Problem instances for outbound truck loading and scheduling problem
DOI10.5281/zenodo.5504138Zenodo5504138MaRDI QIDQ6726286
Dataset published at Zenodo repository.
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Publication date: 13 September 2021
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The following dataset contains problem instances for the outbound truck scheduling and loading problem, which are proposed in the work Giorgi Tadumadze Simon Emde (2021): Loading and scheduling outbound trucks at a dispatch warehouse. IISE Transactions, DOI: 10.1080/24725854.2021.1983923. The problem instances are stored in table instances, where columns of tables can be interpreted as follows: ID: running index; name: instance name, specifying the number of items \(m\), number of trucks \(n\), value of parameter \(\alpha\), [value of parameter \(\Delta\)], and the width of trucks time windows; O: number of served OEMs; m: number of items; n: number of trucks; Q: total number of available workers; D: total number of available dock doors; w_i: vector with \(m\) elements: the \(i\)-th element corresponds to the size (required space) of item \(i\); d_i: vector with \(m\)elements: the \(i\)-th element corresponds to the deadline of item \(i\); r_i: vector with \(m\)elements: the \(i\)-th element corresponds to the relative importance (penalty cost per time unit of earliness) of item \(i\); c_j: vector with \(n\)elements: the \(j\)-th element corresponds to the capacity of truck \(j\); a_j: vector with \(n\)elements: the \(j\)-th element corresponds to the earliest possible departure time of truck \(j\); b_j: vector with \(n\)elements: the \(j\)-th element corresponds to the latest possible departure time of truck \(j\); q_i: vector with \(m\)elements: the \(i\)-th element corresponds to the number of required workers to prepare and load item \(i\); rho_i: vector with \(m\)elements: the \(i\)-th element corresponds to the handling time of item \(i\); B_i: \(m \times n\) matrix: each entry in \(j\)-th column and \(i\)-th row corresponds to the binary parameter which has a value 1 if set of available trucks \(B_i\) contains truck \(j\) (i.e., if truck \(j\) departs towards the OEM, who ordered item); 0 otherwise; The first 270 entries (ID between 1-270) contain OTSLP instances with different instance sizes, used for the computational performance experiments (Section 5.1). The following 100 entries (ID between 271-370) contain 40 OTSLP instances with the varying time window width for each truck (ID between 271-310), 30 OTSLP instances with the varying level of available workers (ID between 311-340), and 30 OTSLP instances with the varying level of available dock doors (ID between 341-370), used for the managerial inside experiments (Section 5.2). The detailed computational results for each instance and solution approach are reported in tables, which are named with the following convention: results_approach. Specifically, we report the required computational runtime in CPU seconds, status of the found solution (Optimal, Infeasible, Feasible / AbortTimeLim), as well as the best found upper (and lower) bound in columns runtime, status, UB and LB.
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