A Max–Min Ant System for the split delivery weighted vehicle routing problem

Tang, Jiafu; Ma, Yizhong; Guan, Jianguo; Yan, Chongjun

doi:10.1016/j.eswa.2013.06.068

Cited by 41 publications

(20 citation statements)

References 30 publications

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“…For price collection we have generated the data randomly. We have set the fixed cost 1000, second the prize Pi is randomly generated in [1,100]. The demand of all customers that must be satisfied is generated in [0.2, 0.6, and 0.8].…”

Section: Resultsmentioning

confidence: 99%

“…This problem has two objectives. [6] Minimization of total distance travelled by vehicles, and [1] Minimization of total cost. The solution of the PCVRP determines a set of delivery routes which satisfy the customer's requirement and obtain the maximum prize collected by visited customer and minimize the total cost of transportation travel from depot to the set of customers.…”

Section: Problem Formulationmentioning

confidence: 99%

“…The objective of the classical vehicle routing problem is to minimization the total cost while satisfying the customers demand. Many variants, which take into account additional constraints such as distance, capacity and time window, have been studied such as capacitated VRP [1]- [5]. In this paper we propose the Prize collecting vehicle routing problem (PCVRP).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A hybrid edge recombination approach to solve price collecting vehicle routing problem

Tiwari

Chang

Elangovan

et al. 2015

2015 International Conference on Control, Automation and Robotics

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In this paper, we consider a Prize Colleting Vehicle Routing Problem (PCVRP). Prize collecting Vehicle Routing Problem is a Variant of Vehicle routing Problem. One of the major concerns of the Prize collecting Vehicle routing problem is that all customers need not to be visited compulsory, but prize must be collected from each customer visited and a penalty has to be paid for every unvisited customer. To guarantee good customer satisfaction, the demand of all visited customers should reach a pre specified value. The objective of this paper is minimization of total distance and total cost of schedule by maximizing the total prize collected by each customers. We have proposed a Hybrid edge recombination approach to solve the PCVRP. To avoid the bias we compare the result with other well know evolutionary algorithm. Computational result shows that the proposed methodology has the promising result.

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Section: Resultsmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A hybrid edge recombination approach to solve price collecting vehicle routing problem

Tiwari

Chang

Elangovan

et al. 2015

2015 International Conference on Control, Automation and Robotics

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“…Then the procedure continues to select the insertion candidate (line 9-16). If * < 0 , create a new route with the corrosponding customer node, or otherwise insert the node into the related route (line [17][18][19][20][21][22]. Update the unrouted customer list (line 23-24).…”

Section: Initial Solutionmentioning

confidence: 99%

A Tabu Search Algorithm for the Discrete Split Delivery Vechicle Routing Problem

Pan¹,

Fu²,

Chen³

2019

JESA

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In the classic split delivery vehicle routing problem, the demands of customers can be split unconditionally into pieces of any size. However, in the real-world distribution system, the customer demands consist of a set of orders on different quantities of goods. During the distribution, demands can be spitted, but orders cannot. This paper considers the vehicle routing problem with split delivery by order. It formulates the problem as an integer linear programming model, creatively applies the binary to the decimal decoder method to represent the solution, proposes a heuristic order-insertion procedure, and develops a tabu search algorithm. Using the developed algorithm, this paper tests 25 benchmark instances. According to the test results, the algorithm proposed has a small gap with the best-known solutions, but has an advantage in computing time. Keywords: vehicle routing, discrete split delivery, ejection chains, tabu search VRP SDVRP DSDVRP Figure 1.

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“…For the past two decades, meta-heuristics have been developed to solve VRPs instead of traditional heuristics in order to find good solutions quickly. Later, many researchers have frequently used meta-heuristics (Birim, 2016;Brandão, 2009Brandão, , 2011Kalayci & Kaya, 2016;Lai et al, 2016;Tang et al, 2013;Tavakkoli-Moghaddam et al, 2007) such as Tabu search (TS), Ant colony optimization (ACO), Simulated annealing (SA) and Genetic algorithm (GA) to solve various VRPs in some real world problems. Nowadays there are many new meta-heuristics that occur in the literature such as differential evolution (DE) and Bee colony (BC).…”

Section: Related Literaturementioning

confidence: 99%

Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

Wichapa¹,

Khokhajaikiat²

2018

10.5267/j.ijiec

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Infectious waste disposal remains one of the most serious problems in the medical, social and environmental domains of almost every country. Selection of new suitable locations and finding the optimal set of transport routes for a fleet of vehicles to transport infectious waste material, location routing problem for infectious waste disposal, is one of the major problems in hazardous waste management. Determining locations for infectious waste disposal is a difficult and complex process, because it requires combining both intangible and tangible factors. Additionally, it depends on several criteria and various regulations. This facility location problem for infectious waste disposal is complicated, and it cannot be addressed using any standalone technique. Based on a case study, 107 hospitals and 6 candidate municipalities in UpperNortheastern Thailand, we considered criteria such as infrastructure, geology and social & environmental criteria, evaluating global priority weights using the fuzzy analytical hierarchy process (Fuzzy AHP). After that, a new multi-objective facility location problem model which hybridizes fuzzy AHP and goal programming (GP), namely the HGP model, was tested. Finally, the vehicle routing problem (VRP) for a case study was formulated, and it was tested using a hybrid genetic algorithm (HGA) which hybridizes the push forward insertion heuristic (PFIH), genetic algorithm (GA) and three local searches including 2-opt, insertion-move and interexchange-move. The results show that both the HGP and HGA can lead to select new suitable locations and to find the optimal set of transport routes for vehicles delivering infectious waste material. The novelty of the proposed methodologies, HGP, is the simultaneous combination of relevant factors that are difficult to interpret and cost factors in order to determine new suitable locations, and HGA can be applied to determine the transport routes which provide a minimum number of vehicles and minimum transportation cost under the actual situation efficiently in this case.

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A Max–Min Ant System for the split delivery weighted vehicle routing problem

Cited by 41 publications

References 30 publications

A hybrid edge recombination approach to solve price collecting vehicle routing problem

A hybrid edge recombination approach to solve price collecting vehicle routing problem

A Tabu Search Algorithm for the Discrete Split Delivery Vechicle Routing Problem

Solving a multi-objective location routing problem for infectious waste disposal using hybrid goal programming and hybrid genetic algorithm

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