Item Listing Optimization for E-Commerce Websites Based on Diversity

Abstract

For e-commerce websites, deciding the manner in which items are listed on webpages is an important issue because it can dramatically affect item sales. One of the simplest strategies of listing items to improve the overall sales is to do so in a descending order of sales or sales numbers. However, in lists generated using this strategy, items with high similarity are often placed consecutively. In other words, the generated item list might be biased toward a specific preference. Therefore, this study employs penalties for items with high similarity being placed next to each other in the list and transforms the item listing problem to a quadratic assignment problem (QAP). The QAP is well-known as an NP-hard problem that cannot be solved in polynomial time. To solve the QAP, we employ quantum annealing (QA), which exploits the quantum tunneling effect to efficiently solve an optimization problem. In addition, we propose a problem decomposition method based on the structure of the item listing problem because the quantum annealer we use (i.e., D-Wave 2000Q) has a limited number of quantum bits. Our experimental results indicate that we can create an item list that considers both sales and diversity. In addition, we observe that using the problem decomposition method based on a problem structure can lead to a better solution with the quantum annealer in comparison with the existing problem decomposition method.

Efficient partition of integer optimization problems with one-hot encoding

“…However, the extracted subproblem still contains unfeasible solutions, and the penalty term remains in the cost function of the subproblem. This partitioning method is similar to that developed in the literature 31 . While the extracted subproblems are embedded usnig complete-graph embedding in the literature 31 algorithm, which we developed in a previous study 45 .…”

“…This partitioning method is similar to that developed in the literature 31 . While the extracted subproblems are embedded usnig complete-graph embedding in the literature 31 algorithm, which we developed in a previous study 45 . Details on how to achieve a multivalued partition using the subproblemembedding algorithm are explained in the Methods section.…”

Solving Constrained Slot Placement Problems Using an Ising Machine and Its Evaluations

“…The sub-optimal solutions are usually obtained by using simulated annealing (SA), branch and bound methods, genetic algorithm and tabu search [23], [24]. In addition, the performance of quantum annealing for quadratic assignment problems was investigated [25]. Recently an Ising model mapping of slot-placement problem was proposed [18].…”

Amoeba-inspired analog electronic computing system integrating resistance crossbar for solving the travelling salesman problem

“…Combinatorial optimization problems are computationally demanding tasks appearing in various practical applications, such as optimization of traffic flow, path planning, nurse scheduling and advertisement allocation 1 – 4 . Often these problems become intractable for conventional von Neumann-type computers, such as general-purpose CPUs; they need to evaluate an enormous number of candidate solutions in a serial manner, where the number of the candidates grows exponentially with the problem size, leading to “combinatorial explosion”.…”