Exact and heuristic approaches to solve the Internet shopping optimization problem with delivery costs

López-Locés, Mario C.; Musiał, Jędrzej; Pecero, Johnatan E.; Fraire-Huacuja, Héctor J.; Błażewicz, Jacek; Bouvry, Pascal

doi:10.1515/amcs-2016-0028

Cited by 13 publications

(3 citation statements)

References 39 publications

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“…• ISOP with two discounting functions (both based on the total amount of money spent in a shop) including price and shipping costs discounts [6] Further evaluation of the Internet Shopping Optimization Problem with its optimiza-tion can be found in [20,29]. Furthermore, some motivations and similarities can be found in research concerning stock market, namely considering multi-period portfolio optimization problem.…”

Section: Related Workmentioning

confidence: 99%

Cloud Brokering with Bundles: Multi-objective Optimization of Services Selection

Musiał

Kieffer

Guzek

et al. 2019

Foundations of Computing and Decision Sciences

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Cloud computing has become one of the major computing paradigms. Not only the number of offered cloud services has grown exponentially but also many different providers compete and propose very similar services. This situation should eventually be beneficial for the customers, but considering that these services slightly differ functionally and non-functionally -wise (e.g., performance, reliability, security), consumers may be confused and unable to make an optimal choice. The emergence of cloud service brokers addresses these issues. A broker gathers information about services from providers and about the needs and requirements of the customers, with the final goal of finding the best match. In this paper, we formalize and study a novel problem that arises in the area of cloud brokering. In its simplest form, brokering is a trivial assignment problem, but in more complex and realistic cases this does not longer hold. The novelty of the presented problem lies in considering services which can be sold in bundles. Bundling is a common business practice, in which a set of services is sold together for the lower price than the sum of services’ prices that are included in it. This work introduces a multi-criteria optimization problem which could help customers to determine the best IT solutions according to several criteria. The Cloud Brokering with Bundles (CBB) models the different IT packages (or bundles) found on the market while minimizing (maximizing) different criteria. A proof of complexity is given for the single-objective case and experiments have been conducted with a special case of two criteria: the first one being the cost and the second is artificially generated. We also designed and developed a benchmark generator, which is based on real data gathered from 19 cloud providers. The problem is solved using an exact optimizer relying on a dichotomic search method. The results show that the dichotomic search can be successfully applied for small instances corresponding to typical cloud-brokering use cases and returns results in terms of seconds. For larger problem instances, solving times are not prohibitive, and solutions could be obtained for large, corporate clients in terms of minutes.

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Section: Related Workmentioning

confidence: 99%

Cloud Brokering with Bundles: Multi-objective Optimization of Services Selection

Musiał

Kieffer

Guzek

et al. 2019

Foundations of Computing and Decision Sciences

Self Cite

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“…Next, three heuristic algorithms, based on greedy and forecasting approaches, are presented and tested. The MinMin and the cellular processing-based heuristic algorithms for ISOP with delivery costs and without any discounts have been investigated by Lopez-Loces et al (2016), where the problem is stated using the integer linear programing model. Another version, referred to as budgeted ISOP (B-ISOP), takes into account a customer’s budget (Marszałkowski, 2015).…”

Section: Problem Formulationmentioning

confidence: 99%

Heuristic algorithms for the Internet shopping optimization problem with price sensitivity discounts

Józefczyk

Lawrynowicz

2018

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Purpose Rapid advancements in internet technology have made it possible to develop electronic commerce in general and internet shopping in particular. Easy access to a vast number of existing internet stores enables buyers to customize their shopping processes to minimize the total purchase cost. This paper aims to investigate a novel internet shopping problem, which consists of the diversification of a given list of products to buy among many stores and to use discounts offered by the stores. Design/methodology/approach The adequate discrete optimization problem referred to as internet shopping optimization problem with price sensitivity discounts (ISOPwD) is investigated, which turned out to be strongly nondeterministic polynomial (NS)-hard. Two heuristic solution algorithms have been derived using the tabu search (TS) and the simulated annealing (SA) metaheuristics for having a solution in a reasonable time. The algorithms have been assessed via computational experiments, and they have been compared with another algorithm known from the literature that has been elaborated for a simpler version of ISOPwD. Findings The conducted evaluation has shown the advantage of both heuristic algorithms on the algorithm known from the literature. Moreover, the TS-based algorithm outperformed the other one in terms of the total cost incurred by customers and the computational time. Research limitations/implications The special primary piecewise linear discounting function is only taken into account. Other possible discounts connected, for example, with bundles of products and (or) coupons are not considered. Practical implications The elaborated algorithms can be recommended for internet shopping providers who want to introduce the ability to search a cost-optimized set of products in their databases or for applications that combine offers from various online retailers, e.g. internet price comparison services and auction sites. Originality/value The novelty of considered ISOPwD, in comparison with similar problems discussed in the literature, deals with an arbitrary number of purchased products, the possibility to buy an identical product in different stores and the consideration of the weight, the amount and the availability of goods as parameters of ISOPwD.

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“…These variants of the problem include price sensitive discounts [5,4,25] and dual discount functions [6] that offer discounts over the total price of a given shopping list and the latter adds a discount over the total delivery cost based on the total cost of the products, a practice that is common among retail and online stores. Further evaluation of the ISOP with its optimization can be found in [20] and [24].…”

Section: Literature Reviewmentioning

confidence: 99%

Trustworthy Online Shopping with Price Impact

Musiał

López-Locés

2017

Foundations of Computing and Decision Sciences

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Abstract. Internet shopping is one of the main pillars of electronic commerce. According to the literature, the Internet Shopping Optimization Problem (ISOP) has been defined in order to optimize the global cost of online purchase, taking into account both the cost of products and shipping. In this study, it was decided to propose and analyze a very interesting, and really substantial, extension of the ISOP. Namely, trust factors were subjected to careful analysis from the customer point of view. The analysis is based on a specially prepared questionnaire, supplemented by the information from the literature and our own observations. Thus, it was possible to propose a definition of a new mathematical model of the problem, and to prove its affiliation to the class of strongly NP-hard problems. In addition, the heuristic algorithm is proposed, which can be used to solve the problem.

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Exact and heuristic approaches to solve the Internet shopping optimization problem with delivery costs

Cited by 13 publications

References 39 publications

Cloud Brokering with Bundles: Multi-objective Optimization of Services Selection

Cloud Brokering with Bundles: Multi-objective Optimization of Services Selection

Heuristic algorithms for the Internet shopping optimization problem with price sensitivity discounts

Trustworthy Online Shopping with Price Impact

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