A Pareto-metaheuristic for a bi-objective winner determination problem in a combinatorial reverse auction

Abstract

The bi-objective winner determination problem (2WDP-SC) of a combinatorial procurement auction for transport contracts comes up to a multi-criteria set covering problem. We are given a set B of bundle bids. A bundle bid b ∈ B consists of a bidding carrier c b , a bid price p b , and a set τ b of transport contracts which is a subset of the set T of tendered transport contracts. Additionally, the transport quality q t,c b is given which is expected to be realized when a transport contract t is executed by a carrier c b . The task of the auctioneer is to find a set X of winning bids (X ⊆ B), such that each transport contract is part of at least one winning bid, the total procurement costs are minimized, and the total transport quality is maximized. This article presents a metaheuristic approach for the 2WDP-SC which integrates the greedy randomized adaptive search procedure, large neighborhood search, and self-adaptive parameter setting in order to find a competitive set of non-dominated solutions. The procedure outperforms existing heuristics.Computational experiments performed on a set of benchmark instances show that, for small instances, the presented procedure is the sole approach that succeeds to find all Pareto-optimal solutions. For each of the large benchmark instances, according to common multi-criteria quality indicators of the literature, it attains new best-known solution sets.

Transport Planning for Procurement and Distribution

“…But this may alternatively be a result of a combinatorial procurement auction for transport contracts (see Buer and Kopfer 2014;Sheffi 2004), which is based on the bids of carriers for transportation lanes or transports to specific delivery areas.…”

Modern Optimization and Simulation Methods in Managerial and Business Economics: A Review

“…Most decision-making processes can be formulated as optimization problems. Among methods to address these problems, one can mention game theory (Sadeghi and Zandieh 2011), metaheuristics (Buer and Kopfer 2014), neural networks (Göçken et al 2016), simulation (Ivanov 2017), fuzzy sets (Graham et al 2019), econometrics (Longo et al 2017), and forecasting (Al Shehhi and Karathanasopoulos 2020). Linear programming (LP) (Vanderbei et al 2015) constitutes one of the most classical and popular approaches.…”

A mixed procurement model for humanitarian relief chains

“…It has already been utilized by several HOs such as Fritz Institute and FEMA (Alp Ertem and Buyurgan, 2011). Although procurement auctions have frequently been used successfully in the commercial setting (Iftekhar et al , 2013; Buer and Kopfer, 2014; Hsieh and Lin, 2012), their applications in the disaster relief setting need a thorough and practical investigation. The most important reason for applying reverse auctions in the relief procurement is to utilize the available inventory of suppliers (especially regarding scarce resources) more efficiently for humanitarian logistics.…”