW-RSCP). The proposed problem is provided with a mathematical formulation and two exact algorithms for solving them, i.e., greedy and branch-and-cut Pareto-based techniques. The algorithms' performance is tested against the Rattanakosin island (the old city of Bangkok) dataset. We conduct 24 test cases, and the computational results confirm the algorithms' efficiency.INDEX TERMS branch-and-cut algorithm, greedy algorithm, knee solution, low carbon tourism, multiobjective optimization, orienteering with time windows, point-of-interests, recommendation, solution ranking, tourist trip design problem

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Section: B Op For Ttdpmentioning

confidence: 99%

Section: Itinerary Selection From Pareto Frontmentioning

confidence: 99%

Multi-Objective Trip Planning With Solution Ranking Based on User Preference and Restaurant Selection

2022

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“…Based on the empirical results from literature [52], the elimination of sub-tours proposed by [19] presents better performance than other analyzed formulations. Therefore, according to the structure of the SLAUPR, it is proposed to replace Constraint (20) and perform a reformulation using constraints presented by [19].…”

mentioning

confidence: 99%

Solving Location Assignment and Order Picker-Routing Problems in Warehouse Management

Bolaños-Zuñiga,

Salazar-Aguilar,

Saucedo-Martínez

2023

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One of the critical warehousing processes is the order-picking process. This activity consists of retrieving items from their storage locations to fulfill the demand specified in the pick lists. Therefore, the storage location assignment affects the picking time and, consequently, reduces the operating costs of the warehouse. This work presents two alternative mixed-integer linear models and an adaptive multi-start heuristic (AMH) for solving the integrated storage location and picker-routing problem. The problem considers a warehouse with a general layout and precedence constraints for picking according to the products weight. Experimental work confirms the efficiency of the proposed reformulations since we found out a total of 334 tested instances and optimal solutions for 51 new cases and 62 new feasible solutions. The proposed AMH improved more than 29% of the best-known solutions and required an average execution time of 117 s. Consequently, our proposed algorithm is an attractive decision-making tool to achieve efficiency when solving practical situations in a warehouse.

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Recommendation rules to personalize itineraries for tourists in an unfamiliar city

Gasmi,

Soui,

Barhoumi

et al. 2024

Applied Soft Computing

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Formulations for the orienteering problem with additional constraints

Cited by 7 publications

References 32 publications

Multi-Objective Trip Planning With Solution Ranking Based on User Preference and Restaurant Selection

Multi-Objective Trip Planning With Solution Ranking Based on User Preference and Restaurant Selection

Solving Location Assignment and Order Picker-Routing Problems in Warehouse Management

Recommendation rules to personalize itineraries for tourists in an unfamiliar city

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